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The purpose of this paper is to examine recovery through lived experience. It is part of a series that explores candid accounts of addiction and recovery to identify important components in the recovery process.

The G-CHIME model comprises six elements important to addiction recovery (growth, connectedness, hope, identity, meaning in life and empowerment). It provides a standard against which to consider addiction recovery, having been used in this series, as well as in the design of interventions that improve well-being and strengthen recovery. In this paper, a first-hand account is presented, followed by a semi-structured e-interview with the author of the account. Narrative analysis is used to explore the account and interview through the G-CHIME model.

This paper shows that addiction recovery is a remarkable process that can be effectively explained using the G-CHIME model. The significance of each component in the model is apparent from the account and e-interview presented.

Each account of recovery in this series is unique and, as yet, untold.

Drawing on the stimulus–organism–response framework, this study examined the environmental stimuli driving tourists' internal, or organismic, states. In addition, the authors investigated the association of the identified organismic variables with the response variables during the COVID-19 pandemic. Specifically, the study examined how the associations between tourists' anticipation of recovery and the national government's smart governance, on one hand, and tourists' desire to travel domestically, their attitude toward domestic travel and their willingness to exhibit prosocial behaviors, on the other, further drive the satisfaction they derive from domestic travel.

The authors used an online questionnaire to collect self-report, single-wave data from individuals residing in India, an emerging market (N = 421).

The findings demonstrate (1) the association of anticipated recovery on the desire to travel and prosocial behavior; (2) the association of smart governance on attitude (although negative); (3) the association of desire, attitude and prosocial behavior on satisfaction; and (4) the lack of any moderation effect for perceived severity.

This study is the first empirical study to investigate the impact of tourists' perceptions and dispositions and the efficacy of the national government on tourists' desire to travel domestically and on their satisfaction with domestic travel. The findings can help emerging market multinationals and global brands engage better with domestic consumers in emerging markets within the context of the current pandemic. In addition, the findings can help to prepare these players to handle future disruptions caused by global health contingencies.

The COVID-19 pandemic severely impacted tourism, and the hotel and restaurant industry was the most affected sector, which faced issues related to business uncertainty and unemployment during the crisis. The analysis of recovery time and the influence factors is significant to support policymakers in developing an effective response and mitigating the risks associated with the tourism crisis. This study aims to investigate numerous factors affecting the recovery time of the hotel and restaurant sector after the COVID-19 crisis by using survival analysis.

This study uses the quarterly value added with the observation time from quarter 1 in 2020 to quarter 1 in 2023 to measure the recovery status. The recovery time refers to the number of quarters needed for the hotel and restaurant sector to get value added equal to or exceed the value added before the crisis. This study applies survival models, including lognormal regression, Weibull regression, and Cox regression, to investigate the effect of numerous factors on the hazard ratio of recovery time of hotels and restaurants after the COVID-19 crisis. This model accommodates all cases, including “recovered” and “not recovered yet” areas.

The empirical findings represented that the Cox regression model stratified by the area type fit the data well. The priority tourism areas had a longer recovery time than the non-priority areas, but they had a higher probability of recovery from a crisis of the same magnitude. The size of the regional gross domestic product, decentralization funds, multiplier effect, recovery time of transportation, and recovery time of the service sector had a significant impact on the probability of recovery.

This study contributes to the literature by examining the recovery time of the hotel and restaurant sector across Indonesian provinces after the COVID-19 crisis. Employing survival analysis, this study identifies the pivotal factors affecting the probability of recovery. Moreover, this study stands as a pioneer in investigating the multiplier effect of the regional tourism and its impact on the speed of recovery.

The purpose of this paper is to investigate sustainable green economy in sub-Saharan African (SSA) countries over the period 1990–2019 using a quantile regression approach, considering the nexus between urbanization, economic growth, renewable energy, trade and carbon dioxide (CO₂) emissions.

The study used a dynamic panel quantile regression to investigate the conditional distribution of CO₂ emissions along the turn-points of urbanization, economic growth, renewable energy, trade and the regressors via quadratic modeling specifications.

The main findings are established as follows. There is strong evidence of the Kuznets curve in the nexus between urbanization, economic growth, renewable energy, trade and CO₂ emissions, respectively. Second, urbanization thresholds that should not be exceeded for sustainability to reduce CO₂ emissions are 0.21%, and 2.70% for the 20th and 75th quantiles of the CO₂ emissions distribution. Third, growth thresholds of 3.64%, 3.84%, 4.01%, 4.36% and 5.87% across the quantiles of the CO₂ emissions distribution. Fourth, energy thresholds of 3.64%, 3.61%, 3.70%, 4.02% and 4.34% across the quantiles of the CO₂ emissions distribution. Fifth, trade thresholds of 3.37% and 4.47% for the 20th and median quantiles of the CO₂ emissions distribution, respectively.

The empirical shreds of evidence offer policy implications in such that building sustainable development and environment requires maintaining the critical mass, not beyond those insightful thresholds to achieving sustainable development and environmentally friendly SSA countries.

Sustainable cities and communities in an era of economic recovery path COVID-19 mitigate greenhouse gas. The policy relevance is of particular concern to the sustainable development goals.

The study is novel considering the extant literature by providing policymakers with avoidable thresholds for policy formulations and implementations in the nexus between urbanization, economic growth, renewable energy and trade openness.

As public health professionals strive to promote vaccines for inoculation efforts, fervent anti-vaccination movements are marshaling against it. This study is motived by a need to better understand the online discussion around vaccination. The authors identified the sentiments, emotions and topics of pro- and anti-vaxxers’ tweets, investigated their change since the pandemic started and further examined the associations between these content features and audiences’ engagement.

Utilizing a snowball sampling method, data were collected from the Twitter accounts of 100 pro-vaxxers (266,680 tweets) and 100 anti-vaxxers (248,425 tweets). The authors are adopting a zero-shot machine learning algorithm with a pre-trained transformer-based model for sentiment analysis and structural topic modeling to extract the topics. And the authors use the hurdle negative binomial model to test the relationships among sentiment/emotion, topics and engagement.

In general, pro-vaxxers used more positive tones and more emotions of joy in their tweets, while anti-vaxxers utilized more negative terms. The cues of sadness predominantly encourage retweets across the pro- and anti-vaccine corpus, while tweets amplifying the emotion of surprise are more attention-grabbing and getting more likes. Topic modeling of tweets yields the top 15 topics for pro- and anti-vaxxers separately. Among the pro-vaxxers’ tweets, the topics of “Child protection” and “COVID-19 situation” are positively predicting audiences’ engagement. For anti-vaxxers, the topics of “Supporting Trump,” “Injured children,” “COVID-19 situation,” “Media propaganda” and “Community building” are more appealing to audiences.

This study utilizes social media data and a state-of-art machine learning algorithm to generate insights into the development of emotionally appealing content and effective vaccine promotion strategies while combating coronavirus disease 2019 and moving toward a global recovery.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-03-2022-0186

COVID-19 has affected the economies adversely from all sides. The sudden halt in production has impacted both the supply and demand sides. It calls for analysis to quantify the impact of the reduction in economic activity on the economy-wide variables so that appropriate steps can be taken. This study aims to evaluate the sensitivity of various sectors of the Indian economy to this dual shock.

The eight-sector open economy general equilibrium Global Trade Analysis Project (GTAP) model has been simulated to evaluate the sector-specific effects of a fall in economic activity due to COVID-19. This model uses an economy-wide accounting framework to quantify the impact of a shock on the given equilibrium economy and report the post-simulation new equilibrium values.

The empirical results state that welfare for the Indian economy falls to the tune of 7.70% due to output shock. Because of demand–supply linkages, it also impacts the inter- and intra-industry flows, demand for factors of production and imports. There is a momentous fall in the demand for factor endowments from all sectors. Among those, the trade-hotel-transport and manufacturing sectors are in the first two positions from the top. The study recommends an immediate revival of the manufacturing and trade-hotel-transport sectors to get the Indian economy back on track.

The present study has modified the existing GTAP model accounting framework through unemployment and output closures to account for the impact of change in sectoral output due to COVID-19 on the level of employment and other macroeconomic variables.

The purpose of this paper is to investigate the mediating role of satisfaction (SAT) in relation to mobile banking service quality (MB-SQ) and continuance intention (CI) among Nepali mobile banking users.

The paper adopted a quantitative approach and cross-sectional survey research design. Data were collected with structured questionnaires from 326 mobile banking users. A partial least squares structural equation modeling (PLS-SEM) and artificial neuro network (ANN) approach were applied to examine hypotheses.

Results confirm a significant positive influence of MB-SQ on SAT and CI of mobile banking adoption. Moreover, MB-SQ partially mediates the relationship between SAT and CI of mobile banking adoption.

Based on the findings of this research, theoretically, this paper attempted to investigate the mediating role of MB-SQ in the CI of mobile banking, and managerially, mobile banking service providers could have insights on designing mobile banking service marketing strategy.

This paper is among the earliest studies to investigate the role of MB-SQ as a higher-order reflective-reflective construct on CI. Moreover, the endogeneity issue has been tested, and ANN has been applied to investigate the predictive relevance of SAT and MB-SQ on CI of mobile banking users. Furthermore, the authors have delved into the ongoing discourse surrounding Generation Y and Generation Z, exploring their implications on CI within the realm of mobile service quality. It provides a critical juncture for understanding continuance intention in the mobile service quality context.

The present study is performed to identify the propagation mechanism of the ripple effect as well as examine the simultaneous impact of risks on supply chain (SC) performance.

A theoretical framework with many hypotheses regarding the relationships between SC risk types and performance is established. The data are collected from a large-scale survey supported by a project of the Japanese government to promote sustainable socioeconomic development for the Association of Southeast Asian Nations (ASEAN) region, with the participation of 207 firms. Structural equation modeling (SEM) is used to test the hypotheses of the theoretical framework.

It is indicated that human-made risk causes operational risk, while natural risk causes both supply risk and operational risk. Furthermore, the impacts of human-made risk and natural risk on performance are amplified through operational risk.

This study is one of the first attempts that identifies the propagation mechanism of the ripple effect and examines the simultaneous impact of risks on performance in construction SCs.

Although many studies on risk management in construction SCs have been carried out, they mainly focus on risk identification or quantification of risk impact. It is observed that research on the ripple effect of disruptions has been very scarce.

The purpose of this study is to explore the relationship between government spending, public debt and the informal economy. In addition, this paper investigates the moderating role of public debt in government spending and the informal economy nexus.

By utilizing a data set spanning from 2000 to 2017 of 32 Asian economies, the study has employed the dynamic ordinary least squares (DOLS) and fully modified ordinary least squares (FMOLS). The study is also extended to consider the marginal effects of government spending on the informal economy at different degrees of public debt.

The results indicate that an increase in government spending and public debt leads to an expansion of the informal economy in the region. Interestingly, the positive effect of government spending on the informal economy will increase with a rise in public debt.

This study stresses the role of government spending and public debt on the informal economy in Asian nations. To the best of the authors' knowledge, this study pioneers to explore the moderating effect of public debt in the public spending-informal economy nexus.