Search results

The purpose of this study is to determine the proportion of the population that will be susceptible to the COVID-19 pandemic, as well as the proportions of infections, recoveries and fatalities from the COVID-19 pandemic.

The design was a longitudinal survey of COVID-19 infections, recoveries and fatalities in Nigeria using the data on the daily updates of the Nigeria Centre for Disease Control for the period 1 May to 23 August 2020. Markov chain analysis was performed on the data.

The results showed that in the long run, 8.4% of the population will be susceptible to COVID-19 infections, 26.4% of them will be infected, 61.2% of the infected will recover and 4% will become fatal. Thus, if this pattern of infections and recoveries continue, the majority of the infected people in Nigeria will recover whilst a very small proportion of the infected people will die.

A dearth of the extant literature on the problem, especially from the management science perspective.

Results of the study will facilitate policymakers’ response to the curtailment of the pandemic in Nigeria.

Curtailing the pandemic through the results of this study will assist in easing the social consequences of the pandemic.

The proposed adjustment to the susceptibilities, infections and recoveries model through the introduction of a fourth state (fatality) to get the susceptibilities, infections, recoveries and fatalities model, signalling a point of departure from previous studies.

Airline scheduling is an extremely complex process. Moreover, disruption in a single flight may damage the entire schedule tremendously. Using an efficient recovery scheduling strategy is vital for a commercial airline. The purpose of this paper is to present an integrated aircraft and crew recovery plans to reduce delay and prevent delay propagation on airline schedule with the minimum cost.

A mixed-integer linear programming model is proposed to formulate an integrated aircraft and crew recovery problem. The main contribution of the model is that recovery model is formulated based on individual flight legs instead of strings. This leads to a more accurate schedule and better solution. Also, some important issues such as crew swapping, reassignment of aircraft to other flights as well as ground and sit time requirements are considered in the model. Benders’ decomposition approach is used to solve the proposed model.

The model performance is also tested by a case including 227 flights, 64 crew, 56 aircraft and 40 different airports from American Airlines data for a 24-h horizon. The solution achieved the minimum cost value in 35 min. The results show that the model has a great performance to recover the entire schedule when disruption happens for random flights and propagation delay is successfully limited.

The authors confirm that this is an original paper and has not been published or under consideration in any other journal.

The purpose of this study is to compare lived recovery journeys in mental health with recovery models.

Unstructured interviews with prompts were conducted with two individuals.

Some recovery models correspond in part with the live experience of subjects. These narratives have personal emphasis that is incongruent with the highlighted models. In particular, the subjects have a place for therapeutic interventions, i.e. talking therapies and medication.

The live experience of the two people with mental health issues crosses boundaries of recovery models. Relevant models include those used in peer support; however, they too do not fit exactly with the detailed journeys.

A varied approach without preconceptions is appropriate to understand the components of these two recovery journeys.

The medical model approach to mental health is not discounted rather it is integral to these two recovery journeys.

This is qualitative research using stated models of mental health recovery. In addition to the principles of hope, meaning, connectedness, identity and empowerment, the two subjects include the essential part for medication and talking therapies in their recovery.

A recent global pandemic, known as coronavirus disease 2019 (COVID-19), affects the manufacturing supply chains most significantly. This effect becomes more challenging for the manufacturers of high-demand and most essential items, such as toilet paper and hand sanitizer. In a pandemic situation, the demand of the essential products increases expressively; on the other hand, the supply of the raw materials decreases considerably with a constraint of production capacity. These dual disruptions impact the production process suddenly, and the process can collapse without immediate and necessary actions. To minimize the impacts of these dual disruptions, we aim to develop a recovery model for making a decision on the revised production plan.

In this paper, the authors use a mathematical modeling approach to develop a production recovery model for a high-demand and essential item during the COVID-19. The authors also analyze the properties of the recovery plan, and optimize the recovery plan to maximize the profit in the recovery window.

The authors analyze the results using a numerical example. The result shows that the developed recovery model is capable of revising the production plan in the situations of both demand and supply disruptions, and improves the profit for the manufacturers. The authors also discuss the managerial implications, including the roles of digital technologies in the recovery process.

This model, which is a novel contribution to the literature, will help decision-makers of high-demand and essential items to make an accurate and prompt decision in designing the revised production plan to recover during a pandemic, like COVID-19.

Some essential issues about modeling of reverse logistics (RL) systems and product recovery networks include consideration of the qualities of the returned products, taking into account uncertainty and integrating the forward and reverse flows. The purpose of this paper is to develop the integrated RL model, which focuses on the control of inventory and production planning problems in a case of uncertainty in demand, quantities and qualities of returns.

The model involves a forward production route, three alternative recovery routes and a disposal route. Various levels of qualities are considered for returned products. A fuzzy mixed integer programming model (FMIP) is developed to provide a solution for the problems of production planning and inventory control. After maximizing the satisfaction degree, different solutions can have the same maximum. Moreover, policies that use all recovery routes and reduce the overall uncertainty have no chance to be chosen. To tackle these problems, a two-phase approach method is applied.

According to the results of the numerical example, using different and appropriate recovery options based on the quality of returns can significantly decrease the recovery costs. Similarly, it is shown that the two-phase approach can be an effective and efficient method to reach a satisfactory solution for such problems.

In this study, after maximizing the FMIP model, a two-phase approach ‒ as a novel optimization technique in this research ‒ is employed to achieve a desirable solution.

Due to the importance of understanding what circumstances make customer recovery programmes successful, this paper aims to study the effects of different cognitive evaluations (disconfirmation of expectations and perceived justice) and affective responses (positive and negative emotions) on satisfaction with complaint handling.

The sample used in this study consists of 679 subjects who, over the last six months, had experienced service failures and had afterwards complained. The data were collected via personal interviews using a structured survey.

The results of the study support the model and highlight the importance of the emotions experienced as a result of the complaint handling. Although these emotions have been underrepresented in the service recovery literature, our investigation shows that these emotions not only have an independent effect on customer satisfaction, after accounting for the effects of the cognitive evaluations of complaint handling, but also play a mediating role in the relationship between these cognitive variables and satisfaction.

This study examines only one service context; consequently, caution is needed when generalizing the results.

Given the findings in this paper, identifying customers' emotions can enable service organizations to know their perceptions of the recovery and, hence, adapt service recovery strategies adequately.

This study incorporates the disconfirmation of expectations paradigm and the dimension of informational justice into the existing models of cognitive and affective antecedents of satisfaction with complaint handling. Furthermore, this study is based on the analysis of real service failures and recovery strategies.

This paper aims to use equity theory to develop and test a model of the dynamics of service recovery in the homesharing context.

Using a sample of those who have experienced a service failure with a homesharing company and have voiced complaints to the company directly, the study adopted alternative model comparison procedures to test three competing models of service recovery and examined the effects of five moderating variables.

The results indicated that the model based on equity theory provides a theoretically and empirically superior explanation of the dynamics of service recovery in the homesharing context than the alternative explanation based on the tenets of justice theory. The two key inputs into the service recovery interaction – consumer complaining and recovery effort and trust in brand – have significant direct effects on post-failure loyalty outcomes, and also significant indirect effects via the mediating mechanism of perceived justice. All five moderators have significant effects for at least one of the post-failure loyalty outcomes.

The findings emphasize the company’s role in service recovery in the homesharing context. Managers of homesharing platforms need to establish customer service infrastructure that minimizes the amount of time-related, procedural and cognitive effort that customers need to expend in the recovery process, and effect communication that enhances trust in the homesharing brand. Future research is needed on the dynamics of service recovery in alternative hotel-homesharing business models, and on the role of value co-creation in the homesharing context.

This study is the first to create a holistic theory-based model of the dynamics of service recovery in the homesharing context, using the novel construct of customer complaining and recovery effort. Also, and contrary to typical conceptualization, it demonstrates the role of trust in brand as an antecedent input into the recovery interaction that can generate loyalty outcomes.

The purpose of this paper is to review the 16 published non-student Recovery Heroes and Remarkable Lives accounts published in Mental Health and Social Inclusion, using the connection, hope, identity, meaning and empowerment (CHIME) framework.

All 16 accounts were rated independently by four researchers and evaluated in terms of whether each account met the five criteria for the CHIME model.

All accounts met the criteria for the CHIME model, with the exception of one, which still met four of the five criteria. Evidence was presented which suggests that the model can be extended to creativity, connectedness, hope, identity, meaning and empowerment (C-CHIME), to incorporate creativity.

While a certain level of subjectivity is required in deciding how each account meets the CHIME criteria, there were high levels of inter-rater reliability within the research team. Creativity had a central place in all the accounts.

The revised C-CHIME model can be used by practitioners to examine accounts of recovery in a more focussed manner and may also help in devising recovery action plans.

The recovery model privileges both professional and lived experience perspectives on recovery. The current review highlights how much we can benefit from the wisdom contained in first person accounts.

This review adds to the existing literature and highlights the importance of creativity for mental health recovery.

This paper proposes investigating a model of service recovery performance in a public health‐care setting.

Frontline hospital staff (administrative and nursing staff) representing a range of out‐patient departments/clinics in a New Zealand inner‐city public hospital completed a self‐administered questionnaire on organizational variables affecting their service recovery efforts, job satisfaction and intention to resign. Data obtained from the hospital were analyzed using the SEM‐based partial least squares (PLS) methodology.

The results show significant relationships between perceived managerial attitudes, work environment perceptions, service recovery performance and outcomes variables.

Limitations of the study are noted including the generalizability of the findings within a public health‐care environment. Suggestions for future research include an examination of other variables potentially important in service recovery efforts. A patient perspective would also be valuable.

The research advances understanding of frontline service recovery performance in a health‐care setting and the findings indicate that health‐care managers can take actions on a number of fronts to assist progress toward the achievement of frontline service recovery excellence.

Very little attention has been given to understanding the antecedents and outcomes of service recovery performance in the health‐care literature. By expanding earlier research in private sector industries, the study investigates a model of service recovery performance in a public health‐care setting.

This paper aims to develop a process model of business-to-business (B2B) relationship recovery after a transgression has placed the future of the relationship in doubt. The research questions ask, How are relationships recovered? and How does the relationship strength pre-transgression influence the recovery process?

The process model is empirically grounded with first-hand narratives of owner managers (OMs) and key personnel of Irish small and medium-sized enterprises (SMEs). Using the critical incident technique, 25 owner and manager interviews in 23 SMEs resulted in 48 recovery narratives.

The findings identify four types of outcomes flowing from two potential recovery process paths. The strength of the relationship pre-transgression and the desire to maintain the relationship influence the parties’ actions during the recovery process and the status of the relationship subsequently.

The authors acknowledge that each narrative in the data are the informants’ construction of the phenomenon. The B2B relationship recovery process model offers OMs and SMEs a blueprint of what to expect, and how they might reach for recovery instead of the relationship ending.

Prior studies either treat recovery as a minor part of an ending process or focus on a single sub-process, leaving the overall process under-researched. This study contributes to the B2B relationship dynamics discussion with a processual view of the overall recovery process, including recovery sub-processes, paths and temporal outcomes in different types of relationships and takes into account the pre-transgression relationship.