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PurposeThe purpose of this paper is to study enterprise innovation in the perspective of external supplier relationship. On this purpose, this paper examines the impact of supplier change on enterprise innovation with the moderating role of market competition.Design/methodology/approachUsing 2012–2020 empirical data of Chinese listed manufacturing enterprises, this paper investigates the relationship among supplier change, market competition and enterprise innovation through a two-way interaction model.FindingsThe results show that supplier change has a negative impact on enterprise innovation. And market competition intensifies the negative relationship between supplier change and enterprise innovation. Additional analyses indicate that the main effect and the moderating effect are more significant when the enterprise is non-state-owned or has lower ownership concentration.Originality/valueThis paper studies enterprise innovation from the perspective of external stakeholders. It focuses on supplier relationship in a dynamic variation view, instead of the traditional static ones. Moreover, this paper explores the contingency effect of market competition and gives practical implications for managers to adjust innovation strategy flexibly.
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In supply chain management (SCM), product classification and demand forecasting are crucial pillars to ensure companies to have production in the right category and quantity for long-term profitability. Due to COVID-19 from 2019, the automobile industry has been seriously negatively affected as the demand dropped dramatically. Therefore, it is necessary to make reasonable product classification and accurate demand forecasting to facilitate automobile companies in SCM to reduce unpopular product manufacture and unnecessary storage costs. In this paper, the Canada automobile market has been chosen with the period from 1946 to 2022. To classify a number of different types of motor vehicles into several categories with general characteristics, K-means Clustering method is applied. With the seasonal patterns and random generated features for auto sales, the time series models ARIMA and SARIMA are adopted for demand forecasting. According to the analysis, the automobiles fitting in the category with high demand and low price are valuable for further production. In addition, SARIMA Model is more accurate and fits better than ARIMA Model for both the training and test datasets for long-term prediction. The classification and forecasting results shed light on guiding manufacturers to adjust production schemes and ensuring auto dealers to predict more accurate sales in order to optimize the strategic planning. © 2023 SPIE.
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Study Design: We conducted a qualitative stakeholder analysis project with suppliers of the MDPP and health care providers. Am J Manag Care. 2023;29(6):In Press _____ Takeaway Points More than 5 years after CMS enacted coverage of the CDC-approved Medicare Diabetes Prevention Program (MDPP) in 2018, little is known about why MDPP uptake is so limited. * Findings of our stakeholder analysis with program suppliers and health care providers reinforced existing evidence on insufficient reimbursement and low awareness of the program. * Newer insights include recommendations about lagged payments, ongoing virtual delivery, and formally diagnosing prediabetes among MDPP participants. * Our findings on barriers and facilitators can inform policy to refine the MDPP and research on the MDPP, particularly within the field of implementation science. _____ Population-level strategies to prevent type 2 diabetes are urgently needed for the more than 24 million older adults with prediabetes in the United States.1 Evidence-based lifestyle interventions can prevent diabetes onset, per evidence from the landmark Diabetes Prevention Program trial.2 Thus, the CDC launched the National Diabetes Prevention Program (NDPP) in 2010.3 Significant reductions in weight and medical spending were observed among Medicare beneficiaries who participated in the NDPP,4 prompting CMS to fully cover the Medicare Diabetes Prevention Program (MDPP) starting in 2018.5 Despite unprecedented Medicare coverage for a disease prevention program, MDPP uptake is limited. Regarding awareness, national guidelines recommend referral to lifestyle intervention for adults aged 40 to 70 years with prediabetes.9 Yet less than 5% of adults eligible for a NDPP reported receiving a referral,10 which may stem from limited awareness among health care providers.11 Thus, we conducted a qualitative stakeholder analysis to learn about regional awareness of, referral to, facilitators of, and barriers to the MDPP. The 8 interviewees included 5 program directors (3 from YMCAs, 1 from a private organization, and 1 from a hospital system) and 3 health care providers (2 family physicians and 1 dietitian).
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In December 2019, a novel coronavirus broke out in Wuhan City, Hubei Province, and, as the center of the coronavirus disease 2019 (COVID-19) epidemic, the economy and production throughout Hubei Province suffered huge temporary impacts. Based on the input–output and industrial pollution emissions data of 33 industrial industries in Hubei from 2010 to 2019, this article uses the non-parametric frontier analysis method to calculate the potential production losses and compliance costs caused by environmental regulations in Hubei's industrial sector by year and industry. Research has found that the environmental technology efficiency of the industrial sector in Hubei is showing a trend of increasing year-on-year, but the overall efficiency level is still not high, and there is great room for improvement. The calculation results with and without environmental regulatory constraints indicate that, generally, production losses and compliance costs may be encountered in the industrial sector in Hubei, and there are significant differences by industry. The potential production losses and compliance costs in pollution-intensive industries are higher than those in clean production industries. On this basis, we propose relevant policy recommendations to improve the technological efficiency of Hubei's industrial environment, in order to promote the high-quality development of Hubei's industry in the post-epidemic era.
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Objective: To estimate the direct costs of hospital care according to coinfection in adult COVID-19 patients. Material(s) and Method(s): A retrospective follow-up study of adult patients hospitalized for COVID-19 between March and August 2020 at the San Vicente Foundation Hospitals (Medellin and Rionegro, Colombia). Patients whose diagnosis of SARS-Cov2 pneumonia was confirmed by RT-PCR test were included. Death from any cause and length of stay were considered outcome variables. Costs were estimated in 20 20 US dollars. Result(s): 365 patients with an average age of 60 years (IQR: 46-71), 40% female, were analyzed. 60.5% required an Intensive Care Unit (ICU). All-cause mortality was 2.87 per 100 patient-days. Patients admitted to the ICU who developed coinfection had an average length of stay of 27.8 days (SD:17.1) and an average cost of $23,935.7 (SD: $16,808.2);patients admitted to the ICU who did not develop a coinfection had an average length of stay of 14.7 days (SD:8.6) and an average cost of $9,968.5 (SD: $8,054.0). Conclusion(s): A high percentage of patients required intensive care, and there was a high mortality due to COVID-19. In addition, a higher cost of care was observed for those patients who developed coinfection and were admitted to ICU.Copyright © 2023 Asociacion Colombiana de Infectologia. All rights reserved.
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[...]best-in-class pharma companies are focusing on reliability and resilience in the supply chain-if they can't make a product or deliver a product on time, a patient is not served, and no sale is made. People can scale to a certain degree but scaling by a factor of 100 is not possible with people in a short period of time and does not deliver on economies of scale. Pharma companies are also issuing 'green bonds' where investors can expect the contribution of capital to improve the company's sustainability.
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PurposeThis paper presents a systematic review of the literature in the domain of maritime disruption management, upon which future research framework and agenda are proposed. Two review questions, i.e. the measures that are employed to manage disruptions and how these contribute to resilience performance, were pursued.Design/methodology/approachThe systematic literature review procedure was strictly followed, including identification and planning, execution, selection and synthesis and analysis. A review protocol was developed, including scope, databases and criteria guiding the review. Following this, 47 articles were eventually extracted for the systematic review to identify themes for not only addressing the review questions but also highlighting future research opportunities.FindingsIt was found that earlier studies mainly focused on measures, which are designed using mathematical models, management frameworks and other technical support systems, to analyse and evaluate risks, and their impacts on maritime players at the levels of organisation, transport system and region in which the organisation is embedded. There is, however, a lack of research that empirically examines how these measures would contribute to enhancing the resilience performance of maritime firms and their organisational performance as a whole. Subsequently, a Digitally Embedded and Technically Support Maritime Disruption Management (DEST-MDM) model is proposed.Research limitations/implicationsThis review is constrained by studies recorded by the Web of Science only. Nevertheless, the proposed research model would expectedly contribute to enhancing knowledge building in the specific domain of maritime disruption management and supply chain management overall while providing meaningful managerial implications to policymakers and managers in the maritime industry.Originality/valueThis research is perhaps one of the first studies which presents a systematic review of literature in maritime disruption management and proposes a future research framework that establishes the link between disruption management and resilience and organisational performance for empirical validation.
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PurposeThis study aims to investigate the relationships among monetary cost (stimulus), perceived greenwash fear, attitude and perceived behavioural control (organism-related factors) and green hotel patronage intention (response) using the stimulus-organism-response (S-O-R) model.Design/methodology/approachA total of 262 valid questionnaires were collected. Data were collected using the purposive sampling method and tested using the partial least squares (PLS) approach.FindingsMonetary cost is positively related to only one organism-related factor which is perceived greenwash fear. All organism-related factors are positively related to response, which is green hotel patronage intention. Attitude mediates the relationship between perceived greenwash fear and green hotel patronage intention, as well as perceived behavioural control and green hotel patronage intention.Research limitations/implicationsA longitudinal study can be performed in the future to observe the actual green hotel patronage behaviour of customers.Practical implicationsGreen hoteliers should focus on the development of communication strategies to enhance their corporate reputation. Green hoteliers also need to build trust by showing their green initiatives are genuine, identify consumers who are willing to pay more for green hotels and offer promotions with price incentives such as frequency discounts, coupons and rebates to increase interest and trialability.Originality/valueFew studies have focused on the use of monetary cost as a stimulus in the S-O-R model to predict green hotel patronage intention. This study also tested the mediating effect of attitude, one of the organism-related factors, in the model.
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Introduction and objective: Diabetes, with its medical complications and societal consequences, is one the most difficult concerns for modern society. The purpose of this narrative review is to characterize the selected public health challenges and opportunities resulting from diabetes in Poland, as well as to identify public health measures that may be adopted to lower the diabetes burden in Poland. Review methods: This narrative review is based on the literature about diabetes in Poland. Scientific papers on diabetes published between 1 January 2010-31 January 2023, available in the PubMed database, were identified using a combination of the following key words: 'diabetes', 'Poland', 'public knowledge', 'management' and 'costs'. Particular attention was paid to the following diabetes-related issues: (1) current and forecast prevalence of diabetes in Poland, (2) diabetic care before and after the COVID-19 pandemic onset, (3) public knowledge of diabetes and diabetes risk factors, and (4) public health interventions to reduce the diabetes burden at the population level. Abbreviated description of the state of knowledge: A continuous growth of both the incidence and the prevalence of diabetes is predicted. Due to insufficient public awareness of diabetes risk factors and symptoms, and the health-debt caused by COVID-19 pandemic, a further rise in the number of diabetic complications is expected, as well as an increase in public spending on health care and social insurance systems. Summary: Public health interventions targeted at preventing diabetes and its complications should not be confined to reducing complications and improving diabetes care, but also include a wide range of initiatives aimed at addressing the fundamental causes of diabetes. Future study should look at the cost-effectiveness of such initiatives in order to mobilize different stakeholders and society.
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Over it's more than 100-year history, the Kennecott operation has often been at the forefront of innovation;driven by the demands of the lower grade ore-body and the higher costs of operating in the US where wages are generally higher and regulation more restrictive. One way of reducing operating costs in c/lb is to increase the lbs produced at minimal cost. Despite the relatively coarse grind at Kennecott - about 30% >150μm, approximately 20% of the Cu lost to tail is liberated chalcopyrite in the <20μm fraction, and about 30%-40% in the <37μm fraction. In 2020 Kennecott undertook a detailed plant scale test of the magnetic aggregation technology to increase copper recovery by reducing fine copper losses. A paired statistical plant test of magnetic conditioning on one rougher line showed a 1.12% increase in Cu recovery to 97% statistical confidence. The next challenge, unforeseen at the start of the project, was the fabrication and transportation to site of the equipment for the three remaining rougher rows, during the severe supply-chain constraints of the Covid pandemic in 2021. This resulted in delays and unforeseen costs as world-wide transportation became chaotic, particularly transportation via west coast USA. Nevertheless, the project was completed and commissioned, with only minor delays and cost increases, due to a flexible approach to overcoming the hurdles encountered. Copyright © 2023 by SME.
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From 2018 to 2022, on average, 70% of the Brazilian effective electric generation was produced by hydropower, 10% by wind power, and 20% by thermal power plants. Over the last five years, Brazil suffered from a series of severe droughts. As a result, hydropower generation was reduced, but demand growth was also declined as results of the COVID-19 pandemic and economic recession. From 2012 to 2022, the Brazilian reservoir system operated with, on average, only 40% of the active storage, but storage recovered to normal levels in the first three months of 2022. Despite large capacity of storage reservoirs, high volatility of the marginal cost of energy was observed in recent years. In this paper, we used two optimization models, NEWAVE and HIDROTERM for our study. These two models were previously developed for mid-range planning of the operation of the Brazilian interconnected power system. We used these two models to optimize the operation and compared the results with observed operational records for the period of 2018-2022. NEWAVE is a stochastic dual dynamic programming model which aggregates the system into four subsystems and 12 equivalent reservoirs. HIDROTERM is a nonlinear programming model that considers each of the 167 individual hydropower plants of the system. The main purposes of the comparison are to assess cooperation opportunities with the use of both models and better understand the impacts of increasing uncertainties, seasonality of inflows and winds, demand forecasts, decisions about storage in reservoirs, and thermal production on energy prices. © World Environmental and Water Resources Congress 2023.All rights reserved
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Knowledge payment is a new method of electronic learning that has developed in the era of social media. With the impact of the COVID-19 pandemic, the market for knowledge payment is rapidly expanding. Exploring the factors that influence users' sustained willingness is beneficial for better communication between knowledge payment platforms and users, and for achieving a healthier and more sustainable development of the knowledge payment industry. The model of unsustainable usage behavior of knowledge payment users was constructed on the basis of expectation inconsistency theory, price equilibrium theory, and perceived value theory, using the 'cognitive-emotional-behavioral' model framework of cognitive emotion theory. The data were collected from 348 users through a web-based questionnaire and analyzed using structural equation modeling. Findings show that expectation inconsistency, price equilibrium, and quality value, emotional value, and social value have significant effects on discontinuous use intentions. Discontinuous use intentions also significantly affect discontinuous use behavior. © 2013 IEEE.
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PurposeCapital structure is an important corporate financing decision, particularly for companies in emerging economies. This paper attempts to understand whether the pandemic had any significant impact on the capital structure of companies in emerging economies. India being a prominent emerging economy is an ideal candidate for the analysis.Design/methodology/approachThe study utilizes three leverage ratios in an extended market index, BSE500, for the period 2015–2021. The ratios considered are short-term leverage ratio (STLR), long-term leverage ratio (LTLR) and total leverage ratio (TLR). A dummy variable differentiates the pre-epidemic (2015–2019) and pandemic (2020–2021) period. Control variables are used to represent firm characteristics such as growth, tangibility, profit, size and liquidity. Dynamic panel data regression is employed to address endogeneity.FindingsThe findings point out that Covid-19 has had a significant, negative effect on LTLR, while the impact on STLR and TLR was insignificant. The findings indicate that companies based in a culturally risk-averse environment, such as India, would reduce the long-term debt to avoid bankruptcy in times of uncertainty.Research limitations/implicationsThe study covers the impact of the pandemic on Indian companies. Hence, generalization of the findings to global context might not be valid.Practical implicationsTo maintain economic growth in the post-crisis period, Indian policymakers should ensure accessibility to low-cost capital. The findings provide impetus to deepen the insignificant corporate bond market in India for future economic revival.Originality/valueDeveloping countries are struggling to revive the economies postpandemic. This is particularly true for Asian economies which are heavily reliant on banks for survival. This research finds evidence to utilize bond market as a source of raising capital for economic revival.
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There is a need for synchronous and inclusive online peer tutoring in large, undergraduate classes. As a lack of data or internet connectivity may limit online peer tutoring, the use of a data-free instant messenger was implemented for online tutoring in a class of 342 students. The Moya application allows students to chat and send voice notes to tutors and peers without using data. Sending attachments incurs data costs but the amount of data is displayed prior to downloading. The qualitative interpretivist case study used data collected from purposive sampling via an online survey. Consent was received from 252 third-year Information Systems students at a historically disadvantaged university. Qualitative data were analysed via thematic content analysis using the Unified Theory of Acceptance and Use of Technology 2 model as a theoretical basis. Findings indicate that the majority of students (85.7%) did not use the data-free Moya instant messenger. Reasons for the low usage included a negative performance expectancy, as students did not see the benefit in using the application to engage with peers or tutors. Perceived effort expectancy was low, as students did not desire to learn to use a new application. Results showed that using WhatsApp was a habit. Moreover, social influence was a factor, as fellow students and tutors were also using WhatsApp. Students recommended increasing awareness of the Moya application and providing training. The price value was expected to be a significant factor as this application does not require data, but this was not the case. Facilitating conditions show that students had data for WhatsApp. Moya has the same interface design as the preferred WhatsApp so learning to use the application should require minimal effort. The unexpected findings indicate that students prefer WhatsApp, an instant messenger that requires data, over a datafree instant messenger. The findings leave lecturers questioning whether using WhatsApp for online peer tutoring is the more viable option.
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Traces of touch provide valuable insight into how we interact with the physical world. Measuring touch behavior, however, is expensive and imprecise. Utilizing a fluorescent UV tracer powder, we developed a low-cost analog method to capture persistent, high-contrast touch records on arbitrary objects. We describe our process for selecting a tracer, methods for capturing, enhancing, and aggregating traces, and approaches to examining qualitative aspects of the user experience. Three user studies demonstrate key features of this method. First, we show that it provides clear and durable traces on objects representative of scientific visualization, physicalization, and product design. Second, we demonstrate how this method could be used to study touch perception, by measuring how task and narrative framing elicit different touch behaviors on the same object. Third, we demonstrate how this method can be used to evaluate data physicalizations by observing how participants touch two different physicalizations of COVID-19 time-series data. © 2023 ACM.
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This study models the United States' response to the COVID-19 pandemic from a transaction cost perspective, with the objective of considering the most efficient delivery of universal health care to the public. The neoclassical framing of production, price, and allocation does not consider the transaction costs resulting from the pandemic's broad effects on the entire economy. The intention of this study is to focus on transaction cost as a particular feature of cost efficiency analyses. The study reveals the effect of pandemic conditions on transaction-specific health-care assets. It considers the asset of registered nursing labor, specifically the changes in travel nurses' compensation during the period 2019 to 2020. This study finds that the doctrine of federal preemption instituting universal health care is economizing due to the lower transaction costs associated with the administrative control of transaction-specific assets and the advancement of collaboration between organizations. The COVID-19-induced transaction cost effects on travel nurse compensation reveal the extent to which the private health-care system operates with implicit inefficiency. This study calculates a residual cost index using U.S. Bureau of Labor Statistics and industry-sourced data. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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PurposeThis study aims to investigate the relationships between loan growth, loan losses and net income after the 2008 global financial crisis. This study further conducts a comparative analysis by considering the period of COVID-19. Design/methodology/approachThis study uses panel data models such as one-step system GMM, random effects, fixed effects and OLS, with a data set of 131 Chinese commercial banks from 2009 to 2020. FindingsThe study finds no significant relationship between loan growth and future loan losses. However, after adjusting loan loss by net interest income (NII-adjusted loan loss), the study reveals that loan growth in the subsequent year decreases if NII-adjusted loan loss increases. The study also demonstrates the positive effect of loan growth on net income as newly expanded loans are funded at similar costs but offered at a lower rate compared with existing loans. During COVID-19, loan growth and net income were higher than in previous years. Originality/valueThe findings suggest that Chinese banks can increase lending to support the economy without sacrificing loan quality, emphasizing the importance of maintaining and enhancing credit policies and practices. Chinese banks should also continue to refine their pricing strategies for loans and deposits. The findings also imply that China's policy responses to the impact of COVID-19 could serve as lessons for future policy decisions.
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This research determines the impacts of COVID-19 US on crawfish production and consumption for 2020 and 2021 using an Equilibrium Displacement Model. In the US, crawfish is one of the seafood commodities where most production is consumed by domestic consumers (7% of domestic consumption is from imports). Crawfish and rice are complementary. Therefore, the impacts of COVID-19 on crawfish consumption simultaneously influence rice production and crawfish producers and consumers. In the first year of COVID-19 (2020), the reduction in crawfish retail demand caused negative effects on final consumers and producers. However, crawfish consumption recovered significantly in the second year (2021), which could compensate for the loss in 2020. Overall, consumer and producer gains ranged from $549 to $626 million if the COVID-19 pandemic only impacted retail consumption. However, in 2021, the increase in production costs due to higher oil/diesel prices and other input prices caused the farm supply to decrease. As a result, total welfare gains ranged from $200 to $228 million. If the demand in 2021 did not increase, but the crawfish farm supply decreased, consumer and producer losses ranged from $929 to $1045 million. Overall, the total effects of COVID-19 on consumers and producers for 2020 and 2021 depend on its effects in 2021. If the demand in 2021 increased following the decrease in farm supply, consumers and producers would benefit from the shocks of COVID-19 due to higher post-COVID-19 demand.
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This dissertation is composed of three chapters. While the chapters pertain to very different contexts, an overarching theme is the analysis of human behavior in response to policies that are inherently economic.The first chapter is the product of joint work with Justin Holz and Rafael Jimenez Duran. It studies repugnance towards price gouging. Emergencies like natural disasters or pandemics trigger sharp price increases for essential products. Anti-price gouging laws are ubiquitous and people take costly actions to report violators to law-enforcement agencies, which suggests that they value punishing sellers that spike prices in these situations. This chapter uses a field experiment to understand individuals' willingness to report sellers who increase the price of personal protective equipment at the height of the COVID-19 pandemic. We argue that reporting decisions contain information about repugnance to price gouging and find that willingness to pay to report is non-trivial and heterogeneous. We also find evidence that repugnance is partly due to distaste for seller profits, depending on the product. These results suggest that regulation discussions would benefit from incorporating repugnance into welfare and from addressing products separately.The second chapter focuses in the use of temporary driving restrictions as a tool for air quality management in Mexico City. Road congestion is understood to be a major source of urban air pollution and is also associated with other large non-health-related costs. Millions of people live in cities in which the number of cars on the road is controlled by allowing or prohibiting the use of a car on a given day depending on its license plate number. The empirical evidence available suggests little benefit from these programs;the policy increases the marginal cost of using the road for some users while decreasing it for others and incentivizes the acquisition of extra vehicles. This chapter studies the effect of temporary increases in the stringency of the restrictions as an add-on policy intended to alleviate extreme pollution events. The increased restrictions are triggered by Ozone levels surpassing a pre-specified threshold. This, coupled with the fact that said threshold was modified several times between 2005 and 2018, allows us to identify the effect of the policy. We document a sizable increase in the average speed of cars in the city during restricted days. This suggests the policy does alleviate congestion. We also observe a reduction on Carbon Monoxide and Ozone concentration, but these results are not robust to changes in the specification's functional form. While we cannot explicitly quantify welfare effects, the minor improvements are unlikely to compensate the major disruption in the commuter network without serious investment in public transit alternatives.The third chapter, co-authored with Enrique Seira and Alan Elizondo, investigates the role of information disclosure on financial markets as tool for consumer protection. We implement a randomized control trial in the Mexican credit card market for a large population of indebted cardholders and measure the impact of disclosures of interest rate and time required to pay outstanding debt on default, indebtedness, account closings, and credit scores;these disclosures are required by law in the United States. We also test the effect debiasing warning messages and social comparison information has on the same outcomes. We find that providing salient interest rate disclosures had no effects, while comparisons and debiasing messages had only modest and short-lived effects at best. We conduct extensive external validity exercises in several banks, with different disclosures, and with actual policy mandates. We conclude the null result is robust. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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COVID-19 pandemic brought up issues with healthcare costs, national economic development and welfare of the society in forefront. Nations across the globe followed different approaches to deal with COVID-19, such as zero tolerance, herd immunity, containment to build treatment capability. National healthcare became a contentious sociopolitical issue involving healthcare costs, technologies and societal health. In the United States even during the COVID-19 pandemic, the government approach was pursuing a sustainable improvement in patient care through adoption of medical and information technologies. The national healthcare policies are framed around technological interventions with the assumption that deployment of technologies could keep healthcare costs under control and at the same time improve health outcomes. However, evidences show that the healthcare costs are in the rise even with impressive progress in technological deployment. This article highlights some of the recent trends in healthcare costs, technological preparedness, medical technology developments in managing COVID-19 pandemic. The US government mandated electronic health record (EHR) systems implementation and assess its impact on healthcare costs and health outcomes. This article emphasizes the need for understanding the interconnectedness of costs, technology and societal health.