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Cloud Manufacturing (CMfg) as a service-oriented manufacturing (SOM) paradigm promotes the paradigm of partnership and collaboration among the globally distributed resources. Like technology-based marketplaces, it can identify different suppliers, determine their available services, and assign them to the requested orders based on the service-demand matching mechanism. The dominant capabilities of the SOM as a service can provide a collaborative and flexible manufacturing network configuration. This paper has focused on developing a new CMfg architecture with a concentrating on collaborative concepts to elaborate the modular manufacturing through the virtual process. In this model, different parts of the customized products can be designed as modules produced by distributed suppliers. A (Formula presented.) representation model for the SOM system has been proposed by this architecture. The proposed architecture is enriched by the help of novel technologies presented in Industry 4.0 (I4.0). The model's performance can be evaluated through different approaches, like topology analysis. Furthermore, to simulate a modeling procedure of the architecture, the process of the ventilator production marketplace is discussed in Tehran, Iran. The capabilities of the model analysis to configure the CMfg network and fulfilling the demands have also been described. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
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This study examines the predictive power of oil shocks for the green bond markets. In line with this aim, we investigated the extent to which oil shocks could be used to accurately make in- and out-of-sample forecasts for green bond returns. Three striking findings emanated from our results: First, the three types of oil shock are reliable predictors for green bond indices. Second, the performances of the predictive models were consistent across the different forecasting horizons (i.e. H = 1 to H = 24). Third, our findings were sensitive to classifying the dataset into pre-COVID and COVID eras. For instance, the results confirmed that the predictive power of oil shocks declined during the crisis period. We also discuss some policy implications of this study's findings. © 2022 The Author(s)
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As cities worldwide are striving to cope with the ongoing crisis of the COVID-19 pandemic, switching to digital platforms has sparked interest in many stakeholders in response to pandemic recovery. The uncertainty of such future shocks questions our way of addressing urban issues at a micro and Macro-Level. The virus makes physical proximity vulnerable to risks. Hence, urgency is required to shift operations to an online mode to ensure COVID-19 safety norms, maintain continuity in operation and productivity at a distance. It may indicate that worldwide, e-commerce giants have grown during the pandemic for their ability to operate through contactless platforms. On the other hand, local stores and markets suffered due to such giants' growth and Covid restrictions. This research explores challenges in the local retail sector caused by the pandemic and proposes a Design-Based solution. Considering Industry 4.0, mobile apps hold the potential to ease workflow and are easily accessible to all. Our final proposition would be to design a mobile app prototype (which would also be co-designed with the users). Methodologically, we have followed a Bottom-Up model approach and performed exhaustive user research and a heuristic evaluation with a probable user group. Only through understanding and accommodating the ‘larger' community can we all cope with the after-effects of this crisis. This research presents an opportunity for consumers to show solidarity with the small Indian retailers and shop the old, local and sustainable way again. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The contribution of commodity risks to the systemic risk is assessed in this paper through a novel approach that relies on the stochastic property of concordance ordering of CoVaR. Considering the period that spans from 2005 to 2022 and the VIX as the proxy for the stability of the financial system, we build the stochastic ordering of systemic risk for 35 commodities belonging to four sectors: Agriculture, Energy, Industrial Metals, and Precious Metals. The estimates of the ΔCoVaR signal that contagion effects from commodity markets to the financial system have been stronger during the years 2017–2019. Backtests validate CoVaR as a more resilient risk measure than the VaR, especially during periods of market turmoils. The stochastic ordering of CoVaR shows that severe losses (downside risk) in commodity markets tend to exacerbate systemic financial distress more than gains (upside risk). Commodity risks arising from WTI and EUA are threatening triggers for systemic risk. In contrast, the financial system is less vulnerable to a broader range of scenarios arising from fluctuations in Gold prices. As top contributors to the systemic risk, among the sectors we find Energy and Precious Metals with respect to upside risk and downside risk. The Covid-19 crisis has deeply amplified the systemic influence arising from the downside risk of WTI, Gasoline, and Natural Gas UK and has confirmed the safe-haven role of Gold. © 2022 Elsevier B.V.
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In the last decade, e-commerce has been growing consistently. Fostered by the covid pandemic, online retail has grown exponentially, particularly in industries including food, clothing, groceries, and many others. This growth in online retailing activities has raised critical logistic challenges, especially in the last leg of the distribution, commonly referred to as the Last Mile. For instance, traditional truck-based home delivery has reached its limit within metropolitan areas and can no longer be an effective delivery method. Driven by technological progress, several other logistic solutions have been deployed as innovative alternatives to deliver parcels. This includes delivery by drones, smart parcel stations, robots, and crowdsourcing, among others. In this setting, this paper aims to provide a comprehensive review and analysis of the latest trends in last-mile delivery solutions from both industry and academic perspectives (see Figure 1 for overview). We use a content analysis literature review to analyse over 80 relevant publications, derive the necessary features of the latest innovation in the last mile delivery, and point out their different maturity levels and the related theoretical and operational challenges. (Figure presented.). © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
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The COVID-19 pandemic and the lockdown pushed people to buy more online. With the increase in online shopping, there was also an increase in ethical issues with electronic retailers resulting from problems with products, misleading price practices, lack of customers' personal and financial data protection, non-delivery of goods, and misleading advertising. This study aimed to determine whether consumers' perceptions of e-retailers' ethics influence online customer experience and satisfaction when purchasing products and services. A research model was developed based on the literature on ethics in e-commerce. To fulfill the objective, a research model on consumer perceptions of ethics in online retailing was tested based on answers of 501 Brazilian online shoppers. Data were gathered through an online questionnaire and analyzed using structural equation modeling with an estimation of minimum least squares. The results indicated significant relations between the e-retailer's ethics, the online experience, and customer satisfaction with the mediation of ethical beliefs, suggesting that the e-retailer's ethics can potentially stimulate a good online consumer experience and satisfaction when purchasing on the internet and may contribute to the relationship between the consumer and the e-retailer. Furthermore, ethical beliefs can mediate these relations, collaborating with the effect of e-retailers' ethics on the consumer's experience and satisfaction. These results represent an advance in the study of new ethical dimensions in electronic retail, which currently are reduced to security and privacy issues. In practice, this study resulted in new knowledge about ethical practices that can guide electronic retailers in the adoption of new customer prospecting strategies. It also highlights the importance of improving regulations that prevent certain behaviors from happening. © 2022 Elsevier Ltd
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The paper investigates the volatility spillover across China's carbon emission trading (CET) markets using the connectedness method based on the quantile VAR framework. The non-linear result shows strong volatility spillover effects in upper quantiles, resulting from major economic and political events. This is in accordance with the risk contagion hypothesis that volatility of carbon price returns is affected by the shocks of economic fundamentals and spills over to other pilots. Guangdong and Shanghai are the most significant contributors to volatility transmission because of their high liquidity and active markets. Hubei CET pilot has shifted from transmitter to receiver since the COVID-19 pandemic. Regarding the pairwise directional connectedness, geographical location and similar market attribute also matter in volatility transmission. This provides implications for policymakers and investors to attach importance to risk management given the quantile-based method rather than the average shocks. © 2023 Elsevier B.V.
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During COVID-19, the explosive growth of demand for fresh agricultural products on E-commerce platform has increased the difficulty of maintaining the greenness and freshness in delivery. The traditional cold chain delivery is effective in keeping greenness, but its information asymmetry makes the freshness-keeping activities unable to be regulated, which may lead to the supply chain members giving up their freshness-keeping efforts. Can the blockchain technology effectively solve these problems? We consider a fresh agricultural product supply chain consisting of a supplier and an E-commerce platform (retailer). The retailer is responsible for the wholesale and sales of fresh agricultural products, and determines the blockchain adoption degree and advertising effort. The supplier is responsible for delivering fresh agricultural products to consumers, and determines the greenness investment and freshness-keeping effort. Based on the traditional and blockchain-based fresh agricultural product supply chain, we discuss the dynamic optimization of freshness-keeping effort, advertising effort, and blockchain adoption degree. Results show that the supplier will give up the freshness-keeping effort after receiving the wholesale funds in the traditional fresh agricultural product supply chain, which will naturally worsen the fresh agricultural products. When adopting blockchain technology, the supplier continues to make the freshness-keeping effort in delivery. And five specific settings are proved that blockchain is effective in maintaining freshness. But two other specific settings are determined that it is not suited for adopting blockchain. In addition, compared with the traditional fresh agricultural product supply chain, blockchain adoption can effectively reduce the freshness-keeping effort, advertising investment and goodwill for achieving the same profit margin level, and will not affect the greenness investment decision of the supplier. Our research can provide some insights into the cold chain logistics management of fresh blockchain. © 2022
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This study analyzes the efficiency of the crude palm oil (CPO) futures market by conducting a variance ratio test and comparing it to the West Texas Intermediate (WTI) futures market. We discover that the weak-form efficient market hypothesis holds for both the CPO and WTI futures markets despite the significant difference in their liquidity. Using a scaling exponent, we investigate speculative trading activities and find that trading CPO futures in expectation of significant returns does not strongly involve a high level of risk unlike WTI futures. Our findings regarding market efficiency of the two futures markets are supported by the significant integration of the two with similar level of information flow from each market to the other. To explore the role of speculation in their market integration, we introduce a natural experimental setting using the coronavirus disease 2019 (COVID-19) pandemic, which caused a sudden decrease in the demand for fuel. The bidirectional information flow between the two markets is intensified after the COVID-19 pandemic due to lower level of speculation. The findings suggest that (i) stakeholders in the CPO market need to pay attention to the crude oil markets to anticipate its price changes, (ii) investors can use WTI futures as a hedging tool against CPO futures as long as there is mutual information flow, and (iii) regulators should carefully implement new CPO futures market policy, as either asymmetric changes in speculation or unbalanced regulation with the WTI futures market can create market distortion and regulatory arbitrage. © 2022 The Authors
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Coronavirus disease 2019 (COVID-19) has accelerated the growth of the digital therapeutics (DTx) market;therefore, development strategies for new DTx products are necessary to satisfy market needs. However, data-driven methods for recommending digital healthcare technologies for novel DTx applications are scarce. We propose a technology opportunity discovery framework that recommends 1) potential technologies as new DTx products, and 2) the applicable target disorders. We applied BERTopic and PatentSBERTa to patents filed with the United States Patent and Trademark Office and calculated the score of potential technologies on the basis of their thematic characteristics with respect to their digital capabilities and similarity to DTx technologies. By identifying the target disorder of similar technologies, specific disorders were proposed that can be treated with the proposed technique. By applying the proposed framework to psychiatric disorders—one of the largest therapeutic areas of DTx, we recommend digital monitoring technologies applicable to poor breathing or sleeping patterns for cognitive impairment. Furthermore, we provide strategies to utilize the recommended digital technologies for DTx for specific disorders to facilitate a direct intervention or treatment, which can contribute to the planning of roadmaps for DTx. © 2022 Elsevier Inc.
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We examine the time-frequency co-movements and return and volatility spillovers between the rare earths and six major renewable energy stocks. We employ the wavelet analysis and the spillover index methodology from January 1, 2018 to May 15, 2020. We report that the COVID-19-triggered significant increase in co-movements and spillovers in returns and volatility between the rare earths and renewable energy returns and volatility. The rare earths act as net recipient of both return and volatility spillovers, while the clean energy stocks are net transmitters of return and volatility spillovers before and during the COVID-19 crisis. The solar and wind stocks are net transmitters/receivers of spillovers before/during the pandemic. The remaining markets shift from net spillover receivers to transmitters or vice versa;evidencing the effects of the pandemic. Our results show that cross-market hedge strategies may have their efficiency impaired during the periods of crises implying a necessity of portfolio rebalancing. © 2022 The Authors
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Purpose: This paper aims to examine consumers' behavioral intention (BI) to order food and beverage items using e-commerce during COVID-19 by incorporating trust (TRU) with the theory of planned behavior (TPB). Design/methodology/approach: Data were collected via an online questionnaire, and the study used a total of 306 accurate and usable responses. The population of the study includes Indian consumers. Data were analyzed using SPSS 25 and AMOS 22.0. The proposed hypotheses were statistically tested. Findings: The empirical results show that attitude (ATT), subjective norms (SN) and trust significantly and positively influence behavioral intention, while perceived behavioral control (PBC) is insignificant. This study reveals that the proposed model explained approximately 51% of the variance in the behavioral intention. Research limitations/implications: Several theoretical and practical implications are drawn on the basis of the findings of the current study that can be used to make recommendations to e-commerce companies and help them understand the behavioral intention of consumers during COVID-19. Since the research is primarily focused on India, it is difficult to extrapolate the findings to other countries. Originality/value: To the best of researchers' knowledge, no single study was carried out in the Indian context that tested the influence of trust on the behavioral intention of ordering food and beverage items using e-commerce during COVID-19. Hence, the present study attempts to understand the factors influencing purchase intention in e-commerce and analyzes the relationship between these factors in the backdrop of COVID-19. © 2022, Emerald Publishing Limited.
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In light of recently increased e-commerce, also a result of the COVID-19 pandemic, this study examines how additive manufacturing (AM) can contribute to e-commerce supply chain network resilience, profitability and competitiveness. With the recent competitive supply chain challenges, companies aim to decrease cost performance metrics and increase responsiveness. In this work, we aim to establish utilisation policies for AM in a supply chain network so that companies can simultaneously improve their total network cost and response time performance metrics. We propose three different utilisation policies, i.e. reactive, proactive – both with 3D printing support – and a policy excluding AM usage in the system. A simulation optimisation process for 136 experiments under various input design factors for an (s, S) inventory control policy is carried out. We also completed a statistical analysis to identify significant factors (i.e. AM, holding cost, lead time, response time, demand amount, etc.) affecting the performance of the studied retailer supply chain. Results show that utilising AM in such a network can prove beneficial, and where the reactive policy contributes significantly to the network performance metrics. Practically, this work has important managerial implications in defining the most appropriate policies to achieve optimisation of supply network operations and resilience with the aid of AM, especially in times of turbulence and uncertainty. © 2022 The Authors
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As chatbots become more advanced and popular, marketing research has paid enormous attention to the antecedents of consumer adoption of chatbots. This has become increasingly relevant because chatbots can help mitigate the fear and loneliness caused by the global pandemic. Therefore, unlike previous work that focused on design factors, we theorize that social presence serves a mediating role between consumer motivations (i.e., hedonic and utilitarian) and intention to use a chatbot service based on self-determination theory. Our results from a structural equation model (n = 377) indicate that hedonic (but not utilitarian) motivation significantly affects chatbots' social presence, ultimately influencing intention to use the chatbot service. We also found that fear of COVID-19 amplifies the effect of social presence on intention to use the chatbot service. In this dynamic, we found an additional moderated moderation effect of generational cohorts (i.e., baby boomers and Generations X, Y, and Z) in experiencing different levels of fear of COVID-19. Overall, our findings emphasize the importance of motivation-matching features for consumer adoption of chatbot services. Our findings also indicate that marketers may utilize the fear element to increase adoption of chatbot services, especially when targeting the young generations (e.g., Generation Z). © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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Traditionally the furniture market in Brazil is owned by family businesses and of national origin, with few exceptions. Based on this premise and the high demand promoted, especially in the Covid-19 pandemic, the market has adapted to the growing demand for residential furniture. Therefore, a conceptual restructuring needs to be carried out due to the great variability of products in the same factory, driven by the target audience, which goes beyond the traditional concepts of factory standardization and enables a new way of thinking according to the demand for products offered by catalog and/or bespoke. In addition, as they are family businesses, there is an inherent risk of closing activities due to the lack of family motivation of the following generations linked to the lack of knowledge to update manufacturing processes. This article concludes that the variability of products offered in each factory is a high option. New concepts must be adopted from handcrafted to manual transition. And, with positional and functional factory configurations, ensuring high efficiency and quality concerning the degree of difficulty, associated with the characteristics of furniture dealerships. To get success, the companies must be directed towards the sustainable production chain to the companies involved. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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In the past, it was believed that investors may generate abnormal returns (AR) for trading stocks by employing technical trading rules. However, since the COVID-19 pandemic broke out, stock markets around the world seem to suffer a serious impact. Therefore, whether investors can beat the markets by applying technical trading rules during the period of COVID-19 pandemic becomes an important issue for market participants. The purpose of this study is to examine the profitability of trading stocks with the use of technical trading rules under the COVID-19 pandemic. By trading the constituent stocks of DJ 30 and NASDAQ 100, we find that almost all of the trading rules employed in this study fail to beat the market during the COVID-19 pandemic period, which is different from the results in 2019. The revealed findings of this study may shed light on that investors should adopt technical trading with care when stock markets are seriously affected by black swan events like COVID-19. © 2023 World Scientific Publishing Company.
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We use a novel card transaction data maintained at the Central Bank of Latvia to assess their informational content for nowcasting retail trade in Latvia. During the COVID-19 pandemic in Latvia, the retail trade turnover dynamics underwent drastic changes reflecting the various virus containment measures introduced during three separate waves of the pandemic. We show that the nowcasting model augmented with card transaction data successfully captures the turbulence in retail trade turnover induced by the COVID-19 pandemic. The model with card transaction data outperforms all benchmark models in the out-of-sample nowcasting exercise and yields a notable improvement in forecasting metrics. We conduct our nowcasting exercise in forecast-as-you-go manner or in real-time squared;that is, we use real-time data vintages, and we make our nowcasts in real time as soon as card transaction data become available for the target month. © 2023 The Authors. Journal of Forecasting published by John Wiley & Sons Ltd.
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This study examines the relationship between crude oil, a proxy for brown energy, and several renewable energy stock sector indices (e.g., solar energy, wind energy, bioenergy, and geothermal energy) over various investment horizons. Using daily data from October 15, 2010, to February 23, 2022, we apply a combination of methods involving co-integration, wavelet coherency, and wavelet-based Granger causality. The results show that the relationship between crude oil and renewable energy indices is non-linear and somewhat multifaceted. Firstly, there are sectorial differences in the intensity of the relationships. Notably, the relationship intensity between the wind and crude oil is lower than that involving geothermal energy or bioenergy. Secondly, the relationship evolves with time. For example, the COVID-19 outbreak seems to have increased the relationship between crude oil and renewable energy markets, notably for solar, bioenergy, and geothermal. Thirdly, the relationship varies across scales. When controlling for the VIX (volatility index), a proxy of the sentiment of market participants, and EPU (economic policy uncertainty index), the relationship seems strong in the long term but weak in the short term. This result is confirmed using a Granger causality test on the wavelet-decomposed series. These findings have important implications for long-term investors, short-term speculators, and policymakers regarding the co-movement between brown and renewable energy markets. © 2022 Elsevier B.V.
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Purpose: E-commerce and social media technologies can significantly benefit the food and beverage industry by reducing costs, streamlining supply activities, and, most importantly, engaging users in active interaction and enhancing social presence. This research aims to propose a model to examine the role of trust and social presence on loyalty in the food and beverage industry. Moreover, the mediating role of trust is the link between social presence and loyalty examined in this study. Design/methodology/approach: A survey has been conducted to examine the structural model. The research model is tested using structural equation modelling (PLS-SEM). Findings: The result indicated the effect of Social presence and Trust in social media on Customer loyalty in the context of online shopping. Our finding contributes remarkable insights into the food and beverage industry, particularly in the COVID-19 era, as more consumers buy through e-commerce platforms. Originality/value: This study expands the understanding of the role of the managers of social commerce websites in maintaining customer loyalty. Hence, the social commerce site managers can use this finding to develop strategies for building customer trust and, ultimately, customer loyalty. © 2022, Emerald Publishing Limited.
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This paper investigates the relationship between oil and airline stock returns under different time frequencies. First, we propose an Autoregressive moving average model with mixed frequency exogenous variable to analyse the different impacts of oil on airline stock returns on daily, weekly, and monthly basis. We consistently find a negative oil-airline stock return nexus on a daily basis, but a positive relationship on a weekly basis. While the former supports the economic-based channel, the latter is in line with the market inertia channel. Our findings help explain mixed results reported in the literature. Further, our time frequency connectedness analysis shows that the economic-based channel dominates the market inertia channel since the connectedness is more pronounced in the short-run compared to the medium- and long-run. Our block connectedness results highlight that business models of airline firms can play a significant role in affecting the connectedness, in which the low-cost airlines are more sensitive to the oil price changes. It is worth noting that there are distinguished drivers of the oil-airline stock return nexus in different time frequencies. The drivers also vary between the Global Financial Crisis and the COVID-19 pandemic. Our results are consistent under a battery of robustness checks and deliver important implications to investors, portfolio managers, and executives of airline firms. © 2022 Elsevier B.V.