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Many parts of the world are experiencing extreme weather events, energy poverty, food insecurity, and lack of access to basic healthcare. Moreover, concerns over socioeconomic, gender, and racial inequalities are growing. These socially relevant issues are ripe for analysis and improvement using an operations management lens. In this paper, we review some of the relevant research advancements made in the last decade, and identify future research directions on these important topics. In particular, we focus on papers related to sustainable planet (renewable energy, environmentally and socially responsible operations, regulation‐driven operations), agriculture, and public health. For future research directions, we discuss the role of innovative business models and disruptive technologies, such as artificial intelligence (AI) and blockchain, in addressing these pressing issues. [ABSTRACT FROM AUTHOR]

Climate change as a global challenge requires collective responses from stakeholders in society. As the main source of energy consumption generating greenhouse gases (e.g., CO2), firms increasingly share their problems and experiences regarding energy saving in interfirm knowledge communities. By distinguishing knowledge sharing from free‐riding, we investigate how firms that participate in an interfirm knowledge community for energy saving improve their energy efficiency. We use a unique panel dataset collected between 2001 and 2011 from the Energy Saving through Partnership program in South Korea. Our findings show that, within the community for energy saving, firms that share their knowledge through presenting their best practices improve energy efficiency to a greater extent (approximately 11.8–14.8%) than free‐riders. Our results suggest that the improvement in knowledge‐sharing firms' energy efficiency is attributed to relevant and tailored feedback gained from other participants. Further, we find that the understanding and activeness of other participants, which determine the quality and quantity of feedback respectively, significantly affect knowledge‐sharing firms' energy efficiency. Overall, our analysis has implications for firms on how they can contribute to a collective response to climate change through their collaborative activities in an interfirm knowledge community. [ABSTRACT FROM AUTHOR]

Climate change is a major global risk and a key driver for greenhouse gas emissions reduction. Yet, firms' internal emissions reduction may create a leakage leading to higher emissions in the supply chain. The related literature suggests that the pollution‐haven hypothesis explains such emissions leakage. In contrast, we explore an alternative reason for supply chain leakage, which is related to optimization of supply chain activities and supply chain innovation. Based on panel data from Bloomberg Environmental, Social, and Governance and Bloomberg Supply Chain, we estimate our models at a dyadic (i.e., firm and supplier) level using two‐way cluster‐robust standard error, treating various sources of endogeneity. We find empirical evidence of a supply chain leakage effect—a higher level of a supplier's emissions is associated with a lower level of a firm's internal emissions. More importantly, the supplier's innovation can be a major reason behind the leakage; the supply chain leakage effect is stronger when a supplier is more innovative. Furthermore, the role of innovation is strengthened when a supplier invests in eco‐innovation and has technological capabilities similar to those of the focal firm. Our findings suggest that supply chain leakage may not be completely driven by the pollution‐haven effect, but instead is associated with supply chain optimization and innovation that may be beneficial in the long run. [ABSTRACT FROM AUTHOR]

A dramatically changing business landscape characterized by volatility and uncertainty (which in turn are driven by unpredictable alterations of conditions by such factors as geopolitical events, climate changes, disasters—natural and human causes, reduction in food, potable water, and critical materials supply along with environmental contamination), has created a situation whereby a rethink of Production and Operations Management (POM) strategies and practices is considered timely and appropriate. Against a backdrop of current POM strengths and weaknesses, and expected POM futures, a response path for POM adoption to deal with such uncertainties and risks is proposed and described in some detail. This involves the treatment of POM as a more interconnected and integrated system than has hitherto been the case. Such an interconnected approach is described as a POM symphony where all key players would be playing from the same script and the POM leader must serve as a coach‐coordinator, that is, the symphony's conductor. [ABSTRACT FROM AUTHOR]

The content of climate change disclosures of large, global companies evolved from 2007 to 2016. Within that window, the same set of firms started measuring and disclosing their supply chain carbon emissions. Does carbon footprinting influence the nature and content of a firm's disclosure on the climate change risks that are expected to affect its business? We explore this question using more than 10,925 climate change disclosures collected by the CDP (formerly the Carbon Disclosure Project) from 2,003 firms worldwide. We use singular value decomposition and text similarity scores to quantitatively examine the content of the CDP disclosures from 2007 to 2016. Using fixed effects and dynamic panel models, we find that measuring supply chain carbon emissions (Scope 3) explains a substantial shift in the content and nature of the disclosures. We find no evidence that measuring and disclosing direct emissions (Scope 1) are associated with substantial changes in the content of the disclosures. One explanation for this is that most of the climate change‐related risks are in the supply chain, not within the company boundaries of large, global firms. Our results show the importance of encouraging firms to voluntarily measure their supply chain carbon emissions if they are not yet aware of their contribution and exposure to climate change. Our work shows that firms' response to climate change is dynamic, and it may take a decade to detect these shifts. [ABSTRACT FROM AUTHOR]

US coal‐fired generating capacity has shed nearly 25% of its footprint between 2011 and 2018. Multiple factors—regulation, natural gas prices, renewable energy adoption, and environmental activism—have each been lauded by various stakeholders for this trend. To improve our understanding of this environmental technology transition, it is important to determine the extent to which each of these factors has accelerated coal unit retirements. We do so in this study through an accelerated failure time model that utilizes data on US coal‐fired generating units from 2008 through 2016. Our findings indicate that environmental regulation, reduced natural gas price volatility, increased utilization of renewable capacity, and the Sierra Club's Beyond Coal campaign have all accelerated coal unit retirements. We do not, however, find evidence that natural gas price levels or the penetration of renewable capacity have accelerated coal unit retirements. Among the significant drivers, we estimate that the Beyond Coal campaign has had the greatest effect per unit, reducing expected operating life by an average of 24.4 months. However, among these factors, federal regulation affected the greatest number of coal units, and thus had the greatest aggregate impact on coal retirements. In post hoc analysis, we estimate that 40% of the generation that had been provided by retired coal‐fired units spilled over to surviving coal‐fired units. However, we estimate the 60% that was displaced from the coal fleet resulted in a 103.6 to 178.2 million metric ton net reduction in CO2 emissions each year. [ABSTRACT FROM AUTHOR]

Extreme precipitation caused by global climate change is expected to have a severe impact on urbanized areas. While decision‐makers struggle with climate uncertainty, an effective infrastructure adaptation strategy attaches great importance to preventing disasters resulting from rainfall. We propose a decision‐making model to incorporate the probability of rainfall disasters and recommend investing time when evaluating projects related to climate adaptation. We use a hydrological statistical model and economic and technical factors to estimate the expected economic losses in several rainfall disaster scenarios, and the value of the adaptation infrastructures is calculated using a real options pricing approach. Then the decision‐making model is applied to a case study involving a campus rainfall disaster prevention facility at the Central University of Finance and Economics in Beijing, China. We established three submerged scenarios with different rainfall intensities, then we evaluated the premium of holding an option to defer and pointed out the optimal investing time in each scenario. This model is expected to provide guidance for the development of adaptation infrastructure for relatively small areas such as communities and universities. And we proved that using real options‐based approach could provide more managerial flexibility for investors. [ABSTRACT FROM AUTHOR]

Operations management methods have been applied profitably to a wide range of technology portfolio management problems, but have been slow to be adopted by governments and policy makers. We develop a framework that allows us to apply such techniques to a large and important public policy problem: energy technology R&D portfolio management under climate change. We apply a multi-model approach, implementing probabilistic data derived from expert elicitations into a novel stochastic programming version of a dynamic integrated assessment model. We note that while the unifying framework we present can be applied to a range of models and data sets, the specific results depend on the data and assumptions used and therefore may not be generalizable. Nevertheless, the results are suggestive, and we find that the optimal technology portfolio for the set of projects considered is fairly robust to different specifications of climate uncertainty, to different policy environments, and to assumptions about the opportunity cost of investing. We also conclude that policy makers would do better to over-invest in R&D rather than under-invest. Finally, we show that R&D can play different roles in different types of policy environments, sometimes leading primarily to cost reduction, other times leading to better environmental outcomes. [ABSTRACT FROM AUTHOR]