Modeling Uncertainties in Workforce Disruptions from Influenza Pandemics Using Dynamic Input‐Output Analysis

Influenza pandemic is a serious disaster that can pose significant disruptions to the workforce and associated economic sectors. This article examines the impact of influenza pandemic on workforce availability within an interdependent set of economic sectors. We introduce a simulation model based on the dynamic input‐output model to capture the propagation of pandemic consequences through the National Capital Region (NCR). The analysis conducted in this article is based on the 2009 H1N1 pandemic data. Two metrics were used to assess the impacts of the influenza pandemic on the economic sectors: (i) inoperability, which measures the percentage gap between the as‐planned output and the actual output of a sector, and (ii) economic loss, which quantifies the associated monetary value of the degraded output. The inoperability and economic loss metrics generate two different rankings of the critical economic sectors. Results show that most of the critical sectors in terms of inoperability are sectors that are related to hospitals and health‐care providers. On the other hand, most of the sectors that are critically ranked in terms of economic loss are sectors with significant total production outputs in the NCR such as federal government agencies. Therefore, policy recommendations relating to potential mitigation and recovery strategies should take into account the balance between the inoperability and economic loss metrics.     

An integrated micro- and macrolevel discussion of global green issues: “It isn't easy being green”

Two key issues arising from globalization of world markets are the impact of business activities on the environment and threats to sustainable development. These issues are usually referred to as “green” issues. This paper presents a detailed discussion of global green issues in the context of a number of environments that include the socioeconomic, political, technological, and competitive arenas. The discussion is based on an attempt to integrate two conceptual models by Maslow (Maslow, A., 1954. Motivation and Personality. Harper & Row, New York) and Cateora (Cateora, P.R., 1983. International Marketing, 4th. ed. Irwin, Chicago, IL). The goal is to bring together both a microlevel perspective of the individual consumer and a macrolevel perspective of business through analysis in multiple environments that are affected by green issues. This integration is viewed conceptually as a recursive system of mutually reinforcing causes and effects at the micro- and macrolevels.The leitmotiv throughout the paper is that “it isn't easy being green,” either for consumers, activists, corporate leaders and managers, or public policymakers. Practical examples are presented to support and illustrate the discussion. The main finding is that a new approach is needed to business in general through a new dominant social paradigm (DSP) and to international business in particular in order to achieve both sustainable development and sustainable consumption. In conclusion, the importance of individual responsibility and action by consumers and managers alike is underlined.     

Benefits of adopting lean production on green performance of SMEs: a case study

Abstract

Small- and medium-sized enterprises (SMEs) are widely recommended to strive, not only for their performance in operational side, but they need to integrate the environmental dimension. To do that, the literature widely indicates a positive impact of lean practices on green performance. However, very few studies have been carried out in SMEs context. In this view, this paper aims at providing through a practical case study of lean implementation in a real-life small manufacturing company, the information to confirm this synergy between lean and green performance. To achieve this aim, a proposed framework of lean and green integration has been implemented in a SME producing different types of pumps. The results achieved shows that there is a strong correlation between operational metrics improvement and green metrics improvement. Moreover, the benefits of lean practices such as 5S, Kanban, SMED, AM, cellular manufacturing and quality control on green performance are widely demonstrated. Future work could study other processes and explore other case-specific supporting tools and techniques.     

Risk‐Based Input‐Output Analysis of Influenza Epidemic Consequences on Interdependent Workforce Sectors

Outbreaks of contagious diseases underscore the ever‐looming threat of new epidemics. Compared to other disasters that inflict physical damage to infrastructure systems, epidemics can have more devastating and prolonged impacts on the population. This article investigates the interdependent economic and productivity risks resulting from epidemic‐induced workforce absenteeism. In particular, we develop a dynamic input‐output model capable of generating sector‐disaggregated economic losses based on different magnitudes of workforce disruptions. An ex post analysis of the 2009 H1N1 pandemic in the national capital region (NCR) reveals the distribution of consequences across different economic sectors. Consequences are categorized into two metrics: (i) economic loss, which measures the magnitude of monetary losses incurred in each sector, and (ii) inoperability, which measures the normalized monetary losses incurred in each sector relative to the total economic output of that sector. For a simulated mild pandemic scenario in NCR, two distinct rankings are generated using the economic loss and inoperability metrics. Results indicate that the majority of the critical sectors ranked according to the economic loss metric comprise of sectors that contribute the most to the NCR's gross domestic product (e.g., federal government enterprises). In contrast, the majority of the critical sectors generated by the inoperability metric include sectors that are involved with epidemic management (e.g., hospitals). Hence, prioritizing sectors for recovery necessitates consideration of the balance between economic loss, inoperability, and other objectives. Although applied specifically to the NCR, the proposed methodology can be customized for other regions.     

Factors preventing the social reintegration of homeless persons: A comparison between residents of long-stay hostels and individuals living on the street

Homelessness is a major social issue in all Western countries. In France, many homeless persons do not have access to the accommodation and help with social reintegration provided in long-stay hostels, and remain on the streets or in other forms of emergency shelter. The objective of the present study is to identify the variables preventing access to these hostels and, more generally, to a process of social reintegration. We compared a group of 10 individuals housed in long-stay hostels with a group of 16 who were still living in the streets. All participants were assessed on the Hospital Anxiety and Depression Scale and underwent a semi-structured interview. Results showed that individuals who had not been admitted to a hostel were characterized by high levels of depression and anxiety, the attribution of responsibility to external factors, a vagrant lifestyle, a lack of social support, a negative approach to reintegration, and an inability to look to the future. This study highlights various factors explaining the reintegration difficulties encountered by a proportion of the homeless population. It suggests new ways of improving support for the homeless.     

Solving constrained optimization problems by solution-based decomposition search

Solving constrained optimization problems (COPs) is a challenging task. In this paper we present a new strategy for solving COPs called solve and decompose (or \( S \& D\) for short). The proposed strategy is a systematic iterative depth-first strategy that is based on problem decomposition. \( S \& D\) uses a feasible solution of the COP, found by any exact method, to further decompose the original problem into a bounded number of subproblems which are considerably smaller in size. It also uses the value of the feasible solution as a bound that we add to the created subproblems in order to strengthen the cost-based filtering. Furthermore, the feasible solution is exploited in order to create subproblems that have more promise in finding better solutions which are explored in a depth-first manner. The whole process is repeated until we reach a specified depth where we do not decompose the subproblems anymore but we solve them to optimality using any exact method like Branch and Bound. Our initial results on two benchmark problems show that \( S \& D\) may reach improvements of up to three orders of magnitude in terms of runtime when compared to Branch and Bound.