Examining the issue of employee intentions to learn and adopt digital technology. (Special Issue: How is hospitality education embedding sustainable practices in their curriculum and programme delivery? an Asian perspective.)

Purpose: In the post-COVID-19 era, the hospitality industry is rapidly moving towards digitalization, which requires employees to upgrade their knowledge and skills. Some employees resist those changes and refuse to upgrade their knowledge, skills and ways of doing things. Therefore, there is a need to understand this unexplored area and so this study examines employee intentions to embrace digital technology from the perspective of upgrading their skills and knowledge. The study investigates the moderating role of the employees' resistance to change motive (RCM) on their intention to embrace digital technology, especially in the post-COVID-19 pandemic scenario. Design/methodology/approach: The research is conducted using dynamic capability view (DCV) theory and status quo bias (SQB) theory. Drawing on the existing literature in this area, a theoretical model is developed, which is validated using the structural equation modelling technique to analyse data from hospitality industry employees. Findings: The results indicate that employees' dynamic capability plays a significant role in employees' upgrading their skill and knowledge capabilities, and this significantly improves employee intention to embrace digital technology. It also finds that the employee RCM plays a significant role in the relationship between upgrading skill capability and their knowledge capability to relation to embracing digital technology. Originality/value: The findings could be used by hospitality managers to better understand employee intentions with regard to adopting digital technology, challenges faced and the way forward.

Emerging COVID waste and its impact on the aquatic environment in India

A highly transmissible and pathogenic Coronavirus SARS-CoV-2 has caused the COVID-19 pandemic, which severely affected human health and impacted negatively on the environment. In this review, we discuss the extent of the generation of COVID waste, and how its disposal can influence the environment. We have especially emphasized the COVID-related biomedical waste management. An attempt has also been made to identify several challenges encountered in India. Studies have indicated an altered water usage pattern, which increased megacities' water footprint in India. Enhanced domestic sewage discharge resulted in higher fecal coliform count in water bodies. Disposal of COVID biomedical waste (CBW) and personal protective equipment (PPE) resulted in a huge amount of single-use plastics (SUPs);which in turn cause the long-term risk of micro- and nano-plastic in the environment. This review also aims to put up the need for well-equipped infrastructure, efficient treatment facility, and public availability of CBW data in India to make effective policies and sustainable solutions for long-term goals. © 2023 Elsevier Inc. All rights reserved.

Investigating the predictors and outcomes of social entrepreneurship in post-COVID-19 period: moderating role of dynamic technology capability

In the post-COVID-19 period, social entrepreneurship is becoming extremely important, as it generates employment, and improves economic prosperity and solves various issues for society. Not many studies have attempted to understand the social entrepreneurship phenomena in post-COVID-19 period and its impact on society. Thus, there is a research gap, which this study aims to fill. This paper aims to analyse the impacts of intellectual capital and entrepreneurial ability on social entrepreneurship, and its impact on society in the post-COVID-19 period, moderated by technology capability. By the inputs of literature and lending knowledge from theories, a research model is prepared. It was verified using structural equation modelling with data collected through a survey. The study finds that intellectual capital and entrepreneur ability both significantly and positively impact social entrepreneurship. This study implies that intellectual capital and entrepreneurial ability could impact social entrepreneurship when moderated by technology capability, which in turn has social impact in the post-COVID-19 period. Also, the study highlights the moderating role of technology capability on social entrepreneurship.

Examining the issue of employee intentions to learn and adopt digital technology

Purpose: In the post-COVID-19 era, the hospitality industry is rapidly moving towards digitalization, which requires employees to upgrade their knowledge and skills. Some employees resist those changes and refuse to upgrade their knowledge, skills and ways of doing things. Therefore, there is a need to understand this unexplored area and so this study examines employee intentions to embrace digital technology from the perspective of upgrading their skills and knowledge. The study investigates the moderating role of the employees' resistance to change motive (RCM) on their intention to embrace digital technology, especially in the post-COVID-19 pandemic scenario. Design/methodology/approach: The research is conducted using dynamic capability view (DCV) theory and status quo bias (SQB) theory. Drawing on the existing literature in this area, a theoretical model is developed, which is validated using the structural equation modelling technique to analyse data from hospitality industry employees. Findings: The results indicate that employees' dynamic capability plays a significant role in employees' upgrading their skill and knowledge capabilities, and this significantly improves employee intention to embrace digital technology. It also finds that the employee RCM plays a significant role in the relationship between upgrading skill capability and their knowledge capability to relation to embracing digital technology. Originality/value: The findings could be used by hospitality managers to better understand employee intentions with regard to adopting digital technology, challenges faced and the way forward. © 2023, Emerald Publishing Limited.

Investigating the employee's customer orientation behaviour: a comparison of the circumstances before and after the pandemic from policy perspective

Purpose: The aim of this research is to investigate how jay customer influence service employees' customer orientation behaviour before and after COVID-19 from a policy perspective. This study will also assess whether jay customer or abusive supervision had a greater or lesser impact on service workers' emotional stage and customer orientation during COVID-19. Design/methodology/approach: The research adopted longitudinal approach to collect the data from Indian service employees engaged in various service organisations (such as airlines, hotels and restaurants). The gathered data over a 13-month period, with (T1) November 2019 and (T2) December 2020. A total of 412 employees responded to the T1 survey. Thirteen months later, of the 412 T1 respondents, 381 returned the second survey. The data collected through questionnaire via both personally visiting the hotel restaurants and airport and through online mode. The research used structural equation modelling and ANOVA for the analysis of results. Findings: The results revealed that the indirect adverse effect of jay customer and abusive supervision on customer orientation via burnout has increased since the start of the pandemic. Furthermore, due to burnout, jay customers had a greater indirect influence on CO during the pandemic than abusive supervision. The result also shows that male employees experience the uncivil behaviour by the customer and the supervisor more frequently than that of female and transgender employees. These findings can be used to efficiently manage the stress of frontline service workers and to suggest policies during times of crisis, such as COVID-19. Research limitations/implications: This study contributes to the field of behavioural studies, mainly in the context of Indian hospitality industry. Policymakers and future researchers can use these findings to understand different customer-related issues from perceptive of Indian customer. Originality/value: The originality and value of this study is related to its pioneering study of jay customer and abusive supervision before and after COVID-19 from policy perspective of Indian service sector. The value of such research work is associated with both scholarly and executive implications. Regarding the latter, this study examines the myopic nature of uncivil behaviour and helps service firms to understand and manage its different forms, conclusively also providing practicable executive directions on the problem. © 2023, Emerald Publishing Limited.

Digital resilience and new business models in the post-COVID-19 scenario: from B2B perspective in the era of knowledge economy

Purpose: The purpose of this study is to examine how the pandemic impacted on business-to-business (B2B) cooperation and coordination, as well as on firms' financial and operational performance, from the B2B context in the era of knowledge economy. Design/methodology/approach: With the help of social network theory, coordination theory and existing literature, a theoretical model was developed conceptually. Later, the conceptual model was validated using structural equation modelling technique with consideration of 712 respondents from different firms who are engaged in managing B2B relationships on behalf of their firms. Findings: The study found that the COVID-19 pandemic has had a considerable moderating impact on the relationship between B2B cooperation and coordination with B2B relationship satisfaction. The study also highlighted that there is a degradation of financial and operational performance of firms due to the impact of COVID-19 pandemic on their B2B relationship management. Practical implications: There is a challenging and ever-evolving global economy caused by the COVID-19 pandemic. Although it is argued that the pandemic has accelerated the growth of some online firms, it has also had a catastrophic effect, culminating in many firms failing. This study has developed a new business model which helps in improving financial as well as operational performance of the firms in post COVID-19 scenario, especially in the era of knowledge economy. Originality/value: This is a unique study as this study (1) develops a unique theoretical model with high explanative power, (2) demonstrates how digital reliance and new business model help the firms in post COVID-19 pandemic and (3) adds to the body of literature in the domain of digital reliance, knowledge economy and B2B relationship management. © 2023, Emerald Publishing Limited.

Revisiting the resource-based view (RBV) theory: from cross-functional capabilities perspective in post COVID-19 period

Due to ever-changing business context, researchers and academicians revisit established theories to examine their validity underdifferent evolving scenarios. Therefore, this study aims to examine the cross-functional capabilities of the organizations by revisiting the resource-based view (RBV) theory, especially focusing on thepost-COVID-19 period. This study also investigates the moderating role of the organization strategic management ability and itsinfluence on the performance of the organizations. After reviewing existing literature and applying RBV theory, a theoretical model was developed conceptually. Later, the conceptual model was validated using the structural equation modeling (SEM) technique with a survey of 342 usable respondents from 21 organizations. The study found thatRBV theory is useful and relevant for explaining organization cross-functional capabilities even in the post-COVID-19 period. We found that cross-functional capabilities have positively impacted overall organization capability, which then positively influences organization performance. The study also found that there is apositive moderating impact of strategic management ability onorganization performance. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Beliefs about vaccination and relation to COVID-19 vaccination side-effects in asthma patients

Background: Clinical trials of COVID-19 vaccination provide evidence of side effects in the placebo group, consistent with some side effects reporting being a nocebo effect (Amanzio M, et al. Lancet Reg Health Eur 2022;12:100253) Aim: To investigate whether side effects of COVID-19 vaccination are associated with negative beliefs about vaccination. Method(s): European patients with severe asthma (SHARP network) completed a questionnaire (May-June 2021) about their vaccination status, the Vaccination Attitudes EXamination (VAX) Scale, a measure of vaccination hesitancy related to four different types of belief, and if vaccinated whether they experienced side effects (none, mild, severe). Result(s): 660 patients from 12 European countries participated, of whom 497 had at least a first vaccination and also completed the VAX questions and side effects. Of these patients, those reporting severe side effects (5.7%) compared to those with mild (48.2%) or no side effects (43.8%) had significantly (p = 0.001, ANOVA) more mistrust of vaccine efficacy, more concerns about future effects and more concerns about profiteering but not significantly more preference for natural immunity (Fig 1). Conclusion(s): People with severe asthma who have negative beliefs about vaccination are more likely to report severe side effects to COVID-19 vaccination. Consistent with the nocebo effect, negative beliefs create negative expectations and side effects. (Figure Presented).

Humoral immune responses to COVID-19 vaccines are reduced in patients with severe asthma

Background: Patients with severe asthma (SA) may be at higher risk of severe COVID-19 (C-19) illness. C-19 vaccines aim to reduce number and severity of infections. Patients with SA are often treated with maintenance oral corticosteroids (mOCS) and/or biologics (mAb)- it is unknown if vaccines will generate the same protective responses in patients with SA on such therapies. Aim(s): To compare magnitude and range of post-vaccination (PV) antibody responses (IgG) in patients with SA on mAb, mOCS or high-dose inhaled corticosteroids (ICS) with healthy controls (HC) without asthma. Method(s): The Virtus finger-prick quantitative C-19 antibody test was used to detect IgG levels 16-24 weeks post second-dose of the C-19 vaccine (123 AstraZeneca, 56 Pfizer, 5 Moderna). IgG>0.2AU was considered positive with range: very high >1.25AU, high 0.751-1.25AU, medium 0.401-0.75AU and low 0.201-0.4AU. SA was defined as per ATS/ERS criteria. Result(s): PV IgG results were obtained from 127 patients with SA (84 mAb, 13 mOCS and 46 ICS) and 57 HC. After adjusting for age, significantly fewer people with SA compared to HC had a positive PV IgG result (81% vs 95% p=0.016). Lower median IgG levels were seen in patients on mOCS (0.40AU) compared to HC (1.24AU) (p=0.051). Patients on mAb had high or very high IgG levels (omalizumab n=25, 0.80AU;mepolizumab n=25, 1.07AU;benralizumab n=34, 1.11AU). Conclusion(s): Overall, a higher proportion of patients with SA had a negative PV IgG level after receiving 2 doses of a C-19 vaccine. This was mainly seen in patients on mOCS while mAb use was associated with high levels of humoral antibody response. These results reinforce the need for booster vaccines in SA, especially in those on mOCS.

Global talent management by multinational enterprises post-COVID-19: The role of enterprise social networking and senior leadership

Multinational enterprises' (MNEs') workforce is made up of people from diverse backgrounds and different locations around the globe. The cross-border transfer of knowledge, skills, and best practices among MNE employees is important to maintain global standards and competitiveness. In the post-COVID-19 period, there is a greater need to exchange knowledge in the changing business environment. The purpose of this study is to examine the issues related to MNEs' global talent management, post-COVID-19. The study investigates the use of enterprise social networking applications for better knowledge exchange and tries to understand the moderating role of senior leadership team support in facilitating the usage of enterprise social networks for cross-border collaboration and talent management. After reviewing the literature and relevant theories, we developed a conceptual model, which is then validated using the SEM technique with 347 respondents from 12 MNEs. The study reveals the importance of using enterprise social networks for cross-border knowledge exchange in the post-COVID-19 period. © 2021 Wiley Periodicals LLC.

Digital workplace and organization performance: Moderating role of digital leadership capability

Since the onset of the COVID-19 pandemic, many organizations have permitted their employees to work from anywhere, giving rise to the phenomenon of the digital workplace, which enables employees to do their work by connecting, communicating, and collaborating with other employees. Organizations' dynamic capabilities play a major role in enabling this transformation of the workplace. As the situation is so recent, there is considerable interest amongst researchers, practitioners, academicians, and policymakers to understand the role of organizations' dynamic capability in digital transformation of the workplace, as well as the role of digital leadership in improving organization performance and enabling the digital transformation process to happen. Therefore, this study investigates the influence of digital workplace on organization performance and the moderating role of digital leadership capability in digitally transforming the workplace. We developed a research model from our review of the literature review and dynamic capability view (DCV) theory, and then we validated it using the PLS-SEM technique on a sample of 335 respondents from different types of organizations that have embarked on the digital transformation journey. The study finds that the dynamic capabilities of organizations have a significant and positive influence on the digital transformation of the workplace, which in turn improves the employees' work-life balance resulting better employee performance and superior organization performance. The study also highlights the significant role that digital leadership plays in the digital transformation of the workplace. © 2023 The Authors

Digital transformation using industry 4.0 technology by food and beverage companies in post COVID-19 period: from DCV and IDT perspective

PurposeThis study aims to understand the influence of digital transformation, using Industry 4.0 technology, on food and beverage companies in the post-COVID-19 period.Design/methodology/approachTo achieve the aim of this study, the authors have used innovation diffusion theory (IDT), dynamic capability view (DCV) theory and relevant literature, to develop a conceptual model. For the data, we surveyed 14, different sized food and beverage companies in India and the authors took inputs from 312 respondents at those companies to validate the conceptual model using the PLS-SEM approach.FindingsThe results from this study suggest that there is a considerable appetite for food and beverage companies to use Industry 4.0 technologies, as a part of their digital transformation journey in the post-COVID-19 scenario.Practical implicationsFood and beverage companies are going through a digital transformation process, which has been accelerated after the COVID-19 pandemic. Managers and leaders of the food and beverage companies need to support activities to adopt Industry 4.0 technologies. Moreover, the leaders should sponsor various readiness and training programs so that their employees successfully adopt these modern technologies.Originality/valueThis is a primary study on food and beverage companies that are using Industry 4.0 technologies or are in the process of digital transformation. The usage of both IDT and DCV to develop the unique conceptual model is an important contribution to the body of knowledge. Moreover, the proposed model has a high explanatory power, which makes the model effective.

Humoral immune responses to COVID-19 vaccines are reduced in patients with severe asthma

BackgroundPatients with severe asthma (SA) may be at higher risk of severe COVID-19 (C-19) illness. C-19 vaccines aim to reduce number and severity of infections. Patients with SA are often treated with maintenance oral corticosteroids (mOCS) and/or biologics- it is unknown if vaccines will generate the same protective responses in patients with SA on such therapies.AimsTo compare magnitude and range of post-vaccination (PV) antibody responses (IgG) in patients with SA on biologics, mOCS or high-dose inhaled corticosteroids (ICS) with healthy controls (HC) without asthma.To review temporal trends in PV IgG in patients with SAMethodsThe Virtus finger-prick quantitative C-19 antibody test was used to detect IgG levels 16–24 weeks post second-dose of the C-19 vaccine (123 AstraZeneca, 56 Pfizer, 5 Moderna). PV IgG levels were also measured in a subset of patients 6 weeks PV. IgG>0.2 AU was considered positive with range: very high >1.25 AU, high 0.751–1.25 AU, medium 0.401–0.75 AU and low 0.201–0.4 AU. SA was defined as per ATS/ERS criteria.ResultsPV IgG results were obtained from 127 patients with SA (84 on biologics, 13 mOCS and 46 ICS) and 57 HC. After adjusting for age, significantly fewer people with SA compared to HC had a positive PV IgG result (81% vs 95% p=0.016). Compared to HC (1.24 AU), lower median IgG levels were seen in patients on high dose ICS (1.02 AU, p=0.033) and mOCS (0.40 AU, p=0.017).Patients on biologics had high or very high IgG levels (omalizumab n=25, 0.80 AU;mepolizumab n=25, 1.07 AU;benralizumab n=34, 1.11 AU).Paired temporal measurements in 37 SA patients showed regression coefficient -0.005 (95%CI -0.006,-0.003) and can be interpreted as IgG decreases, on average, by 0.15 AU per month.ConclusionOverall, a higher proportion of patients with SA had a negative PV IgG level after receiving 2 doses of a C-19 vaccine. This was mainly seen in patients on mOCS while biologic use was not associated with reduced humoral antibody response. These results reinforce the need for booster vaccines in SA, especially in those on mOCS.

WE-Net: An Ensemble Deep Learning Model for Covid-19 Detection in Chest X-ray Images Using Segmentation and Classification

Amidst the increasing surge of Covid-19 infections worldwide, chest X-ray (CXR) imaging data have been found incredibly helpful for the fast screening of COVID-19 patients. This has been particularly helpful in resolving the overcapacity situation in the urgent care center and emergency department. An accurate Covid-19 detection algorithm can further aid this effort to reduce the disease burden. As part of this study, we put forward WE-Net, an ensemble deep learning (DL) framework for detecting pulmonary manifestations of COVID-19 from CXRs. We incorporated lung segmentation using U-Net to identify the thoracic Region of Interest (RoI), which was further utilized to train DL models to learn from relevant features. ImageNet based pre-trained DL models were fine-tuned, trained, and evaluated on the publicly available CXR collections. Ensemble methods like stacked generalization, voting, averaging, and the weighted average were used to combine predictions from best-performing models. The purpose of incorporating ensemble techniques is to overcome some of the challenges, such as generalization errors encountered due to noise and training on a small number of data sets. Experimental evaluations concluded on significant improvement in performance using the deep fusion neural network, i.e., the WE-Net model, which led to 99.02% accuracy and 0.989 area under the curve (AUC) in detecting COVID-19 from CXRs. The combined use of image segmentation, pre-trained DL models, and ensemble learning (EL) boosted the prediction results. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Driving Impact in Claims Denial Management Using Artificial Intelligence

A healthcare provider’s ability to quickly and efficiently process claims and quantify denial rates is critical to ensure smooth revenue cycle management and medical reimbursement. But the hospitals and medical practitioners are receiving more claim denials from payers, with the average rate of denial steadily increasing year over year. The recent COVID-19 pandemic has further accelerated the denial rate. An accurate denial detection algorithm can help to reduce the burden on healthcare providers. In this study, we propose a boosting-based machine learning framework to predict the likelihood of claims being denied along with the reason code at a line level. Prediction at a line level provides a finer-grained explanation to the administrative staff by pointing out the specific line for corrections. The list of important features provides an interpretable solution to the healthcare providers which enables them to create the right edits and correct the claim before going out to the payer. This in turn helps the healthcare provider dramatically improve both net patient revenue and cash flow. They can also put a check on their costs, as fewer denials mean less rework, resources, and time devoted to appealing and recovering denied claims. The denial model showed good performance with Area Under the Curve (AUC) of 0.80 and 0.82 for professional and institutional claims respectively. According to our estimates, the model has the potential to save 15%–50% of the denial cost for a healthcare provider. This in turn would have a tremendous impact on the healthcare costs as well as help make the healthcare process smoother. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Assessing the AI-CRM technology capability for sustaining family businesses in times of crisis: the moderating role of strategic intent

Purpose This study assesses the capability of artificial intelligence integrated customer relationship management (AI-CRM) technology for sustaining family businesses in times of crisis, such as the COVID-19 pandemic. The study also investigates the moderating role of strategic intent in sustaining family businesses in times of crisis. Design/methodology/approach The authors used dynamic capability view theory and related literature on family business and technology adoption to develop a conceptual model. This model has been validated using the structural equation modeling technique considering 332 usable responses from people of India involved in family businesses and technology adoption. The study also uses multigroup analysis to examine the moderating role of strategic intent. Findings The study finds that adoption of AI-CRM technology significantly and positively impacts dynamic capabilities of the family businesses, such as sensing, seizing and transforming capabilities, which in turn positively and significantly influences their sustainability during crises. The study also highlights the significant moderating impact of strategic intent for sustaining family business firms in uncertain times. Practical implications This study has highlighted the importance for family businesses to adopt AI-CRM technology and its influence on their dynamic capabilities. The study also provides important inputs to the management of family businesses regarding adoption of new technologies and their significance during crises. The study also documents that strategic intent could help family businesses to survive during such times. The study is conducted in India and thus cannot be generalized. Originality/value This study table is unique in that it investigates the influence of AI-CRM technology and the moderating role of strategic intent on family business sustainability in times of crisis. Moreover, the proposed theoretical model is a unique model with explanative power of 71%.

Corporate social responsibility in post COVID-19 period: critical modeling and analysis using DEMATEL method

Purpose: The purpose of this study is to identify the critical success factors (CSFs) of corporate social responsibility (CSR) in the post-COVID-19 period and to identify the cause–effect relationships amongst those CSFs. Design/methodology/approach: The success factors impacting CSR activities are identified based on inputs from 14 experts in the CSR domain. Thereafter, authors use a statistical approach to identify CSFs with inputs from useable respondents. Finally, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was applied to understand the causal relationship between different CSFs. Findings: Using the DEMATEL method, the authors developed an analytical model showing cause–effect aspects of the CSFs and identified seven factors which firms need to emphasize more to execute better CSR activities in the post-COVID-19 period. Research limitations/implications: The authors asked 14 experts for their inputs, but more experts could have made identifying success factors more comprehensive. In this study, the DEMATEL method found seven CSFs that improve CSR activities in the post-COVID-19 period. Another identification process could have enriched the study. The findings of this study cannot be generalized since this study is based on the inputs of employees from India only. Practical implications: This proposed analytical model is effective in determining the complex interactions among all impacting CSFs. Firms' CSR managers and policy makers can use the proposed model, especially in the post-COVID-19 period. Originality/value: The proposed model provides a precise and most accurate analysis for CSFs impacting CSR activities in the post-COVID-19 period. It also provides a unique opportunity for the competent authorities at firms to understand the interaction of different impacting CSFs and takes necessary actions. No other exhaustive analytical model is available in this context. © 2022, Emerald Publishing Limited.