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The COVID-19 pandemic has wreaked havoc across supply chain (SC) operations worldwide. Specifically, decisions on the recovery planning are subject to multi-dimensional uncertainty stemming from singular and correlated disruptions in demand, supply, and production capacities. This is a new and understudied research area. In this study, we examine, SC recovery for high-demand items (e.g., hand sanitizer and face masks). We first developed a stochastic mathematical model to optimise recovery for a three-stage SC exposed to the multi-dimensional impacts of COVID-19 pandemic. This allows to generalize a novel problem setting with simultaneous demand, supply, and capacity uncertainty in a multi-stage SC recovery context. We then developed a chance-constrained programming approach and present in this article a new and enhanced multi-operator differential evolution variant-based solution approach to solve our model. With the optimisation, we sought to understand the impact of different recovery strategies on SC profitability as well as identify optimal recovery plans. Through extensive numerical experiments, we demonstrated capability towards efficiently solving both small- and large-scale SC recovery problems. We tested, evaluated, and analyzed different recovery strategies, scenarios, and problem scales to validate our approach. Ultimately, the study provides a useful tool to optimise reactive adaptation strategies related to how and when SC recovery operations should be deployed during a pandemic. This study contributes to literature through development of a unique problem setting with multi-dimensional uncertainty impacts for SC recovery, as well as an efficient solution approach for solution of both small- and large-scale SC recovery problems. Relevant decision-makers can use the findings of this research to select the most efficient SC recovery plan under pandemic conditions and to determine the timing of its deployment.
Adoption of carbon regulation mechanisms facilitates an evolution toward green and sustainable supply chains followed by an increased complexity. Through the development and usage of a multi-choice goal programming model solved by an improved algorithm, this article investigates sustainability strategies for carbon regulations mechanisms. We first propose a sustainable logistics model that considers assorted vehicle types and gas emissions involved with product transportation. We then construct a bi-objective model that minimizes total cost as the first objective function and follows environmental considerations in the second one. With our novel robust-heuristic optimization approach, we seek to support the decision-makers in comparison and selection of carbon emission policies in supply chains in complex settings with assorted vehicle types, demand and economic uncertainty. We deploy our model in a case-study to evaluate and analyse two carbon reduction policies, i.e., carbon-tax and cap-and-trade policies. The results demonstrate that our robust-heuristic methodology can efficiently deal with demand and economic uncertainty, especially in large-scale problems. Our findings suggest that governmental incentives for a cap-and-trade policy would be more effective for supply chains in lowering pollution by investing in cleaner technologies and adopting greener practices.
Increased electricity consumption along with the transformations of the energy systems and interruptions in energy supply can lead to a blackout, i.e., the total loss of power in an area (or a set of areas) of a longer duration. This disruption can be fatal for production, logistics, and retail operations. Depending on the scope of the affected areas and the blackout duration, supply chains (SC) can be impacted to different extent. In this study, we perform a simulation analysis using anyLogistix digital SC twin to identify potential impacts of blackouts on SCs for scenarios of different severity. Distinctively, we triangulate the design and evaluation of experiments with consideration of SC performance, resilience, and viability. The results allow for some generalizations. First, we conceptualize blackout as a special case of SC risks which is distinctively characterized by a simultaneous shutdown of several SC processes, disruption propagations (i.e., the ripple effect), and a danger of viability losses for entire ecosystems. Second, we demonstrate how simulation-based methodology can be used to examine and predict the impacts of blackouts, mitigation and recovery strategies. The major observation from the simulation experiments is that the dynamics of the power loss propagation across different regions, the blackout duration, simultaneous unavailability of supply and logistics along with the unpredictable customer behavior might become major factors that determine the blackout impact and influence selection of an appropriate recovery strategy. The outcomes of this research can be used by decision-makers to predict the operative and long-term impacts of blackouts on the SCs and viability and develop mitigation and recovery strategies. The paper is concluded by summarizing the most important insights and outlining future research agenda toward SC viability, reconfigurable SC, multi-structural SC dynamics, intertwined supply networks, and cross-structural ripple effects.
AbstractBlack box machine learning models are currently being used for high-stakes decision making in various parts of society such as healthcare and criminal justice. While tree-based ensemble methods such as random forests typically outperform deep learning models on tabular data sets, their built-in variable importance algorithms are known to be strongly biased toward high-entropy features. It was recently shown that the increasingly popular SHAP (SHapley Additive exPlanations) values suffer from a similar bias. We propose debiased or "shrunk" SHAP scores based on sample splitting which additionally enable the detection of overfitting issues at the feature level.
We contribute to the recent debates on demand and growth regimes in modern finance-dominated capitalism linking them to the post-Keynesian research on macroeconomic policy regimes. We examine the demand and growth regimes, as well as the macroeconomic policy regimes for the big four Eurozone countries, France, Germany, Italy and Spain, for the periods 2001–2009 and 2010–2019. First, our approach supports the usefulness of the identification of demand and growth regimes according to growth contributions of the main demand components and financial balances of the macroeconomic sectors. This allows for an understanding of the demand sources of growth, or stagnation, if there is a lack of demand, of how these sources are financed and of potential financial instabilities and fragilities. Second, when it comes to the macroeconomic policy drivers of demand and growth regimes, as well as their respective changes, we show that the exclusive focus on fiscal policies, as in the previous literature, is too limited and that it is the macroeconomic policy regime which matters here, i.e. the combination of monetary, fiscal and wage policies, as well as the open economy conditions.
Alle reden von der digitalen Transformation, die so viele Bereiche des Lebens durchdringt, Ängste und Sorgen schafft, disruptive Risiken und Chancen bietet und schillernde neue Arbeitswelten verspricht. Die digitale Transformation hat eine kulturelle Dimension: Sie verändert Unternehmen, die Art wie wir miteinander kommunizieren, wie wir arbeiten, wie wir Leistungen erbringen und diese messen.
Dieser Sammelband zeichnet anhand von zahlreichen wissenschaftlichen Arbeiten, Fallstudien, Praxisberichten, Essays und einem Interview die facettenreiche Welt der digitalen Kulturtransformation der Berliner Wirtschaft durch interaktive Spielelemente nach. Gleichzeitig dokumentiert er die fruchtbare und kreative Arbeit des DiKuBiS-Forschungsprojektes unter Einbeziehung vieler Praxispartner.
Er richtet sich zuerst an interessierte Praktiker, die Einblicke in Theorien und die vielfältige Praxis der digitalen Kulturtransformation gewinnen wollen.
https://www.ludeo.de/ludeo-kultur/
Scholars have suggested that design thinking and effectuation theory may enrich each other. However, to date, we lack deeper theorizing and empirical evidence to further advance this valuable discourse for the benefit of innovation management. Our qualitative study draws on 41 in-depth interviews with Australian designer-founders, with the aim to provide a theoretical perspective on and empirical insights into the relationship between the behavioral practices of design thinking and the cognitive principles of effectuation. The contributions are twofold. First, our study explains how design thinking practices enable designer-founders to enact the cognitive principles of effectuation. Uncovering these “entrepreneurial ways of designing” provides an explanation for the effectiveness of design thinking for entrepreneurial innovation and new venture creation. Second, our study sheds light on the ways in which designer-founders interpret effectuation principles through the professional values and norms embodied in design thinking. These “designerly ways of entrepreneuring” resemble particular, normative interpretations of effectual action. By doing so, our study offers empirical substantiation and theoretical elaboration of the ways in which design thinking functions as an approach for entrepreneurial innovation and new venture creation. Through shedding light on the “entrepreneurial ways of designing” and “designerly ways of entrepreneuring” exhibited by designer-founders, our research reveals the reciprocal relationship between design thinking and effectuation theory.
This paper examines empirically the importance of equity
preferences for the formation of international environmen-
tal agreements (IEA) for transboundary pollution control.
Although it has been shown theoretically that the existence
of equity preferences among countries considering an IEA
increases the chances for formation and stability of a coali-
tion, empirical assessments of such preferences have been
limited to climate change mitigation and single-country
studies. We consider the case of marine plastic pollution, of
which a large share consists of food and beverage con-
tainers, representing a transboundary pollution control
problem of increasing policy concern, with properties that
lead to distinct considerations for equity and the sharing of
abatement costs. We employ a coordinated choice experi-
ment in the United Kingdom and United States to assess
preferences for abatement-cost allocations in a marine plas-
tics IEA. Pairs of cooperating countries and the relative
allocation of abatement costs are varied experimentally.
Results show systematic aversion to both advantageous and
disadvantageous inequality with respect to abatement costs
but also that the relative strength of advantageous and dis-
advantageous inequality aversion differs across countries.
Across both countries, there is evidence that left-leaning
voters generally favor more equal international sharing of
abatement costs. Differences of these results from the case
of greenhouse gas emission reduction, and implications for
current efforts to establish a legally binding global treaty on
marine plastic pollution, are discussed.
Exiting the COVID-19 pandemic: after-shock risks and avoidance of disruption tails in supply chains
(2021)
Entering the COVID-19 pandemic wreaked havoc on supply chains. Reacting to the pandemic and adaptation in the “new normal” have been challenging tasks. Exiting the pandemic can lead to some after-shock effects such as “disruption tails.” While the research community has undertaken considerable efforts to predict the pandemic’s impacts and examine supply chain adaptive behaviors during the pandemic, little is known about supply chain management in the course of pandemic elimination and post-disruption recovery. If capacity and inventory management are unaware of the after-shock risks, this can result in highly destabilized production–inventory dynamics and decreased performance in the post-disruption period causing product deficits in the markets and high inventory costs in the supply chains. In this paper, we use a discrete-event simulation model to investigate some exit strategies for a supply chain in the context of the COVID-19 pandemic. Our model can inform managers about the existence and risk of disruption tails in their supply chains and guide the selection of post-pandemic recovery strategies. Our results show that supply chains with postponed demand and shutdown capacity during the COVID-19 pandemic are particularly prone to disruption tails. We then developed and examined two strategies to avoid these disruption tails. First, we observed a conjunction of recovery and supply chain coordination which mitigates the impact of disruption tails by demand smoothing over time in the post-disruption period. Second, we found a gradual capacity ramp-up prior to expected peaks of postponed demand to be an effective strategy for disruption tail control.
Der zweite Band der Schriftenreihe des EMF-Instituts thematisiert die Konferenz „Familienunternehmen – „Wir reden
darüber!“ Im Mittelpunkt steht die Kommunikation im Familienunternehmen. Welche Sprache braucht ein Unternehmen? Welche
Regeln der Kommunikation gelten? Und sprechen Familienunternehmen
eine andere Sprache? Diese Schrift enthält – ganz im Sinne der Konferenz – keine rein wissenschaftlichen Abhandlungen, sondern einen bunten Mix aus neuen, praxisrelevanten wissenschaftlichen Fragestellungen und Erfahrungsberichten sowie Meinungen von Familienunternehmern.
Combinations of art and products are a classic and current topic. Examples like the collaboration of the Medici with artists in the Renaissance or the logo development of Chupa Chups by Salvador Dali are historical examples. The BMW art cars by Jeff Koons and Cao Fei or the art‐based special editions of Louis Vuitton bags are current best practices. All these cases expected a positive impact of art on the product or brand evaluation. This spillover effect was coined “art infusion effect” by Hagtvedt and Patrick. This, as well as further studies on the art infusion effect, are predominantly concerned with classical fine arts. However, despite an observable increase of urban arts‐brands collaborations, the effects of these have not been researched. Our study determines that graffiti and street art are perceived by consumers as art. To confirm the art infusion effect for urban art, a laboratory experiment was conducted. The presence of urban art has a favourable influence on the evaluation of products. These results replicate and extend the findings of Hagtvedt and Patrick. As drivers of the urban art infusion effect, we also identify two additional drivers: the fit between the art and the product and the “lifestyle perception”.
Shark incidents are rare and graphic events, and their
consequences can influence the behavior of beach users,
including bathers, to a great extent. These incidents can
be thought of as a fearsome risk that may lead decision
makers to overreact or respond with inaction. This paper
examines the reaction of recreational beach users, includ-
ing bathers, to changes in the risk of shark incidents. In
addition to valuing recreational visits to Durban Beach,
South Africa, we study the reaction of beach visitors to a
hypothetical scenario in which protective shark nets,
deployed in coastal waters to protect bathers, are to be
removed. To examine potential heterogeneity of the treat-
ment effect in a travel cost-contingent behavior model, we
develop a semiparametric multivariate Poisson lognormal
(MPLN) model to jointly analyze observed and stated visit
counts. Results show that removing protective shark nets
at Durban beach would decrease recreational visits by
more than 20%. Applying the semiparametric MPLN
model we further find that both the value of a recreational
visit and the predicted change in visitation rates vary as a
function of whether recreationists usually enter the water,
whether they have heard of previous shark incidents, and
their general risk attitude.
The coronavirus (COVID-19) outbreak shows that pandemics and epidemics can seriously wreak havoc on supply chains (SC) around the globe. Humanitarian logistics literature has extensively studied epidemic impacts; however, there exists a research gap in understand-ing of pandemic impacts in commercial SCs. To progress in this direction, we present a systematic analysis of the impacts of epidemic outbreaks on SCs guided by a structured lit-erature review that collated a unique set of publications. The literature review findings sug-gest that influenza was the most visible epidemic outbreak reported, and that optimization of resource allocation and distribution emerged as the most popular topic. The streamlining of the literature helps us to reveal several new research tensions and novel categorizations/classifications. Most centrally, we propose a framework for operations and supply chain management at the times of COVID-19 pandemic spanning six perspectives, i.e., adap-tation, digitalization, preparedness, recovery, ripple effect, and sustainability. Utilizing the outcomes of our analysis, we tease out a series of open research questions that would not be observed otherwise. Our study also emphasizes the need and offers directions to advance the literature on the impacts of the epidemic outbreaks on SCs framing a research agenda for scholars and practitioners working on this emerging research stream.