ABSTRACT
The COVID-19 pandemic has triggered a set of government policies and supermarket regulations, which affects customers' grocery shopping behaviours. However, the specific impact of COVID-19 on retailers at the customer end has not yet been addressed. Using text-mining techniques (i.e., sentiment analysis, topic modelling) and time series analysis, we analyse 161,921 tweets from leading UK supermarkets during the first COVID-19 lockdown. The results show the causes of sentiment change in each time series and how customer perception changes according to supermarkets' response actions. Drawing on the social media crisis communication framework and Situational Crisis Communication theory, this study investigates whether responding to a crisis helps retail managers better understand their customers. The results uncover that customers experiencing certain social media interactions may evaluate attributes differently, resulting in varying levels of customer information collection, and grocery companies could benefit from engaging in social media crisis communication with customers. As new variants of COVID-19 keep appearing, emerging managerial problems put businesses at risk for the next crisis. Based on the results of text-mining analysis of consumer perceptions, this study identifies emerging topics in the UK grocery sector in the context of COVID-19 crisis communication and develop the sub-dimensions of service quality assessment into four categories: physical aspects, reliability, personal interaction, and policies. This study reveals how supermarkets could use social media data to better analyse customer behaviour during a pandemic and sustain competitiveness by upgrading their crisis strategies and service provision. It also sheds light on how future researchers can leverage the power of social media data with multiple text-mining methodologies. © 2022 The Authors
ABSTRACT
Background: Different degrees of liver injury have been reported in COVID-19 patients. However, the impact of COVID-19 on long-term liver functions remains unclear. We aimed to characterize COVID-19 patients with residual liver function abnormality over time up to 1 year after COVID-19 diagnosis. Methods: All COVID-19 patients diagnosed between 23 January 2020 and 1 May 2020 in Hong Kong were identified by a territory-wide electronic database managed by Hospital Authority, Hong Kong, and retrospectively studied. All suspected and confirmed cases of COVID-19 in Hong Kong are reported to the Department of Health and hospitalized under the care of the Hospital Authority. The outcomes of interest were residual abnormality in alanine aminotransferase (ALT), alkaline phosphatase (ALP), and total bilirubin over 1 year after COVID-19 diagnosis. The upper limit of normal (ULN) of ALT and total bilirubin were 40 U/L and 19 μmol/L, respectively. The age- and gender-specific ULN of ALP was defined by each of the local laboratories. Results: Of 1,040 COVID-19 patients included, i.e. all the cases reported to the Department of Health, the mean age was 38±18 years, 560 (53.8%) were male, 4.1% and 0.3% had hepatitis B and C virus infection, respectively;7.8% had diabetes and 13.8% had hypertension;none had liver cirrhosis and 7 (0.7%) died. Among 1,004 patients with liver biochemistries on day 0-30, 182 (18.1%), 88 (8.8%), and 72 (7.2%) had ALT ≥2xULN, total bilirubin ≥2xULN, and ALP ≥ULN on day 0-30, respectively. For patients with ALT ≥2xULN on day 0-30, 46.8% had ALT normalized on day 31-90;the percentage of normal ALT increased to 71.6% on day 91-180 and 71.4% on day 181-365 (P=0.002). For patients with total bilirubin ≥2xULN on day 0-30, 84.2% had total bilirubin normalized on day 31-90;the proportion of normal total bilirubin remained stable till day 181-365 (P=0.126). For patients with ALP >ULN on day 0-30, 64.9% had ALP normalized on day 31-90;the percentage of normal ALP increased to 80.6% on day 91-180 and 86.2% on day 181-365 (P=0.033) (Figure). Compared to 121 COVID-19 patients with ALT <2xULN on day 31-90, the 20 patients with prolonged ALT ≥2xULN on day 31-90 had higher ALP and lymphocyte counts during COVID-19;the proportion of patients with chronic hepatitis B and C, alcohol dependence, diabetes and hypertension were not significantly different between the two groups. Two (10.0%) patients with ALT ≥2xULN on day 31-90 died, while no patients with ALT <2xULN on day 31-90 died (P=0.019). Conclusion: A minority of patients had residual liver function abnormality up to 1 year after COVID-19 diagnosis. Prolonged abnormal ALT may be due to more severe liver function abnormality during COVID-19.
ABSTRACT
New product development to enhance companies’ competitiveness and reputation is one of the leading activities in manufacturing. At present, achieving successful product design has become more difficult, even for companies with extensive capabilities in the market, because of disorganisation in the fuzzy front end (FFE) of the innovation process. Tremendous amounts of information, such as data on customers, manufacturing capability, and market trend, are considered in the FFE phase to avoid common flaws in product design. Because of the high degree of uncertainties in the FFE, multidimensional and high-volume data are added from time to time at the beginning of the formal product development process. To address the above concerns, deploying big data analytics to establish industrial intelligence is an active but still under-researched area. In this paper, an intelligent product design framework is proposed to incorporate fuzzy association rule mining (FARM) and a genetic algorithm (GA) into a recursive association-rule-based fuzzy inference system to bridge the gap between customer attributes and design parameters. Considering the current incidence of epidemics, such as the COVID-19 pandemic, communication of information in the FFE stage may be hindered. Through this study, a recursive learning scheme is established, therefore, to strengthen market performance, design performance, and sustainability on product design. It is found that the industrial big data analytics in the FFE process achieve greater flexibility and self-improvement mechanism on the evolution of product design.
ABSTRACT
Background: Different degrees of liver injury were reported in patients infected by Coronavirus disease 2019 (COVID-19) It is possibly caused by systemic inflammation and adverse drug reactions in severe COVID-19 patients under different medical treatments However, the impact of liver injury on adverse clinical outcomes remains unclear We aimed to examine the impact of liver injury on clinical outcomes in COVID-19 patients Methods: All COVID-19 patients reported to the Department of Health between 23 January 2020 and 1 May 2020 in Hong Kong were identified using an electronic database managed by Hospital Authority, Hong Kong, and retrospectively studied Alanine aminotransferase (ALT)/ aspartate aminotransferase (AST) elevation was defined as ALT/AST ≥2x upper limit of normal (ULN) (i.e. 80 U/L) Acute liver injury was defined as ALT and/or AST ≥2xULN, with total bilirubin ≥2xULN (i.e. 38 μmol/L) and/or international normalized ratio (INR) ≥1.7. The primary endpoint was a composite of intensive care unit (ICU) admission, use of invasive mechanical ventilation, and/or death Results: 1,040 COVID-19 patients were identified. Their mean age was 38±18 years, 560 (53 8%) were male, 4 1% and 0 3% had hepatitis B and C virus infection, respectively;53 (5 1%) were admitted to ICU, 22 (2 1%) received invasive mechanical ventilation, and 4 (0 4%) died Among 816 COVID-19 patients who had serial measurement of liver biochemistries, 184 (22 5%) had ALT/ AST elevation and 15 (1 8%) had acute liver injury Acute liver injury was more common in patients who had hepatitis B/C virus infection than those who did not have (9 4% vs. 1 8%, P=0 026) ALT/AST elevation (adjusted odds ratio [aOR] 7 92, 95% CI 4 14-15 14, P<0 001) and acute liver injury (aOR 6 40, 95% CI 1 78-23 07, P=0 005) were independently associated with development of primary endpoint (Table) Use of lopinavirritonavir ± ribavirin + interferon beta (aOR 1 94, 95% CI 1 20- 3 13, P=0 006) and corticosteroids (aOR 3 92, 95% CI 2 14- 7 16, P<0 001) were independently associated with ALT/AST elevation Use of corticosteroids was associated with acute liver injury (aOR 4 76, 95% CI 1 56-14 50, P=0 006), while all 15 patients who developed acute liver injury also usedlopinavir-ritonavir ± ribavirin ± interferon beta Conclusion: ALT/AST elevation and acute liver injury were independently associated with adverse clinical outcomes in COVID-19 patients Use of lopinavir-ritonavir, with or without ribavirin, interferon beta and/or corticosteroids were associated with ALT/AST elevation and acute liver injury in COVID-19 patients.