Embedding Isolation, Contact Tracing, and Quarantine in Transmission Dynamics of the Coronavirus Epidemic—A Case Study of COVID-19 in Wuhan

Coronaviruses have caused multiple global pandemics. As an emerging epidemic, the coronavirus disease relies on nonpharmacological interventions to control its spread. However, the specific effects of these interventions are unknown. To evaluate their effects, we extend the susceptible–latent–infectious–recovered model to include suspected cases, confirmed cases, and their contacts and to embed isolation, close contact tracing, and quarantine into transmission dynamics. The model simplifies the population into two parts: the undiscovered part (where the virus spreads freely—the extent of freedom is determined by the strength of social distancing policy) and the discovered part (where the cases are incompletely isolated or quarantined). Through the isolation of the index case (suspected or confirmed case) and the subsequent tracing and quarantine of its close contacts, the infections flow from the undiscovered part to the discovered part. In our case study, multisource data of the novel coronavirus SARS-CoV-2 (COVID-19) in Wuhan were collected to validate the model, the parameters were calibrated based on the prediction of the actual number of infections, and then the time-varying effective reproduction number was obtained to measure the transmissibility of COVID-19 in Wuhan, revealing the timeliness and lag effect of the nonpharmacological interventions adopted there. Finally, we simulated the situation in the absence of a strict social distancing policy. Results show that the current efforts of isolation, close contact tracing, and quarantine can take the epidemic curve to the turning point, but the epidemic could be far from over; there were still 4,035 infected people, and 1,584 latent people in the undiscovered part on March 11, 2020, when the epidemic was actually over with a strict social distancing policy.

Frontiers in Service Science: Integrating ESG Measures and Supply Chain Management: Research Opportunities in the Postpandemic Era

The COVID-19 pandemic has highlighted the instrumental role of supply chains in delivering economic, human, and societal value. At the same time, the pandemic has intensified interest among businesses, governments, and academics to examine environmental, social, and governance (ESG) issues. In today’s hyper-globalized economy, ESG measures are futile unless they explicitly incorporate a firm’s end-to-end operations throughout its entire supply chain. On the other hand, well-calibrated ESG measures should play a central role in guiding a firms’ day-to-day supply chain management practices. To illustrate the value of unifying ESG and end-to-end supply chain thinking, we present three supply chain cases that arose amid the COVID-19 pandemic, involving online platforms; public health supply chains; and vaccine development, manufacturing, and distribution, respectively. Drawn from these three cases, we spotlight some new research opportunities in both ESG and supply chain management.

Linking Customization Capability with CRM Technology Adoption and Strategic Alignment

Building on contingency theory and the input–process–output model, this paper investigates the relationships between customer relationship management (CRM) technology adoption, customization capability, CRM effectiveness, and strategic alignment. By surveying senior managers of customized service projects from 288 information technology service firms in Taiwan, we find that CRM technology adoption has a positive relationship with customization capacity, which is, in turn, positively correlated with CRM effectiveness with the correlation being moderated by strategic alignment. This study suggests that CRM marketing and operational technologies can enhance CRM effectiveness via customization capability. This study also uncovers approaches to achieving enhancement.

Optimal Pooling, Batching, and Pasteurizing of Donor Human Milk

Human breast milk provides nutritional and medicinal benefits that are important to infants, particularly those who are premature or ill. Donor human milk, collected, processed, and dispensed via milk banks, is the standard of care for infants in need whose mothers cannot provide an adequate supply of milk. In this paper, we focus on streamlining donor human milk processing at nonprofit milk banks. On days that milk is processed, milk banks thaw frozen deposits, pool together milk from multiple donors to meet nutritional specifications of predefined milk types, bottle and divide the pools into batches, and pasteurize the batches using equipment with various degrees of labor requirements. Limitations in staffing and equipment and the need to follow strict healthcare protocols require productive, expedient, and frugal pooling strategies. We formulate integer programs that optimize the batching-pasteurizing decisions and the integrated pooling-batching-pasteurizing decisions by minimizing labor and meeting target production goals. We further strengthen these formulations by establishing valid inequalities for the integrated model. Numerical results demonstrate a reduction in the optimality gap through the strengthened formulation versus the basic integer programming formulation. A case study at Mothers’ Milk Bank of North Texas demonstrates significant improvement in meeting milk type production targets and a modest reduction in labor compared with former practice. The model is in use at Mothers’ Milk Bank of North Texas and has effectively improved their production balance across different milk types.

Appreciation to Referees, 2021

Saif Benjaafar, Editor-in-Chief of Service Science, thanks the referees who have generously provided expert counsel and guidance on a voluntary basis to the journal. Without them, the journal would not be able to function. The following list acknowledges those who acted as referees for papers considered during this past calendar year.

COVID-19 and Hotel Productivity Changes: An Empirical Analysis Using Malmquist Productivity Index

This research investigates the impact of COVID-19 on hotel productivity change using the Malmquist Productivity Index (MPI). For 26 U.S. hotel brands, productivity changes over 10 quarters from the first quarter of 2018 to the second quarter of 2020 were analyzed. After the COVID-19 outbreak, the investigated hotels’ productivity deteriorated. Decomposition revealed that, whereas technical efficiency change (EC) improved, technological change (TC) regressed, resulting in deterioration of the MPI. The investigated hotels’ EC-related practices included enhanced cleaning operations, partnering with a hygiene brand, cutting the workforce, and pay cuts. Practices related to TC included the adoption of new hygiene technology and setting a new standard at the organizational level through the formation of a global council and accreditation related to disinfection and hygiene. Our results show that though U.S. hotels are trying to improve their productivity by efficiently utilizing resources, frontier technology’s regress is decreasing productivity. Our results support the importance of investment in technology for productivity management. This research provides empirical evidence for the need for hotels to pursue technological advances to overcome the pandemic.

Service Delivery Strategies for Alleviating Pandemic Suffering While Maintaining Profitability

The postpandemic world requires a renewed focus from service providers on ensuring that all customer segments receive the essential services (food, healthcare, housing, education, etc.) that they need. Philanthropic service providers are unable to cope with the increased demand caused by the social, economic, and operational challenges induced by the pandemic. For-profit service providers offering no-pay services to customers, allowing them to self-select a service option, is becoming a popular strategy in various settings. Obtaining insights into how to efficiently balance societal and financial goals is critical for a for-profit service provider. We develop and analyze a quantitative model of customer utilities, vertically differentiated product assortment, pricing, and market size to understand how service providers can effectively use customer segmentation and serve the poor in the lowest economic strata. We identify conditions under which designing the service delivery to be accessible to the poor can simultaneously benefit the for-profit service provider, customers, and the entire society. Interestingly, we observe that the increasing customer valuation of the no-pay option because of a superior quality service offered by a service provider need not benefit customers. Our work provides a framework to obtain operational, economic, and strategic insights into socially responsible service delivery strategies.