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PurposeIn past years, the global supply chain has witnessed devastating effects of coronavirus (COVID-19) disease. However, the COVID-19 pandemic has renewed the interest of the Sustainable Supply Chain (SSC) stakeholders on sustainability. The stakeholders are now rethinking their business processes and strategy to make them sustainable. In this context, the relevant literature is required to support emerging markets to formulate sustainability-focussed strategies. The purpose of this study is to provide a comprehensive analysis of potential antecedents that leads towards sustainable development of freight transportation in emerging markets.Design/methodology/approachInitially, the antecedents of the Sustainable Freight Transport (SFT) system are derived from the literature survey followed by verification from the experts. Then, the potential antecedents are categorized under four (social, organizational, operational and environmental) broad categories. Afterwards, a Neutrosophic Analytic Network Process (N-ANP) method is employed to obtain the priority weights of the identified potential antecedents.FindingsThe paper identified and ranked 17 antecedents of the SFT system. According to the study's findings, the top three antecedents of SFT are "the presence of a multimodal transportation system,” "circularity in SFT” and "traffic congestion management”. The results from the study advocate the promotion of existing multi-modal transport facilities which is promising to achieve sustainability. The results suggested the adoption of the digital twin to manage the transport operations.Originality/valueThis study sheds light on how to achieve sustainability in the freight transportation system post-COVID era highlighting the potential antecedents. The study's findings will assist practitioners in developing SFT strategies in the face of such pandemics in future.
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Movement restrictions implementation due the COVID-19 pandemic affected people's mobility and and transportation sectors globally. Tourism, retail, transportation, and hospitality also suffered significant consequences that indirectly impacted a country's economic stability. Hence, this paper presents the Malaysian experience with the effects of the pandemic on transportation services and travel behaviour. Online sources, secondary data and a questionnaire survey were employed to collect the relevant data. These data were further analysed and presented in this paper. In general, transportation sectors involving air, rail and public bus showed decreased demand and services. A severe drop in services was observed in air transportation which is more than 97%. Most people prefer not to use public transportation to avoid the risk of COVID-19 infection. Noticeable changes in travel behaviour and mode preference during and pre-pandemic are observed, particularly on trips related to work/school. Key pandemic factors concerning transportation were fear of infection and social distance. Hence, most people prefer to use a private vehicle. The changes in transportation service and travel behaviour result in severe losses in the transportation sector in Malaysia.
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By March of 2020, most cities worldwide had enacted stay-at-home public health orders to slow the spread of COVID-19. Restrictions on nonessential travel had extensive impacts across the transportation sector in the short term. This study explores the effects of COVID-19 on shared e-scooters by analyzing route trajectory data in the pre- and during-pandemic periods in Austin, TX, from a single provider. Although total shared e-scooter trips decreased during the pandemic, partially owing to vendors pulling out of the market, this study found average trip length increased, and temporal patterns of this mode did not meaningfully change. A count model of average daily trips by road segment found more trips on segments with sidewalks and bus stops during the pandemic than beforehand. More trips were observed on roads with lower vehicle miles traveled and fewer lanes, which might suggest more cautious travel behavior since there were fewer trips in residential neighborhoods. Stay-at-home orders and vendor e-scooter rebalancing operations inherently influence and can limit trip demand, but the unique trajectory data set and analysis provide cities with information on the road design preferences of vulnerable road users.
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COVID-19 has shocked every system in the U.S., including transportation. In the first months of the pandemic, driving and transit use fell far below normal levels. Yet people still need to travel for essential purposes like medical appointments, buying groceries, and-for those who cannot work from home-to work. For some, the pandemic may exacerbate extant travel challenges as transit agencies reduce service hours and frequency. As travelers reevaluate modal options, it remains unclear how one mode-ride-hailing-fits into the transportation landscape during COVID-19. In particular, how does the number of ride-hail trips vary across neighborhood characteristics before versus during the pandemic? And how do patterns of essential trips pre-pandemic compare with those during COVID-19? To answer these questions, we analyzed aggregated Uber trip data before and during the first two months of the COVID-19 pandemic across four regions in California. We find that during these first months, ride-hail trips fell at levels commensurate with transit (82%), while trips serving identified essential destinations fell by less (62%). Changes in ride-hail use were unevenly distributed across neighborhoods, with higher-income areas and those with more transit commuters and higher shares of zero-car households showing steeper declines in the number of trips made during the pandemic. Conversely, neighborhoods with more older (aged 45+) residents, and a greater proportion of Black, Hispanic/Latinx, and Asian residents still appear to rely more on ride-hail during the pandemic compared with other neighborhoods. These findings further underscore the need for cities to invest in robust and redundant transportation systems to create a resilient mobility network.
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PurposeThis study aims to investigate the conditions for the financial feasibility of an incentive-based model for self-drop or crowdsourced drop of the product to be returned at designated drop boxes (thereby ensuring a contactless process).Design/methodology/approachConstraint-based non-linear mathematical modeling was done for cost differential with and without crowdsourcing. This was analyzed against returns on investment for the installed infrastructure. Scenarios were looked into from the linear, iso-elastic and logarithmic demand functions to identify the optimal incentive policy. The results were further evaluated using "willingness to return” for customer willingness for product returns via drop boxes.FindingsCrowdsourcing is viable when product returns are no more than 15%–20% of the overall products, with a logistics cost differential of 15%–25%. These were only viable when the product return incentive was within the range of 15%–20% of the product cost, as well as the penalty was in the range of 25 to 40% for wrong returns.Research limitations/implicationsThe findings are expected to aid the organizations in successfully designing product return policies while adhering to the post-COVID-19 norms, including contactless transactions and social distancing.Originality/valueThe study provides a look into the viability sensitivity of effective gains/profitability against the required level of service for returns, wrong returns, penalties and incentives for crowdsourcing in a developing country like India.
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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.
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The aim is to analyse the business results of the Lyft platform during the Covid 19 pandemic. Research and analysis of business results are the basis for comparison with the business results of other corporations in the sharing economy model. Selected financial indicators were used in the analysis, which were put in relation with selected ride-hailing indicators. The research was done using the financial analysis of parameters from the corporation's profit and loss account, that is, statistical regression of the ride-hailing trend in the selected time period. The research results indicate a strong impact of the Covid 19 pandemic on the overall activities of the corporation. In the first quarter of 2020, during the lockdown in the USA, the corporation's revenues and the number of rides dropped sharply. The corporation's revenues continuously grew until the emergence of the Covid 19 pandemic, and fell sharply with the advent of the lockdown model. The same trend was shown with the number of ride-hailing activities. After emerging from the crisis, revenues are recovering as well as the number of ride-hailing.
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Mobility and transportation activities in smart cities require an increasing amount of energy. With the frequent energy crises arising worldwide and the need for a more sustainable and environmental friendly economy, optimizing energy consumption in these growing activities becomes a must. This work reviews the latest works in this matter and discusses several challenges that emerge from the aforementioned social and industrial demands. The paper analyzes how collaborative concepts and the increasing use of electric vehicles can contribute to reduce energy consumption practices, as well as intelligent x-heuristic algorithms that can be employed to achieve this fundamental goal. In addition, the paper analyzes computational results from previous works on mobility and transportation in smart cities applying x-heuristics algorithms. Finally, a novel computational experiment, involving a ridesharing example, is carried out to illustrate the benefits that can be obtained by employing these algorithms.
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This paper examines the efficacy of telemedicine (TM) technology compared to traditional face-to-face (F2F) visits as an alternative healthcare delivery service for managing diabetes in populations residing in urban medically underserved areas (UMUPAs). Retrospective electronic patient health records (ePHR) with type 2 diabetes mellitus (T2DM) were examined from 1 January 2019 to 30 June 2021. Multiple linear regression models indicated that T2DM patients with uncontrolled diabetes utilizing TM were similar to traditional visits in lowering hemoglobin (HbA1c) levels. The healthcare service type significantly predicted HbA1c % values, as the regression coefficient for TM (vs. F2F) showed a significant negative association (B = −0.339, p < 0.001), suggesting that patients using TM were likely to have 0.34 lower HbA1c % values on average when compared with F2F visits. The regression coefficient for female (vs. male) gender showed a positive association (B = 0.190, p < 0.034), with HbA1c % levels showing that female patients had 0.19 higher HbA1c levels than males. Age (B = −0.026, p < 0.001) was a significant predictor of HbA1c % levels, with 0.026 lower HbA1c % levels for each year's increase in age. Black adults (B = 0.888, p < 0.001), on average, were more likely to have 0.888 higher HbA1c % levels when compared with White adults.
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The implementation of the urban underground logistics system (ULS) can effectively mitigate the contradiction between the surging logistics demand and the increased negativity of urban logistics. The widespread implementation of ULS still suffers from a lack of research into its operation in the marketplace, although the research on ULS system technology and network design appears to be sufficient. A new supply chain for logistics service based on ULS (ULS-SSC) was proposed, as ULS embedded in the urban logistics system could lead to the evolution of the role of supply chain participants. This article analyzed the organizational structure and operation characteristics of ULS-SSC and designed a top-down ULS-SSC operation process model based on the designed functional structure and subsystems relationship using the hierarchical colored Petri net (HCPN). The simulation results show that the integrated information management platform based on ULS can integrate urban logistics service supply chain resources and operate effectively under the two main service modes designed. The high-time delay intermediate links can be upgraded by system optimization, and the links with initial pickup and terminal distribution can be improved through outsourcing and supply chain collaboration. The findings provide new insights into the feasibility of the operation of ULS in the market and help stimulate the implementation of ULS.
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Theory of Planned Behavior (TPB) has been implemented to evaluate the structure of behavioral change of the local communities in the forest and wildlife conservation program in Tangkahan, the eastern part of GLNP. This study has the purpose to reveal the determinant factors of local community behavior to support forest and wildlife conservation through ecotourism activities and to formulate a strategy to recover wildlife ecotourism in the post-COVID-19 outbreak. The study was conducted in Tangkahan through a survey method to collect the data. The data were analyzed using linear regression analysis. This study found that the determinant factors of behavioral intention are the conservation attitude and perceived behavioral control and behavioral intention significantly affects the behavior to participate in conservation activities. To improve the visiting number and the ecotourism service in Tangkahan in the post-COVID 19 outbreak, the community should transform and develop the management system from a conventional to virtual/digital method, develop and follow the COVID-19 protocol of ecotourism, re-arrange the ticket fee and the tour packages to cope with domestic visitors and improve the access to the area by constructing the roads and provision of transportation services.
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This study aimed to evaluate the spatial accessibility of tourism attractions in the urban destination city. An analytical framework for assessing urban tourism accessibility at different spatial scales was proposed to provide references on the interaction of urban transport and tourism systems. In addition to the travel time-based measure, a modified gravity model integrating the tourism destination attractiveness, urban transport system characteristics, and tourist demand distribution was developed to evaluate tourism accessibility in this study. Real-time travel data obtained from the Web Maps service were used to take the actual road network operation conditions into consideration and improve the accuracy of estimation results. Taking Nanjing as an example, the analysis results revealed the spatial heterogeneity of tourism accessibility and inequality in tourism resource availability at different levels. Road transport service improvement plays a dominant role in increasing tourism accessibility in areas with insufficient tourism resources, such as the outskirts of the destination city. As for areas with abundant attractions, authorities could pay attention to destination attractiveness construction and demand management in addition to the organization and management of road network operations around attractions during holidays. The results of this study provide a potentially valuable source of information for urban tourism destination management and transport management departments.
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The transportation industry is closely related to the macroeconomic development. The transportation services index (TSI) can be used to measure the relationship between them. The freight services index in Henan Province (HNFSI) is proposed based on the TSI. The HNFSI index is used to analyze the correlation, the periodicity, and the impact of COVID-19 between the development of economic and transportation in Henan Province. The results show that the correlation coefficient between the HNFSI index and the Growth Rate of Industrial Added Value which represents trends in economic development, is 0.745. The freight transportation demand increases with a certain periodicity and regularity. Due to the influence of COVID-19, the HNFSI in January 2020 decreased by 37.7% compared to the same period of 2019, and decreased by 56.3% in February. However, after March 2020, the freight service is greatly improved. © ASCE.
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With the effective control of Novel coronavirus pneumonia, the priority problem which all cities have to face is how to provide convenient transportation services for the resumption of production. Take Qingdao for example, It is proposed that the transformation of public transportation users to private transportation is the key to effectively control the spread of the epidemic before the NCP is completely resolved at the urban traffic level. On this basis, we put forward some suggestions on how to provide urban transportation services for commuting during the special period of the epidemic. Such as, we need to focus on the low-income groups who commute over long distances, the traffic environment of slow traffic commuter groups and traffic accessibility within the influential scope of core area. © ASCE.
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Outbreaks of the COVID-19 pandemic, caused by the SARS-CoV-2 virus, have led to the creation of social distancing and lockdown policies to reduce the spread of the virus. Consequently, public/private transportation services, schools, workplaces, and retail stores' operations were disrupted. We gather user mobility reports worldwide to learn impacts of early COVID-19 outbreaks on human mobility patterns and trends. Building time series of six types of activities tracked in the Google Community Mobility Reports (CMR), we develop visualization tools and interactive dashboards for linking mobility and COVID-19 infection data at different levels (from county- and state-level in the US, to country level for the rest of the world). We show that the relationship between mobility and COVID-19 infection changes over time, and therefore the stage of the pandemic is essentially important for understanding how containment policies can affect infections and deaths caused by the COVID-19 pandemic. © 2022 IISE Annual Conference and Expo 2022. All rights reserved.
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Kentlerde yaşayan insanlar için;kentsel ulaşım, gündelik yaşantının doğal bir parçasıdır. Sıradan bir kentli, 20.yy’da gitmek istediği yere, büyük olasılıkla motorlu bir aracın yardımıyla ulaşabilmektedir. Kentlerde taşıt araçları için gerekli altyapının sunulması, bu araçların kullanımını giderek daha da kolaylaştırmıştır. Yaygınlaşan taşıt araçları ise, yolculuk talebini tetikleyerek yük ve yolcu hareketlerinin artmasına neden olmuştur. Ancak kısa denilebilecek bir süre sonra, ulaşımın ekonomik ve çevresel maliyetleri katlanabilir olmaktan çıkmış ve kentlerdeki yaşam kalitesi düşmüştür. Böylece motorlu taşıt araçları odağında gelişen kentler ve ulaşım planları sorgulanır olmuştur. Daha sürdürülebilir ulaşım sistemlerine yönelik arayışlar bu şekilde başlamıştır. Erişilebilirliği, yayayı, mikro hareketlilik araçlarını gözeten yeni ulaşım paradigması artık kentlerin yeni gündemini oluşturmaktadır. Bu çalışma, mevcut ulaşım sistemi ile yukarıda özetlenen gerekçelerle ortaya çıkan yeni ulaşım paradigmasının kavramsal olarak karşılaştırması ile başlamıştır. Ardından, seyahat eğilimlerinde yaşanan değişimler nedenleriyle birlikte ele alınmıştır. Bugünün yük ve yolcu ulaşımındaki eğilimlerin tespit edilmesi, gelecekteki ulaşım sistemine yön vermek bakımından önem taşımaktadır. Bu eğilimleri değiştiren unsurlar;ekonomik, sosyal, teknolojik ve çevresel başlıklarında incelenmiştir. Son olarak, COVÍD-19 salgının, mevcut eğilimlere ve ulaşımın paydaşlarına olan etkileri üzerinde durulmuştur. Bu makalenin amacı, kentsel ulaşımın gündemini oluşturan yeni ulaşım paradigmasına, değişen eğilimlere ve COVÍD salgının ulaşım üzerindeki etkilerine işaret etmektir. Makale, nitel araştırma yöntemiyle ikincil veri taramasına dayalı olarak kurgulanmıştır. Sonuç olarak ortaya çıkan yeni seyahat davranışları, hem dikkate alınması gereken bulgulardır, hem de sonuçlardır. Ulaşımda COVÍD-19 salgını nedeniyle hızlanan yeniden yapılanma süreci, son dönemde kentleri etkileyecek gelişmeleri tarif etmektedir. Yeni hareketlilik davranışları, şehir plancılarının mevcut ulaştırma pratiklerini gözden geçirmesini gerekli kılmaktadır.Alternate :For people living in cities;urban transport is a natural part of daily life. In the 20th century, an ordinary citizen can probably reach the place, she/he wants to go, with the help of a motor vehicle. Providing the necessary infrastructure for vehicles in cities has facilitated their usage. The widespread transportation vehicles, on the other hand, triggered the demand for travel and caused an increase in freight and passenger mobility. However, after a short period of time, the economic and environmental costs of transportation ceased to be bearable and the quality of life in cities decreased dramatically. Thus, cities and transportation plans focused on motor vehicles began to be questioned. In this way, the search for more sustainable transportation systems has begun. The new transportation paradigm, which considers accessibility, pedestrian, micro-mobility vehicles, has started to be mentioned more and more. First of all, this study started with a conceptual comparison of the existing transportation system and the new transportation paradigm that emerged with the reasons outlined above. The existence of the structure, human and traffic density in the cities enabled to emerge the solution from the cities. As cities have difficulty in carrying the burden of automobiles, the basic paradigm in the understanding transportation is questioned and new ideas come to the fore. Environmental pollution, high costs of time and fossil fuels;force citizens to produce healthier solutions in cities. The traditional transportation policies that are demand-oriented and based on the mobility of vehicles from one place to another has been out dated. This understanding has left its place o modern transportation policies. The changes in travel trends are discussed together with their reasons. Determining the trends in today’s freight and passenger transportation is important in terms of directing the future transportation system. The factors that change these trends are paraphrased under four headings: economic, social, technological and environmental. Finally, the effects of the COVID-19 pandemic on current trends and transportation stakeholders are emphasized. Local and global measures taken during the global pandemic caused transportation to be completely stopped or slowed down in certain periods. In fact, the pandemic did not only lead to change in passenger behaviors and demands, but also affected all stakeholders of transportation. In the article, its impacts on economic sectors, its impacts on individuals receiving transportation services and its impacts on the public sector are explained with examples. This study has been prepared to point out these issues that constitute the agenda of urban transportation. The article was created with a qualitative research method and was constructed based on secondary data searching. The analysis and policy reports of international institutions on a global scale were examined, and the issues on the agenda in academic studies were discussed. As a result, new travel behaviors are both findings and consequences to consider. The restructuring process of transportation, which has accelerated due to the COVID-19 pandemic, describes the developments that will affect cities the most in the recent period. New mobility behaviors make it necessary for city planners to review existing transport practices. Consequently new travel behaviors are both findings and consequences to be considered. The restructuring process, which has to accelerate due to the COVID-19 pandemic in transportation, describes the developments that will affect the cities the most in the recent period. New mobility behaviors make it necessary for city planners to review existing transportation practices. The existing legal/administrative structure needs to be restructured. Renewed structure of transport system needs to gain the competence to meet the requirements.
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Public travel is an important support for urban citizens’ production and life. As a collective choice behavior, there are different action logics behind the common sharing travel and public sharing travel in China. It is beneficial to provide public travel services to citizens and improve the performance of urban governance by sorting out the different public travel types and their inner choice logics. A fuzzy set of qualitative, comparative analyses reveals that citizens’ choice of common sharing travel or public sharing travel consists of two paths, in which user size, rule attainment, convenience, and travel distance are important triggers. The government and enterprises should improve the combined supply of each factor to enhance citizens’ public travel experience, guide citizens’ public travel choice behavior, and help the development of a common sharing travel industry so as to promote the construction of green transportation, public transport cities, and smart cities.
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Religion tourism has a significant contribution to Indonesia's national economic development. culture, religion, and economics are covered in the global hospitality business tourism. This research aims to examine the influence of driving motivation, attracting motivations, motivations of Islamic attributes to the loyalty of visits through the satisfaction of visiting, from tourists who come to Indonesia. This article used an empirical study based on research during the COVID 19 pandemic happened. The data research was collected by 298 foreign and national tourists using purposive sampling techniques. The data is analyzed using Path analysis with SPSS software. The motivation of Islamic attributes indirectly affects the loyalty of visits (through the satisfaction of visiting) to tourists before they decide. The results highlight the importance of Islamic attributes related to Indonesia tourism, that contributes several contributions: 1) as a theoretical contribution, religion still takes place in everyone decisions, 2) as a tourism industry, there are many efforts to increase tourist satisfaction and loyalty to their visits, 3) as a policymaking contribution, the Indonesian government needs to improve marketing strategies that will ensure satisfaction and encourage tourists to come again.
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Postal delivery is the world's longest-running service business process. Every city on the planet has this service, which is supported by a network of various depots serving as collection and delivery points. In distributing postal item delivery, Pos Indonesia through the Postal Processing Centre (PPC) is a distribution streamline that connects cities and regions with delivery centres closer to the final customer. Pos Indonesia has previously established a distribution pattern based on a zone-based system comprising a primary distribution centre and various delivery centres, delivery schedules, internal fleets, and predetermined routes.However, with reduced production capacity, as demonstrated by reducing traditional mail and less than truckload operations and anticipating customer needs for timely delivery, delivery patterns with fixed schedules and the internal fleet are unable to address this issue. Close-Open Mixed Vehicle Routing Problem (COMVRP) is proposed to optimize delivery by involving external fleets, and this is to reduce transportation costs where external fleets do not have fixed costs and do not need to return to PPC after delivery. The Genetic Algorithm is used to find heuristic solutions for each delivery history after Nearest Neighbor (NN)implementationto validate vehicle routes. Combined COMVRP-NN-GA produces a set of solutions, which will be used in the Monte Carlo Simulation (MCS). The results demonstrate that COMVRP outperforms existing scenarios, from optimizing six-vehicle routes to estimating five routes using a single external vehicle route, significantly reducing total mileage. The simulation findings based on the historical delivery dataset may be used to develop future delivery patterns based on the number of vehicles and total route distance and reduce transportation costs.
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Background: Nowadays, a gradual change in customers’ attitudes towards transport service makes it more challenging to understand the reasons behind customers’ travel decisions. High-speed rail (HSR) has been mentioned recently and is expected as the best and most modern transport option in long-distance trips in Vietnam. However, research studies have paid scant regard to how HSR’s attributes may affect potential users, and therefore the motivations and barriers to adopting HSR are still unknown. Objectives: This study aimed at examining motivations and barriers to take-up HSR for considering customers’ preference on the proper attributes and levels of HSR. Method: This study drew on a nationwide survey and conjoint analysis to investigate customers’ behaviour. Results: In Vietnam’s context, HSR ticket was found to be the principal barrier to adoption, whereas the speed of HSR was identified as the least important behavioural driver amongst potential HSR users. The results show that HSR design and planning should provide a combination of minimum check-in and waiting time, a 20-min frequency, average speed of 250 km/h, all add-on services and facilities, ticketing of approximately VND 500–700 thousand per 300–500 km and nearby all-day parking. Conclusion: This investigation has demonstrated the value of conjoint analysis to compare a wide range of attributes associated with consumers’ decision to use HSR. The findings indicate that in countries such as Vietnam, in particular, where train usage is low, policymakers and transportation agencies seeking to boost the use of HSR must take attributes other than fare into consideration.