ABSTRACT
COVID-19 accelerated change within the UK retail market. It encouraged the growth of online shopping, providing the necessary demand for grocers to invest in their operations, and transformed the economics of their businesses. As innovative new business models emerged, some existing retailers collapsed leading to significant changes on the high street. Landlords were also affected. As some retail tenants struggled to pay their rents, other parts of the sector prospered and sought additional warehouse capacity to cope with rising demand. Not only does this illustrate how different parts of the retail sector faired during COVID-19, but it also demonstrates how the move online has resulted in the emergence of new opportunities. © 2023 the authors.
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This article uses data from several publicly available databases to show that the distribution of intellectual property for frontier technologies, including those useful for sustainable development, is very highly skewed in favor of a handful of developed countries. The intellectual property rights (IPR) regime as it exists does not optimize the global flow of technology and know-how for the attainment of the sustainable development goals and is in need of updating. Some features of the Fourth Industrial Revolution imply that the current system of patents is even more in need of reform than before. COVID-19 vaccines and therapies and the vast inequality in access to these has highlighted the costs of inaction. We recommend several policy changes for the international IPR regime. Broadly, these fall into three categories: allowing greater flexibility for developing countries, reassessing the appropriateness of patents for technologies that may be considered public goods, and closing loopholes that allow for unreasonable intellectual property protections.
ABSTRACT
One of the key indicators to measure the sustainability and resilience of a city during a public health crisis is how well it can meet the daily needs of its residents. During the COVID-19 lockdown in Shanghai in 2022, e-commerce shopping and delivery became the most important method for ensuring the city's material supplies. This article uses the distribution data of a fresh e-commerce platform's pre-warehouse and static population distribution data to establish a basic material supply system evaluation model for the city and explore its resilience potential. Focusing on the central urban area of Shanghai, this study uses a population heat map with geographic coordinates to reflect the static distribution of residents and obtains the distribution data of the e-commerce pre-warehouses. Using kernel density analysis, the relationship between the pre-warehouses and the residents' needs is established. Through analysis, it was found that the supply capacity of fresh food in different areas of Shanghai during the lockdown could be categorized as insufficient, adequate, or excessive. Based on these three categories, improvement strategies were proposed. Finally, this article suggests establishing a scientific supply security system to promote urban sustainability and prepare for future challenges.
ABSTRACT
The current COVID-19 pandemic situation necessitates the need for a prompt, safe and a contactless method for the dispatch of basic items and other essentials in various domains such as hospitals, manufacturing industries and warehouses. Contemporary robot technology can help build robots that can handle objects safely and replace and/or assist humans in such domains. Robots with soft grippers can be used in hospitals where lightweight items like bottles, medicines and tablets can be handed over to patients. They can be used in warehouses to lift objects of varying topology. This paper discusses the design of the gripper arm for a robotic trolley that can be used to pick and place objects. The gripper arm was modelled on Autodesk Fusion360, and the analysis was done on Ansys. The arm and the gripper were manufactured using ABS plastic and a composite material consisting of elastosil silicone rubber, respectively. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
The government addresses that one of the biggest problems in the country is lacking an effective contact tracing solution. The Philippines' current contact tracing systems have encountered a lot of challenges because of the lack of features that would ensure safety and awareness to users around. The study aims to propose a system framework that can be used as Contact Tracing Solution using data warehousing and edge computing would improve the tracing in small and concentrated areas such as universities and offices. The researchers gather reviews and studies on how to develop a system that would address the current problem in the contact tracing scenario in the Philippines, particularly in the education field. The researcher will be going to apply the descriptive and development design for the conduct of the study and the waterfall methodology will be the software model for the development of the proposed system. Therefore, it is better to develop a contact tracing application that will be used by universities whose main objective is to spread awareness to potentially close contacts of a COVID-19 positive case and further implement the system framework to provide a proactive solution for contact tracing in the academe. © 2022 IEEE.
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When the globe was hit by the vicious Covid 19 pandemic, multiple industries faced the virus's wrath and that included the agricultural warehouse industry. Consequently, many warehouses which had received large shipment stocks of agricultural products were never to be used again as it had reached its expiration date. This led to major losses for the agricultural warehouses as well as losses in crops for farmers and large scale agriculturists. The main objective of this paper is to build a model which utilises 3 heavy-weight algorithms (Seasonal Autoregressive Integrated Moving Average-SARIMA, Long short term memory-LSTM and Holt Winters) and predicts the agricultural needs of retailers and consumers based on previous data from different warehouses. Deploying this system will not help in the regulation of goods in warehouses but will also aid in maximizing the profits and minimizing the losses for warehouses. The algorithm with the least MAE(Mean Absolute Error) value will be considered for forecasting the sales of the aforementioned product. © 2022 IEEE.
ABSTRACT
This study analytically develops a new recovery planning optimisation model for managing the impacts of the recent COVID-19 outbreak for online business operations. Firstly, a mathematical model for the ideal plan is designed and then extended to generate a recovery plan in a finite planning horizon that maximises total profit. Recovery plans are generated considering two scenarios, namely the dynamic and uncertain situations. For the dynamic situation, a realistic system with time-dependent and dynamic demand, supply, and warehouse capacity for investigating the impacts of the COVID-19 outbreak is developed using several measures, such as collaborating with emergency suppliers, increasing warehouse capacity, and considering back-orders and lost sales to form recovery strategies. For the uncertain situation, demand, supply, and warehouse capacities are considered as uncertain variables. Further, an innovative solution approach using an adapted differential evolution technique, which is capable of (i) generating long-term recovery plans and (ii) solving both small- and large-scale problems, is developed. The results are illustrated using numerical analyses and simulation experiments. A sensitivity analysis is also conducted. In practice, the proposed optimisation model will assist the decision-makers of online business operations facing the COVID-19 outbreak to decide the optimal recovery plans.
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This paper addresses the impact of the Covid-19 lockdown on the warehousing of perishable items facing demand-side shocks, mainly those with selling price and product quality dependent demand, for example, fresh fruits, meats, vegetables, packed foods, etc. Along with demand-side issues, such an inventory system consumes a significant amount of energy in terms of freshness, increasing carbon tax and dwindling the firm's total profit. We formulate two-warehouse inventory models of perishables items using the first-in-first-out (FIFO) dispatching policy under two different Covid-19 lockdown scenarios. The two-warehouse system primarily consists of an owned warehouse (OW) and a rented warehouse (RW). Two different lockdown scenarios are considered as;(i) the lockdown during the consumption of goods in OW and (ii) the lockdown during the consumption of goods in RW. The demand rate is assumed to decline and surge by a finite volume as lockdown is forced and relaxed. The proposed models help in assessing the impact of lockdown on (i) product quality, (ii) product cost, (iii) inventory level, (iv) freshness keeping efforts, (v) investment in green technologies, and (vi) carbon cap and trade policy. We determine the above six parameters to maximize the firm's total profit. The key findings of this model suggest that yield is primarily affected due to carbon cap and trade policy, lockdown period, item price, backlogging, and variation in the holding costs in OW and RW. These models may assist the small, medium, and large firms involved in perishable or cold supply chains to assess the effect of Covid-19 like disruption and take corrective measures to maximize their profit.
ABSTRACT
PurposeThis study explores coopetition opportunities between e-tailers and brick-and-mortar (BM) retailers and provides a conceptual framework. These opportunities may be triggered by events such as social distancing causing crises (SDCC).Design/methodology/approachA grounded theory based approach was used wherein 119 news articles and 48 academic papers are the main sources of data to analyse the real-world responses. A typical qualitative methodology, including open and axial coding, was used. To further analyse the insights obtained, six in-depth interviews were conducted.FindingsNon-customer-interfacing-based coopetition, such as small BM stores serving as e-marketplace sellers and customer-interfacing-based coopetition, such as large BM stores serving as showrooms, are some potential coopetition opportunities.Research limitations/implicationsThe majority of the available studies dwell more on offline retailers developing online channels. This study investigates the opposite situation and conceptualises a new understanding of how e-tailers and BM retailers can work together more harmoniously. This study can be used as a springboard by academicians for future research on a larger scale. Five research propositions are offered that can guide hypothesis generation. Development of case studies and consulting services for the industry are the other research opportunities.Practical implicationsSocial distancing as a measure may vanish from the world with time;however, social distancing's implications are still pertinent given that new diseases, including new variants of pandemic potential, could continue to emerge. The study puts forward propositions based on theoretical dimensions and second-order themes derived from first-order categories. These propositions are about the drivers of coopetition and the opportunities with both large and small BM stores that e-tailers can leverage during a crisis, given that launching e-tailers' own BM stores demands large investments. This study has social and economic implications too.Originality/valueThis study investigates coopetition, an important trend but lacking adequate research. Whilst only few studies examine coopetition from a crises' perspective, this study investigates develops a new understanding of coopetition opportunities between e-tailers and BM retailers. This study adds to the scarce literature how such opportunities may be triggered by events such as SDCC.
ABSTRACT
Sentiment analysis is used to analyze data in text format such as tweets from Twitter social media users. Twitter is one of the most popular social media with more than half a billion users and can generate large volumes of data. It is difficult to operate large-scale data, so the data warehouse can be used as a data storage area that allows the operation of large-scale data. The final step of data warehousing is the application of business intelligence. This research uses dimensional model approach to build data warehouse from Twitter and uses lexicon-based approach to analyze public opinion of Twitter users toward covid-19 vaccine in Indonesia. The results show that the creation of a data warehouse and sentiment analysis have been successfully carried out based on the evaluation of the data warehouse and sentiment analysis. The evaluation carried out on the data warehouse is to examine the components of the dimensional model based on indicators and dimensional modeling rules by Kimball. While the evaluation carried out on sentiment analysis is the confusion matrix with the result of the accuracy of sentiment analysis is 74%. © 2022 IEEE.
ABSTRACT
Industry 4.0 influences automation, better logistics warehouse, smart manufacturing for larger productions, and supply chain management. Gamification is no longer a new topic where its framework and methodology got used for user engagement and motivation towards attitude change from repetitive activities. This paper aims to study Gamification's implementation to improve Industry 4.0 as more intelligent supply chain management needs emerge from its different departments as the current system lacks integration. Also, the supply chain industry has several monotonous tasks, and keeping employee motivated is the challenge. Industries are lagging in utilizing the gamification benefits to set up game-based engagement. In the continuously evolving market and competition, relevance is the key, which the study proposes with Gamification. With the emerging technology needs and urges of adaptability, that may lead to progressive growth and value to compete in the unceasing demands in the market. The author analyzes the annex of Gamification in supply chain management among the different aspects of Industry 4.0 to affect employee motivation in tedious work. Motivation drives human action, and different Gamification approach in literature has demonstrated the power to change the individual attitude. And the study analyzes the Gamification framework with Industry 4.0 technologies to support supply chain management to bring modernization. The research approach of this study is to understand the existing literature and analyze the detailed area under Gamification and Supply Chain Management. © 2022 IEEE.
ABSTRACT
The current COVID-19 pandemic situation necessitates the need for a prompt, safe and a contactless method for the dispatch of basic items and other essentials in various domains such as hospitals, manufacturing industries and warehouses. Contemporary robot technology can help build robots that can handle objects safely and replace and/or assist humans in such domains. Robots with soft grippers can be used in hospitals where lightweight items like bottles, medicines and tablets can be handed over to patients. They can be used in warehouses to lift objects of varying topology. This paper discusses the design of the gripper arm for a robotic trolley that can be used to pick and place objects. The gripper arm was modelled on Autodesk Fusion360, and the analysis was done on Ansys. The arm and the gripper were manufactured using ABS plastic and a composite material consisting of elastosil silicone rubber, respectively. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
In sparsely occupied large industrial and commercial buildings, large-diameter ceiling fans1 (LDCFs) are commonly utilized for comfort cooling and destratification;however, a limited number of studies were conducted to guide the operation of these devices during the COVID-19 pandemic. This study conducted 223 parametrical computational-fluid-dynamics (CFD) simulations of LDCFs in the U.S. Department of Energy warehouse reference building to compare the impacts of fan operations, index-person, and worker-packing-line locations on airborne exposures to infectious aerosols under both summer and winter conditions. The steady-state airflow fields were modeled while transient exposures to particles of varying sizes (0.5–10 μm) were evaluated over an 8-h period. Both the airflow and aerosol models were validated by measurement data from the literature. It was found that it is preferable to create a breeze from LDCFs for increased airborne dilution into a sparsely occupied large warehouse, which is more similar to an outdoor scenario than a typical indoor scenario. Operation of fans at the highest feasible speed while maintaining thermal-comfort requirements consistently outperformed the other options in terms of airborne exposures. There is no substantial evidence that fan reversal is beneficial in the current large space of interest. Reversal flow direction to create upward flows at higher fan speeds generally reduced performance compared with downward flows, as there was less airflow through the fan blades at the same rotational speed. Reversing flow at lower fan speeds decreased airflow speeds and dilution in the space and, thus, increased whole-warehouse concentrations. © 2023 Elsevier Ltd
ABSTRACT
Due to the popularity of smartphones, cameras can be seen everywhere. QR codes are widely used daily, and their application is becoming more and more diverse, such as for warehouse management, electronic tickets, mobile payment, etc. As COVID-19 rapidly spread worldwide, people were forced to change their payment habits. Contactless systems, such as electronic tickets, became increasingly used to display information and avoid traditional queues. However, the standard QR code comprises black and white squares in monochrome images, which is not visually appealing. Yet, the easiest way to present a theme in a QR code is an image, which is more eye-catching and easier to understand than text. In this study, we devise an IS-QR method to integrate full-color images with QR codes by instance segmentation, using BlendMask to extract image feature regions and take Human Visual System into account. Discrete wavelet transform and contrast sensitivity were used to lessen the impact of reduced readability of QR codes during printing. Representative image visual quality measures, including PSNR, MSE, SSIM, FSIM, and GMSD, were used to measure the experimental results in order to validate the effectiveness of QR code beautification. The subjective quality evaluation is also performed. Finally, the measurement results indicate that the beautified QR codes generated by the method IS-QR designed in this study perform better than other related studies in terms of visualization and beautification. © 2022 Elsevier Inc.
ABSTRACT
Bi-level programming is an efficient tool to tackle decentralized decision-making processes in supply chains with upper level (i.e., leader) and lower level (i.e., follower). The leader makes the first decision while the follower makes the second decision. In this research, a bi-level programming formulation for the problem of location-inventory-routing in a two-echelon supply chain, including a number of central warehouses in the first echelon and retailers in the second echelon with perishable products under uncertain demand, is proposed. The total operational costs at both levels are minimized considering capacity constraints. Due to the uncertain nature of the problem, a scenario-based programming is utilized. The economic condition or unforeseen events such as COVID-19 or Russia-Ukraine war can be good examples for uncertainty sources in today's world. The model determines the optimal locations of warehouses, the routes between warehouses and retailers, number of received shipments and the amount of inventory held at each retailer. A revised solution method is designed by using multi-choice goal programming for solving the problem. The given revised method attempts to minimize the deviations of each decision maker's solution from its ideal value assuming that the upper level is satisfied higher than the lower level. Base on some numerical analysis, the proposed solution technique is more sensitive to the upper bounds of the goals rather than the lower bounds. © 2022 Elsevier B.V.
ABSTRACT
Based on the Baidu Index, taking "warehousing"and "warehouse"as the keywords, the Baidu search index of "warehousing"and "warehouse"nationwide is statistically analyzed. It is found that the Baidu search index with "warehousing"and "warehouse"as the keywords has significantly increased before and after the COVID-19 epidemic, which shows that the basic role of logistics warehousing in the national economic and social development is increasingly obvious, and the corresponding demand for logistics warehousing is growing. Based on the big data of Warehouse in Cloud, incomplete statistics of "warehousing demand"of "demand location"in China's provinces are similar to the analysis of differences in the source places (regions and provinces) of different search groups through the "population portrait"of Baidu Index. The "warehousing demand"and "warehousing supply"of the key cities in central and Western China are counted. Focusing on the key cities in central and Western China, the correlation analysis of warehousing rent and demand area is carried out. It is found that, on the one hand, the regional logistics warehousing demand is 3 years (the lease term is less than 1 year or 1-3 years), with intra-period volatility. On the other hand, regional centers (National Central Cities) have absolute advantages in the attraction of regional logistics and warehousing. Furthermore, in recent years, due to the impact of the COVID-19 epidemic and extreme meteorological and geological disasters, the adverse impact on the regional economic and social development will show that the demand for logistics and warehousing will be interrupted, reduced and lagged, and the growth will be restored in subsequent years. The average rent of key cities in Western China is 22.52 yuan/m2·month, the average vacancy rate is 11.65%, and there are 1359 warehouses in the park. The average rent of key cities in the central region is 23.5 yuan/m2·month, the average vacancy rate is 13.86%, and there are 1070 warehouses in the park. From the perspective of rent, Changsha shows the highest rent, while Taiyuan shows the lowest rent. Furthermore, the vacancy rate of Chongqing and Xi'an are the highest and lowest, respectively. There is a correlation between the variable of warehousing rent in 2022 and the total retail sales of consumer goods in 2021 (Spearman correlation coefficient is significant). There is a correlation between the variable of average warehousing demand area in 2019-2021 and the sample of the third industry production value in 2021 and the sample variable of total import and export volume of goods in 2021 (Pearson correlation coefficient is significant). The variable of average warehousing demand area in 2019-2021 and the sample variable of resident population. There is a correlation between the total retail sales of social consumer goods in 2021 (Spearman correlation coefficient is significant). On the one hand, the statistical analysis of big data on the digital warehousing information platform can provide reference for the prediction of supply and demand of logistics warehousing and modern logistics service industry in the high-quality development of the region. On the other hand, the spatial econometric analysis of logistics industry and regional economic growth represented by logistics warehousing needs further research. CCS CONCEPTS •Human-centered computing ∼Collaborative and social computing ∼Collaborative and social computing theory, concepts and paradigms ∼Computer supported cooperative work © 2022 ACM.
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In this paper, we propose a multidimensional spatiotemporal modeling framework of data warehouse creation for tracing dynamic events in contemporary applications, like crowd contact tracing for Covid-19 prevention. Such a framework offers a natural and consistent solution for slowly changing dimension management. It provides a progressive evolution from traditional static data management to modern dynamic data analysis with spatiotemporal tracking capabilities for IoT applications. Based on such a framework, en-tity-centered resource integration and related business intelligence applications can be rig-orously developed, managed and properly tracked. © 2022 Institute of Information Science. All rights reserved.
ABSTRACT
Mobile robots have been used in warehouses worldwide as a means for distribution of goods and gained demand after the Covid19 labor issue. This paper proposes an Autonomous Mobile Robot (AMR) to navigate in a warehouse environment to its target location using LIDAR. The method used to solve this problem is a deep reinforcement learning algorithm called deep Q-network (DQN) to detect and avoid obstacles and reach the target location. DQN is used as it is desired for solving complex tasks. Training of the DQN algorithm is carried out in ROS Gazebo environment using LIDAR-based robot model. The LIDAR sensor detects the obstacles and the odometer sensor helps to find the distance between the target location are used as inputs for training the algorithm and optimal actions are taken based on the two inputs. A reward policy is awarded when an obstacle is avoided and reaches the target location. The results show that mobile robot can successfully navigate in an unknown environment through simulation and real life. © 2022 IEEE.
ABSTRACT
Purpose: This study explores coopetition opportunities between e-tailers and brick-and-mortar (BM) retailers and provides a conceptual framework. These opportunities may be triggered by events such as social distancing causing crises (SDCC). Design/methodology/approach: A grounded theory based approach was used wherein 119 news articles and 48 academic papers are the main sources of data to analyse the real-world responses. A typical qualitative methodology, including open and axial coding, was used. To further analyse the insights obtained, six in-depth interviews were conducted. Findings: Non-customer-interfacing-based coopetition, such as small BM stores serving as e-marketplace sellers and customer-interfacing-based coopetition, such as large BM stores serving as showrooms, are some potential coopetition opportunities. Research limitations/implications: The majority of the available studies dwell more on offline retailers developing online channels. This study investigates the opposite situation and conceptualises a new understanding of how e-tailers and BM retailers can work together more harmoniously. This study can be used as a springboard by academicians for future research on a larger scale. Five research propositions are offered that can guide hypothesis generation. Development of case studies and consulting services for the industry are the other research opportunities. Practical implications: Social distancing as a measure may vanish from the world with time;however, social distancing's implications are still pertinent given that new diseases, including new variants of pandemic potential, could continue to emerge. The study puts forward propositions based on theoretical dimensions and second-order themes derived from first-order categories. These propositions are about the drivers of coopetition and the opportunities with both large and small BM stores that e-tailers can leverage during a crisis, given that launching e-tailers' own BM stores demands large investments. This study has social and economic implications too. Originality/value: This study investigates coopetition, an important trend but lacking adequate research. Whilst only few studies examine coopetition from a crises' perspective, this study investigates develops a new understanding of coopetition opportunities between e-tailers and BM retailers. This study adds to the scarce literature how such opportunities may be triggered by events such as SDCC. © 2022, Emerald Publishing Limited.
ABSTRACT
In recent years, the changing market needs due to the dramatic increase of e-commerce and the effects of Covid-19 pandemic have caused a growing demand for supply chain operations. This dynamic business context is also associated with relevant technological and innovative modifications. In the logistics sector, automated warehouses play a crucial role in dealing more effectively with this development trend. For this reason, they are a relevant topic in universities and engineering faculties. Nevertheless, these systems mostly find application and implementation in the industrial sector, determining a significant detachment from the academic sphere. This usually results in a not complete awareness of university students related to the development and operations of such structures. Therefore, an automated warehouse made up by an innovative Automated Storage and Retrieval System and a Mobile Industrial Robot fleet recently installed in a university laboratory was showed to a group composed of 62 engineering students with different academic background. Moreover, a simulation was carried out, physically reproducing the main operations of a distribution centre, namely receiving, kitting, picking, and shipping processes. The students perception related to the automated warehouses was then evaluated through a questionnaire submitted at the end of the experience. The survey demonstrated that most of the students was interested in topics related to the industrial logistics, despite many of them never saw an automated warehouse before the laboratory test. Furthermore, the large majority of the students evaluated positively the simulation and they affirmed that the proposed experience significantly enriched their knowledge about logistics automation. Finally, many students declared that thanks to the test, the interest towards the automated warehouses increased and more than 50% started considering the idea of working in the logistics sector. © 2022, AIDI - Italian Association of Industrial Operations Professors. All rights reserved.