Design and Implementation of Intelligent Truck Based on Azure Kinect

In recent years, due to the impact of COVID-19, the market prospect of non-contact handling has improved and the development potential is huge. This paper designs an intelligent truck based on Azure Kinect, which can save manpower and improve efficiency, and greatly reduce the infection risk of medical staff and community workers. The target object is visually recognized by Azure Kinect to obtain the center of mass of the target, and the GPS and Kalman filter are used to achieve accurate positioning. The 4-DOF robot arm is selected to grasp and transport the target object, so as to complete the non-contact handling work. In this paper, different shapes of objects are tested. The experiment shows that the system can accurately complete the positioning function, and the accuracy rate is 95.56%. The target object recognition is combined with the depth information to determine the distance, and the spatial coordinates of the object centroid are obtained in real time. The accuracy rate can reach 94.48%, and the target objects of different shapes can be recognized. When the target object is grasped by the robot arm, it can be grasped accurately according to the depth information, and the grasping rate reaches 92.67%. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

THE MODERNIZATION OF THE STREET VENDORS SERVICES DURING THE COVID-19 PANDEMIC-THE FOOD TRUCKS PHENOMENON

Since Covid-19 began to spread, street food vendors' activities have raised many issues. The lockdown of restaurants and coffees to control the pandemic in the cities appeared to be a vital response to the city's dramatic procedures. Therefore, the development of street food vending in the form of food trucks was one of these activities that responded to the Covid-19 pandemic and became a phenomenon during the lockdown period in Bahrain. Food trucks are scattered in many areas serving the community by providing food services. But the unplanned location of some food trucks negatively affects the quality of the city's open spaces causing problematic urban changes and producing traffic jams;moreover, it needs to consider the landscape architecture elements. Therefore, the study explains the term street food vendors and their hazards due to COVID-19 circumstances, followed by illustrating the regulation that manages food truck activities. Then it analyzes the risks resulting from some case studies. The study ends with presenting design guidelines to improve the criteria of the site location of the food truck activities. These guidelines will assist the municipalities in avoiding any possible negative impacts and the haphazard positions of these food trucks in cities. © 2023, Jomard Publishing. All rights reserved.

Using AI and ML to predict shipment times of therapeutics, diagnostics and vaccines in e-pharmacy supply chains during COVID-19 pandemic

PurposeThis paper aims to address the pressing problem of prediction concerning shipment times of therapeutics, diagnostics and vaccines during the ongoing COVID-19 pandemic using a novel artificial intelligence (AI) and machine learning (ML) approach.Design/methodology/approachThe present study used organic real-world therapeutic supplies data of over 3 million shipments collected during the COVID-19 pandemic through a large real-world e-pharmacy. The researchers built various ML multiclass classification models, namely, random forest (RF), extra trees (XRT), decision tree (DT), multilayer perceptron (MLP), XGBoost (XGB), CatBoost (CB), linear stochastic gradient descent (SGD) and the linear Naïve Bayes (NB) and trained them on striped datasets of (source, destination, shipper) triplets. The study stacked the base models and built stacked meta-models. Subsequently, the researchers built a model zoo with a combination of the base models and stacked meta-models trained on these striped datasets. The study used 10-fold cross-validation (CV) for performance evaluation.FindingsThe findings reveal that the turn-around-time provided by therapeutic supply logistics providers is only 62.91% accurate when compared to reality. In contrast, the solution provided in this study is up to 93.5% accurate compared to reality, resulting in up to 48.62% improvement, with a clear trend of more historic data and better performance growing each week.Research limitations/implicationsThe implication of the study has shown the efficacy of ML model zoo with a combination of base models and stacked meta-models trained on striped datasets of (source, destination and shipper) triplets for predicting the shipment times of therapeutics, diagnostics and vaccines in the e-pharmacy supply chain.Originality/valueThe novelty of the study is on the real-world e-pharmacy supply chain under post-COVID-19 lockdown conditions and has come up with a novel ML ensemble stacking based model zoo to make predictions on the shipment times of therapeutics. Through this work, it is assumed that there will be greater adoption of AI and ML techniques in shipment time prediction of therapeutics in the logistics industry in the pandemic situations.

Impact of COVID-19 Prevention and Control Measures on Expressway Transportation in Guangdong-Hong Kong-Macao Greater Bay Area

Under the background of normalized COVID-19 prevention and control, regional epidemics occur frequently in China. How to quantify the impact of COVID-19 prevention and control measures on economic operation and passenger and freight transportation has become an urgent problem. To this end, we design a calculation method for expressway transportation indicators, propose the level and stage division process of COVID-19 prevention and control measures, and then establish a difference-in-difference model to further analyze their impact on expressway transportation indicators. Taking major cities in the Guangdong-Hong Kong-Macao Greater Bay Area as an example, case studies are conducted based on the expressway toll data and COVID-19 prevention and control information from May 2020 to April 2022. The results show that in the level I (strengthened) stage, the passenger vehicle flow has dropped significantly, the drop in each case is between 8% and 27%, and the freight indicators have not changed significantly. In Shenzhen and Dongguan, both passenger and freight indicators dropped sharply in the level II (strict) stage. Passenger vehicle flow in the two cities dropped by 46.3% and 33.7%, and truck flow by 42.7% and 27.6%, respectively, and cargo and turnover decreased as much as truck flow. The average inter- city distance of expressway passenger cars has a downward trend under the level I stage, but under the level II stage, the average inter-city distance of passenger cars and trucks has increased significantly. This study can provide a certain reference value for the formulation and implementation of COVID-19 prevention and control measures in cities and urban agglomerations. © 2022 Science Press. All rights reserved.

Guest editorial: NOFOMA 2021 conference special issue

In the first paper, "Customer experience dimensions in last-mile delivery: an empirical study on unattended home delivery”, John Olsson, Daniel Hellström and Yulia Vakulenko examine the substantial impact of the pandemic on home delivery of groceries and other online purchases. To fill this gap, the authors have collected primary and secondary data from seven countries to explore how policymakers employed different supply chain risk management strategies for handling shortage risks in their paracetamol supply chains before and during COVID-19. [...]we are very thankful for the time and effort that is put in by the reviewers in this special issue, the support from IJPDLM editorial team and the invaluable guidance from Professor Chee Yew Wong as chief editor, who helped us during the whole process.

The role of innovativeness and supply chain agility in the Australian service industry: a dynamic capability perspective

PurposeThis paper aims to investigate the conditional indirect effect of innovativeness on performance via supply chain agility (SCA) in the service industry at higher and lower collaborative relationships.Design/methodology/approachThe hypothesised model is operationalised with survey data from 245 Australian service firms collected via LinkedIn and analysed using structural equation modelling and fuzzy set qualitative comparative analysis (fsQCA).FindingsThe analysis found that SCA significantly mediates the relationship between innovativeness and performance. Further, the conditional indirect effect of innovativeness on performance via SCA was significant when the collaborative relationship was high. Results also revealed that a configuration of both innovativeness and agility better predicts performance.Originality/valueThis study is an early attempt to investigate SCA in service industries by scrutinizing SCA from an innovative point of view. While previous studies have demonstrated the role of innovativeness in enhancing a firm's performance, this study explores this link further by investigating the conditional indirect effect of innovativeness on performance via SCA at different levels of collaborative relationships.

Strategic responses to the pandemic: a case study of the US department store industry

PurposeThe study focuses on (1) the success of three strategies employed during the pandemic – two "persevering” strategies, curbside pickup and return window extension and one innovative strategy, virtual try-on technology and (2) whether the strategies are likely to be successful in the post-pandemic world.Design/methodology/approachThe authors utilize a panel dataset containing 17 department store chains in the US The panel includes weekly sales by the retailers at the city level from 2018 to 2021, encompassing both a pre-COVID-19 period and a period during the pandemic. A two-way fixed effects model, including retailer-city fixed effects and year-week fixed effects, is used to estimate department store sales.FindingsThe authors find that the two persevering strategies offset the negative impact of government-imposed containment and health measures on sales performance. On the other hand, the innovative strategy is more effective with a low level of containment and health measures, leading to our observation that virtual try-on may be more sustainable than the other two strategies in a post-pandemic environment.Originality/valueThis paper makes the following contributions: First, the authors contribute to the literature on strategies that may be used to respond to crises. Second, the authors contribute to the retail management literature, assessing the impact of the three retail strategies on department store sales. Finally, the authors compare the impact on sales of the two persevering strategies to the innovative strategy and conclude that a mix of these types of strategies may be most effective at generating short-term sales during a crisis and longer-term sales post crisis.

Supply chain risk management strategies in normal and abnormal times: policymakers' role in reducing generic medicine shortages

PurposeThis paper links supply chain risk management to medicine supply chains to explore the role of policymakers in employing supply chain risk management strategies (SCRMS) to reduce generic medicine shortages.Design/methodology/approachUsing secondary data supplemented with primary data, the authors map and compare seven countries' SCRMS for handling shortage risks in their paracetamol supply chains before and during the first two waves of the COVID-19 pandemic.FindingsConsistent with recent research, the study finds that policymakers had implemented few SCRMS specifically for responding to disruptions caused by COVID-19. However, shortages were largely avoided since multiple strategies for coping with business-as-usual disruptions had been implemented prior to the pandemic. The authors did find that SCRMS implemented during COVID-19 were not always aligned with those implemented pre-pandemic. The authors also found that policymakers played both direct and indirect roles.Research limitations/implicationsCombining longitudinal secondary data with interviews sheds light on how, regardless of the level of preparedness during normal times, SCRMS can be leveraged to avert shortages in abnormal times. However, the problem is highly complex, which warrants further research.Practical implicationsSupply chain professionals and policymakers in the healthcare sector can use the findings when developing preparedness and response plans.Social implicationsThe insights developed can help policymakers improve the availability of high-volume generic medicines in (ab)normal times.Originality/valueThe authors contribute to prior SCRM research in two ways. First, the authors operationalize SCRMS in the medicine supply chain context in (ab)normal times, thereby opening avenues for future research on SCRM in this context. Second, the authors develop insights on the role policymakers play and how they directly implement and indirectly influence the adoption of SCRMS. Based on the study findings, the authors develop a framework that captures the diverse roles of policymakers in SCRM.

Resilience in healthcare supply chains: a review of the UK's response to the COVID19 pandemic

PurposeThe purpose of this explorative research is to analyse the resilience of the United Kingdom's (UK) healthcare supply chains from a customer's perspective in the light of the coronavirus pandemic.Design/methodology/approachUsing the capabilities of preparedness, robustness, recovery and adaptability as the foundational percept for supply chain resilience, 22 healthcare professionals in 17 of the UK's National Health Scheme (NHS) Trusts were interviewed to explore their personal and organisational approaches adopted relative to the provision of eye protection, gloves, gowns, aprons, masks and respirators. The Dynamic Capabilities View is mapped to the resilience capabilities and used to analyse the data from a transformational supply chain research perspective.FindingsThe supply chains were largely unprepared, which was not particularly surprising even though the availability of gloves was significantly better compared to the other personal protective equipment (PPE). Techniques adopted to ensure robustness and recovery revealed the use of unsanctioned methods such as extended use of PPE beyond recommended use, redefinition of guidelines, protocols and procedures by infection control and the use of expired PPE – all of which compromised customer well-being.Research limitations/implicationsAs the paper views resilience through the lens of customers, it does not provide the perspectives of the supply chain practitioners as to the reasons for the findings and the challenges within these supply chains.Practical implicationsThe compromise of the well-being of healthcare workers due to the vulnerabilities of healthcare supply chains is highlighted to managers and prescriptions for post-disruption adaptability are made.Originality/valueThis paper introduces transformative research to supply chain resilience research by uniquely looking at resilience from the customers' well-being perspective.

A Mobile Based Garbage Collection System

Garbage disposal and collection is an ongoing global crisis amplified by the increasing world population, lack of funds and public awareness, and recently because of the Covid-19 pandemic. Information Technology can be utilized as a solution for the existing garbage collection methods that are old-fashioned, time-consuming, and energy-consuming due to the lack of a unified and consistent system that incorporates all the parties involved in garbage production and collection. A mobile-based garbage collection system is proposed to overcome the issues aforementioned through route and schedule optimization, AI chatbot, and optimized GPS tracking. The route and schedule optimization is achieved through vehicle routing problem with time windows(VRPTW) with synchronization and precedence that was optimized using LNS;the total travel cost went from 172 minutes to 144 minutes. The AI chatbot feature facilitates reporting garbage collection issues and complaints and enquiring about waste management tips (reduce, recycle, and reuse tips) to be used at home. The most prominent role of developing this AI chatbot is replacing the manual process of reporting garbage collection issues in Sri Lanka with an efficient and interactive way. The chatbot has waste management tips Q and A. In Optimized GPS Tracking, the user can use the map to find the nearest garbage disposal place based on the type of rubbish they generate. The truck driver can find the optimal path to the closest current garbage disposal centres and public trash bins and view the location of Homeowners on the map. The optimized path between two points is displayed based on distance, time, and fuel consumption. The main goal of the component is to show the location of garbage disposal bins and the optimal paths for truck drivers using Linear regression and the Node2vec algorithm. © 2022 IEEE.

New Insights into the Ferry Business in the Turbulent Environment

Purpose: The purpose of the article is to analyse the challenges faced by the ferry operators and discuss what activities they take when operating in a turbulent environment resulted from COVID-19 pandemic and effects of economic situation of the Baltic States. Design/Methodology/Approach: Several research methods were applied, literature review, data exploration method, desk research and in-depth interviews. Findings: Research revealed lack of current publications on ferry business activity in the context of dynamic and changing drivers influencing the ferry shipowners during last three years. Practical Implications: The article emphasizes that the activities undertaken by the ferry operators allow to operate despite the negative external factors and what should be undertaken to minimalize the adverse effects. Originality/Value: The literature researching the ferry shipping is not extensive, it includes a relatively small number of scientific articles and monographs. Most of the research concerns the last decade. However, there are no current studies on the functioning of the ferry sector, the activity of which in the last three years was significantly influenced by changes that occurred in the external environment. The article fills the research gap in the ferry sector studies.

Fifteen Years of Community Exposure to Heavy-Duty Emissions: Capturing Disparities over Space and Time.

Disparities in exposure to traffic-related air pollution have been widely reported. However, little work has been done to simultaneously assess the impact of various vehicle types on populations of different socioeconomic/ethnic backgrounds. In this study, we employed an extreme gradient-boosting approach to spatially distribute light-duty vehicle (LDV) and heavy-duty truck emissions across the city of Toronto from 2006 to 2020. We examined associations between these emissions and different marginalization indices across this time span. Despite a large decrease in traffic emissions, disparities in exposure to traffic-related air pollution persisted over time. Populations with high residential instability, high ethnic concentration, and high material deprivation were found to reside in regions with significantly higher truck and LDV emissions. In fact, the gap in exposure to traffic emissions between the most residentially unstable populations and the least residentially unstable populations worsened over time, with trucks being the larger contributor to these disparities. Our data also indicate that the number of trucks and truck emissions increased substantially between 2019 and 2020 whilst LDVs decreased. Our results suggest that improvements in vehicle emission technologies are not sufficient to tackle disparities in exposure to traffic-related air pollution.

Guest editorial: Deepening the theoretical understanding of agility and resilience in global supply chains

Specifically, they address the following broad topics: the role of organizational intangible resources in facilitating supply chain resilience, the application of resilience to service recovery, the long-term view of supply chain resilience, the multifaceted effect of supply base complexity on supply chain agility and resilience, and the application of agility to improve customer performance. Using a cross-sectional questionnaire, the authors collected data from 180 medium-to senior-level managers and found that organizational learning has a positive impact on supply chain resilience, while organizational innovativeness and organizational agility mediate this relationship. To illustrate, the value of returns in the USA amounted to $400 bn in 2020 (National Retail Federation, 2021). [...]a recent customer survey by United Parcel Service showed that about 58% of consumers are not satisfied with the service they encounter when returning products to retailers (Warren, 2020). Furthermore, in keeping with the focus of the special issue on the theoretical underpinnings of supply chain resilience, the authors draw on procedural justice theory to also explore the mediating roles of procedural justice (i.e. the policies and procedures used to offer the desired customer outcome) and interactional justice (i.e. the customer's interpersonal treatment during service recovery) in the relationship between service recovery resilience on the one hand and customer satisfaction and customer loyalty on the other.

Guest editorial: The “new normal”: rethinking supply chains during and post-COVID-19 global business environment

[...]supply sources were disconnected and production facilities were shut down, creating shortages at the retail/customer end and surpluses at the supplier/manufacturer end (Deloitte, 2020). [...]the COVID-19 outbreak has tested the resilience of global supply chains and has highlighted many challenges. With the substantial magnitude of the COVID-19 disruptions, supply chain resilience has received significant attention from researchers, practitioners, governments and industries (Remko, 2020;Scholten et al., 2020). [...]it was not surprising to see that the accepted papers in this special issue have addressed one or more aspects of supply chain resilience. 2.2 Supply chain resilience Resilience is defined as the way of getting back to normal or “new normal” conditions by destabilising or minimising external shocks or disturbances or threats (Luthar and Cicchetti, 2000). Examples of avoidance in a new normal environment are the selection of alternative suppliers from diversified regions, use of multiple suppliers to avoid the supply risks, having multiple buyers to avoid buyer disruption, having alternative production facilities and maintaining better collaboration and partnership with third-party logistics service providers to prevent the negative impact of supply chain disruption within the supply chain (Chowdhury and Quaddus, 2017;Ivanov et al., 2018;Hosseini et al., 2019;Kaufman, 2020).

Multilevel Mixed-Effects Models to Identify Contributing Factors on Freight Vehicle Crash Severity

Freight vehicle crashes are more serious than regular vehicle crashes because they are likely to lead to major damage and injury once they occur;therefore, countermeasures are needed. The fatality rate from freight vehicle crashes is 1.5 times higher than that of all other accidents, and the death rate from expressway freight vehicle crashes continues to increase. In this study, the ten-freight-vehicle crash severity models (the ordered logit and probit model, the multinomial logit and probit model, mixed-effects logit and probit model, random-effects ordered logit and probit model, and multilevel mixed-effects ordered logit and probit model) are used to analyze the freight vehicle crash severity factors. The model was constructed using data collected from expressways over eight years, and 13 factors were derived to increase the severity of crashes and 7 factors to reduce the severity of crashes. As a result of comparing the 10 constructed models using AIC and BIC, the multilevel mixed-effects ordered probit model showed the best performance. It is expected that it can contribute to improving the safety of freight vehicles in the expressway section by utilizing factors related to the severity of crashes derived from this study.

When Three Is Better than Two: How Culture Can Bridge Collaboration in Globally Distributed Teams

[...]of the COVID-19 pandemic, many managers have stopped travelling and have started leading online GDTs for the first time. [...]the Brazilian team was given the responsibility of developing the first medium-sized, heavy-duty truck (the Volvo VM), working alongside the French and Swedish teams. [...]research has been developing ways to explain these processes inside GDTs (Cagiltay et al., 2015;Hoch & Kozlowski,20l4). According to the authors,'in the absence of communication norms, team members resorted to using the practices prevalent in their local setting' (Malhotra et al., 2007, p. 62).

The Spatio-Temporal Pattern Air Quality During Pandemic in Batang District Based On Google Earth Engine Approach

Resilient and sustainable infrastructure development is necessary to support innovative industries. Batang Regency is one of the regencies on the island of Java that is currently intensively building infrastructure to prepare the Batang Integrated Industrial Estate (KITB). Therefore, the government also supports this Presidential Regulation Number 79 of 2019 and Presidential Regulation No. 109 of 2020, which observes the development of the Batang Regency Integrated Industrial Estate. When the Covid-19 pandemic hit Indonesia in early March 2020, many changes occurred in the infrastructure development process. Some infrastructure has been temporarily suspended due to the Covid-19 pandemic. Of course, this will be followed by a decrease in emissions due to limited movement and infrastructure development there. This study wants to analyze how the air changes from the beginning of the pandemic until 2022. The air changes will be seen by monitoring NO2 formed from emissions from cars, trucks, buses, and industry. This is intended to measure/identify how the pattern of air changes considering the Batang District is passed by the Pantura road so that there is a high intensity of movement. The method used is spatial analysis with google earth engine Sentinel 5P images. The result of this study can provide input monitoring emissions related to technological advances in the era of open data.

Pathways to Carbon-Free Transport in Germany until 2050

The transport sector has to be widely decarbonized by 2050 to reach the targets of the Paris Agreement. This can be performed with different drive trains and energy carriers. This paper explored four pathways to a carbon-free transport sector in Germany in 2050 with foci on electricity, hydrogen, synthetic methane, or liquid synthetic fuels. We used a transport demand model for future vehicle use and a simulation model for the determination of alternative fuel vehicle market shares. We found a large share of electric vehicles in all scenarios, even in the scenarios with a focus on other fuels. In all scenarios, the final energy consumption decreased significantly, most strongly when the focus was on electricity and almost one-third lower in primary energy demand compared with the other scenarios. A further decrease of energy demand is possible with an even faster adoption of electric vehicles, yet fuel cost then has to be even higher or electricity prices lower.

Calculation and Assessment of CO2e Emissions in Road Freight Transportation: A Greek Case Study

Road freight transportation is already contributing significantly to global warming, and its emissions are predicted to grow dramatically in the following years. Carbon footprint calculation can be used to assess CO2e emissions to understand how an organization’s activities impact global sustainability. To this end, the main objective of this paper is initially to assess the impact of Green House Gas (GHG) emissions stemming from road freight transportation. Subsequently, we adopt the EN 16258 standard to calculate the carbon footprint of a truck fleet of a freight transport operator in Greece. Based on the obtained results, we assess the performance of the company’s fleet by adopting relevant sustainability indicators. We also evaluate the use of CNG as an alternative fuel and its impact on CO2e emissions and operational costs. The paper concludes with a list of additional measures toward further reduction and offsetting of CO2e emissions.

Sanitation progress slows to a crawl amid pandemic

Speed read COVID-19 upped demand for water, sanitation and hygiene facilities But progress has been slow, before and since the pandemic began Data collection on WASH access is key to gaining ground, say experts Progress towards universal access to handwashing facilities has slowed in communities from Latin America to Sub-Saharan Africa amid the pandemic, data analysis reveals. According to the UN children’s agency UNICEF, 82 per cent of Brazilians had access to safe water sources in 2015, increasing slightly to 86 per cent in 2020. “The public water companies installed pipe systems and donated tanker trucks to the poorest communities, installed laundries for the street population and negotiated the water billing debt. [...]the increase in water consumption has been detrimental for some communities: in Algeria, water consumption increased with the rise in the number of COVID-19 cases, creating a major water deficit.