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Mustafee, Navonil; Harper, Alison & Viana, Joe
(2023)
Hybrid Models with Real-time Data: Characterising Real-time Simulation and Digital Twins
Vis sammendrag
Real-time Simulation (RtS) and Digital Twins (DT) are terms generally associated with hybrid models
that use real-time data to drive computational models. Additionally, in the case of DTs, real-time data
is often used to create virtual replicas of the physical system as it progresses through real-time. There
is an increasing volume of literature on RtS and DT; however, the field of OR/MS is yet to coalesce on
accepted definitions and conceptualisations. This has arguably led to the cascading usage of these terms.
The objective of the paper is threefold: (1) distinguish between RtS and DT, (2) present RtS-DT
conceptualisation in four dimensions, and (3) present methodological and technical insights on
developing RtS with limited data. We argue that the evolution of conventional simulation models to
fully-fledged hybrid DTs may necessitate a focus on a transitional stage; namely, RtS models primarily
driven using historical distributions with limited real-time data feeds.
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Hormozi, Mohammad Ali; Zaki Dizaji, Hassan, Bahrami, Hoshang, Sharifyazdi, Mehdi & Monjazi, Nasim
(2023)
Multi-objective optimization of allocating sustainable mechanization for spraying and harvesting systems in paddy fields
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Chen, Jeff Zeyun; Elemes, Anastasios, Hope, Ole-Kristian & Yoon, Aaron S.
(2023)
Audit-Firm Profitability: Determinants and Implications for Audit Outcomes
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Tamssaouet, Karim & Dauzère-Pérès, Stéphane
(2023)
A general efficient neighborhood structure framework for the job-shop and flexible job-shop scheduling problems
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Steen, Riana; Håheim-Saers, Nils & Aukland, Gina
(2023)
Military unmanned aerial vehicle operations through the lens of a high-reliability system: Challenges and opportunities
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Steen, Riana; Haug, Ole Jacob & Patriarca, Riccardo
(2023)
Business continuity and resilience management: A conceptual framework
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Mekonnen, Zeleke; Melaku, Tsegaye, Tucho, Gudina Terefe, Mecha, Mohammed, Årdal, Christine & Jahre, Marianne
(2023)
The knock-on effects of COVID-19 pandemic on the supply and availability of generic medicines in Ethiopia: mixed methods study
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Shen, Liji; Dauzère-Pérès, Stéphane & Maecker, Söhnke
(2023)
Energy cost efficient scheduling in flexible job-shop manufacturing systems
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Berterottière, Lucas; Dauzère-Pérès, Stéphane & Yugma, Claude
(2023)
Flexible job-shop scheduling with transportation resources
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A. Wood, David; Kuruppu, Gowindage Chamara Jayanath, Berg, Terje, Madsen, Dag Øivind, Lyngstadås, Hakim, van pelt, Victor, Johanson, Bjørn Daniel, Kulset, Ellen Hiorth Marthinsen, Heinzelmann, Rafael & Sundkvist, Charlotte Haugland
(2023)
The ChatGPT artificial intelligence chatbot: How well does it answer accounting assessment questions?
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ChatGPT, a language-learning model chatbot, has garnered considerable attention for its ability to respond to users’ questions. Using data from 14 countries and 186 institutions, we compare ChatGPT and student performance for 28,085 questions from accounting assessments and textbook test banks. As of January 2023, ChatGPT provides correct answers for 56.5 percent of questions and partially correct answers for an additional 9.4 percent of questions. When considering point values for questions, students significantly outperform ChatGPT with a 76.7 percent average on assessments compared to 47.5 percent for ChatGPT if no partial credit is awarded and 56.5 percent if partial credit is awarded. Still, ChatGPT performs better than the student average for 15.8 percent of assessments when we include partial credit. We provide evidence of how ChatGPT performs on different question types, accounting topics, class levels, open/closed assessments, and test bank questions. We also discuss implications for accounting education and research.
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Steen, Riana; Haakonsen, Geir & Steiro, Trygve Jakobsen
(2023)
Patterns of Learning: A Systemic Analysis of Emergency Response Operations in the North Sea through the Lens of Resilience Engineering
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Zuiderwijk, Dianka; Steen, Riana & Pedro, Ferreira
(2023)
Learning from Operational planning
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Wood, David & Lyngstadås, Hakim
(2023)
The ChatGPT Artificial Intelligence Chatbot: How Well Does It Answer Accounting Assessment Questions?
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Chen, Lu; Yang, Wenhui, Qiu, Kejun & Dauzère-Pérès, Stéphane
(2023)
A lexicographic optimization approach for a bi-objective parallel-machine scheduling problem minimizing total quality loss and total tardiness
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In wafer fabrication, production quality is a key performance index and is subject to machine condition deterioration. This paper studies a parallel-machine scheduling problem that can typically be found in the photolithography process. To solve the problem, a lexicographic optimization approach is proposed where the total quality loss is firstly minimized and the second objective is to minimize total tardiness. An optional maintenance activity is also considered to restore the machine condition to a certain level. Optimality properties are discussed, based on which an exact scheduling algorithm is developed. Experimental analyses derived from real data demonstrate the effectiveness of the proposed algorithm and support some managerial insights.
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Kasapidis, Gregory A.; Dauzère-Pérès, Stéphane, Paraskevopoulos, Dimitris C., Repoussis, Panagiotis P. & Tarantilis, Christos D.
(2023)
On the multiresource flexible job-shop scheduling problem with arbitrary precedence graphs
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Rodoplu, Melek; Dauzère-Pérès, Stéphane & Vialletelle, Philippe
(2023)
Integrated planning of maintenance operations and workload allocation
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Lyngstadås, Hakim & Berg, Terje
(2023)
The C-Suite of Supplier Collaboration: A Configurational Analysis of the How’s and Why’s.
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Steen, Riana; Shukla, Anurag & Solbakken, Even André
(2023)
On the cyber-emergency preparedness in a resilient organization
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Steen, Riana; Gregersen, Lars, Løvstad, Karl Andre & Haugen, Maud
(2023)
Applying Functional Resonance Analysis Method to strengthen resilience in the Norwegian customs infrastructure
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Flores-Gómez, Mario; Borodin, Valeria & Dauzère-Pérès, Stéphane
(2023)
Maximizing the service level on the makespan in the stochastic flexible job-shop scheduling problem
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Tamssaouet, Karim; Engebrethsen, Erna & Dauzère-Pérès, Stéphane
(2023)
Multi-item dynamic lot sizing with multiple transportation modes and item fragmentation
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Kvaal, Erlend; Löw, Edgar, Novotny-Farkas, Zoltán, Panaretou, Argyro, Renders, Annelies & Sampers, Peter
(2023)
Classification and Measurement under IFRS 9: A Commentary and Suggestions for Future Research
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Charles, Mehdi; Dauzère-Pérès, Stéphane, Kedad-Sidhoum, Safia & Mazhoud, Issam
(2022)
Motivations and analysis of the capacitated lot-sizing problem with setup times and minimum and maximum ending inventories
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This paper first analyzes the negative impact of the end-of-horizon effect when solving the capacitated multi-item lot-sizing problem with setup costs and times on a rolling horizon. Maximum ending inventories for items and a global minimum ending inventory are considered to define a new optimization problem whose optimal solutions are much less impacted by the end-of-horizon effect. Then, a generation scheme is proposed to create new instances with initial inventories and ending inventories. This scheme relies on the analysis of the cyclical production planning problem to derive relevant parameters. Computational experiments are carried out to compare the solutions obtained for original instances of the literature and for the new instances, and to analyze the relevance of the new instances on a rolling horizon.
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Walrave, Bob; Dolmans, Sharon, van Oorschot, Kim E., Nuijten, Arno L. P. , Keil, Mark & van Hellemond, Stefan
(2022)
Dysfunctional Agile-Stage-Gate Hybrid Development: Keeping Up Appearances
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Steen, Riana & Pollock, Kevin
(2022)
Effect of Stress on Safety-critical Behaviour: An Examination of combined Resilience Engineering and Naturalistic Decision-making Approaches
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Che, Limei; Myllymäki, Emma-Riikka & Svanstrøm, Tobias
(2022)
Auditors’ self-assessment of engagement quality and the role of stakeholder priority
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van Oorschot, Kim E.; Akkermans, Henk A. , Wassenhove, Luk N. van & Wang, Yan
(2022)
Organizing for Permanent Beta: Performance Measurement Before versus Performance Monitoring After Release of Digital Services
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Akartunali, Kerem & Dauzère-Pérès, Stéphane
(2022)
Dynamic Lot Sizing with Stochastic Demand Timing
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In this paper, a novel way of modeling uncertainty on demand in the single-item dynamic lot sizing problem is proposed and studied. The uncertainty is not related to the demand quantity, but rather to the demand timing, i.e., the demand fully occurs in a single period of a given time interval with a given probability and no partial delivery is allowed. The problem is first motivated and modeled. Our modeling naturally correlates uncertain demands in different periods contrary to most of the literature in lot sizing. Dynamic programs are then proposed for the general case of multiple demands with stochastic demand timing and for several special cases. We also show that the most general case where the backlog cost depends both on the time period and the stochastic demand is NP-hard.
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Perraudat, Antoine; Dauzère-Pérès, Stéphane & Vialletelle, Philippe
(2022)
Robust tactical qualification decisions in flexible manufacturing systems
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In some flexible manufacturing systems, such as semiconductor manufacturing systems, machines must be qualified, i.e. certified and eligible, to process a product. This paper investigates a tactical capacity planning problem that consists in minimizing the number of (product, machine) qualifications to ensure that the manufacturing system is robust against the uncertainty on the product mix. First, we propose a deterministic modeling of the problem, followed by a robust modeling based on the robust optimization paradigm when demand uncertainty is characterized by product cannibalization. Then, a mathematical model, also based on the robust optimization paradigm, to characterize the robustness of a set of qualifications is introduced. Finally, in the computational study on industrial data, we show that the price of uncertainty is small, often less than a few additional qualifications by machine whereas the robustness of the qualifications determined for the nominal product mix often lead to capacity constraint violations. We also show that a restricted number of new relevant qualifications out of all possible new qualifications is required to achieve the same robustness as the case where all new qualifications are performed. Considering demand uncertainty in qualification management is therefore critical since robustness is relatively cheap.
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Cahan, Steven F.; Che, Limei, Knechel, W. Robert & Svanstrøm, Tobias
(2022)
Do Audit Teams Affect Audit Production and Quality? Evidence from Audit Teams’ Industry Knowledge
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Hope, Ole-Kristian; Rao, Pingui, Xu, Yanping & Yue, Heng
(2022)
Information sharing between mutual funds and auditors
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Kisser, Michael & Rapushi, Loreta
(2022)
Equity issues, creditor control and market timing patterns: Evidence from leverage decreasing recapitalizations
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We contribute to the literature on “market timing” by exploring periods of simultaneous equity issues and debt retirements (a leverage decreasing recapitalization, LDR). Contrary to traditional equity issues, LDRs are predicted by measures of creditor control whereas capital investment has no such predictive power. Nevertheless, LDRs occur after stock price run- ups and in periods of high valuation which subsequently decrease. The valuation dynamics are robust and also obtain for subsamples of LDR firms violating financial covenants. A comparison to debt retirements financed by illiquid asset sales and an analysis of discretionary cost items further corroborates the interpretation that LDR firms successfully “time the market” to finance the debt retirement.
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van Oorschot, Kim; Van Wassenhove, Luk N., Jahre, Marianne, Selviaridis, Kostas & de Vries, Harwin
(2022)
Drug shortages: A systems view of the current state
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Dube, Nonhlanhla; Li, Qiujun, Selviaridis, Kostas & Jahre, Marianne
(2022)
One crisis, different paths to supply resilience: The case of ventilator procurement for the COVID-19 pandemic
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Lang, Wei; Lang, Hao, Hui, Eddie C.M., Chen, Tingting, Wu, Jiemin & Jahre, Marianne
(2022)
Measuring urban vibrancy of neighborhood performance using social media data in Oslo, Norway
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Hope, Ole-Kristian; Wang, Danye, Yue, Heng & Zhao, Jianyu
(2022)
Information Quality and Workplace Safety
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Perraudat, Antoine; Dauzère-Pérès, Stéphane & Vialletelle, Philippe
(2022)
Optimizing multiple qualifications of products on non-identical parallel machines
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Gartner, Daniel; Viana, Joe, Tabar, Bahman Rostami , Pförringer, Dominik & Edenharter, Günther
(2022)
Challenging the throwaway culture in hospitals: Scheduling the mix of reusable and Single-Use bronchoscopes
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Optimal material resource planning is crucial to run safe and cost-efficient hospital services. In this article, we investigate a real problem in hospitals, motivated by an environmental and economically inefficient use of disposable, single-use, endoscopes. We develop a mathematical model and create a decision support tool to determine when reusable, multi-use, bronchoscopes should be sent for inspection including information to what extent single-use bronchoscopes can cover the remaining demand. The results show that the proposed approach can contain operational costs which consist of costs for buying single-use devices, inspection costs and reprocessing costs, i.e., sterilization of reusable devices. Our tool can assist hospitals to predict when reusable bronchoscopes should undergo inspection and whether the current inventory of reusable devices is sufficient to cover the demand. Finally, we evaluate the impact of variation in demand on total costs.
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Khadri, Ines Julia & Viana, Joe
(2022)
Simulation of IT Data Integration to Optimize an Antibiotics Supply Chain with System Dynamics
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Supply chain (SC) optimization is essential for a firm to cope with everchanging market conditions and disruptions. New technologies have allowed for more advanced supply chain optimization. This paper uses system dynamics (SD) simulation to model the effects of data integration technologies on an antibiotic (AB) SC operation. The study aims to improve the AB SC to benefit all relevant stakeholders including the patient population. We evaluate how IT integration technologies can improve communication across the SC to mitigate or reduce the impact of the of disruptions on AB users. The presented model is under development and is subject to structural and parametric changes as discussions continue with stakeholders about the system structure and what data can be used and disclosed. Despite extensive SC optimization literature there has been a growing call of an evidence base to support decision making relating to national medicine policies.
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van Oorschot, Kim E.; Wassenhove, Luk N. van & Jahre, Marianne
(2022)
Collaboration–competition dilemma in flattening the COVID-19 curve
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Testing for COVID-19 is a key intervention that supports tracking and isolation to prevent further infections. However, diagnostic tests are a scarce and finite resource, so abundance in one country can quickly lead to shortages in others, creating a competitive landscape. Countries experience peaks in infections at different times, meaning that the need for diagnostic tests also peaks at different moments. This phase lag implies opportunities for a more collaborative approach, although countries might also worry about the risks of future shortages if they help others by reallocating their excess inventory of diagnostic tests. This article features a simulation model that connects three subsystems: COVID-19 transmission, the diagnostic test supply chain, and public policy interventions aimed at flattening the infection curve. This integrated system approach clarifies that, for public policies, there is a time to be risk-averse and a time for risk-taking, reflecting the different phases of the pandemic (contagion vs. recovery) and the dominant dynamic behavior that occurs in these phases (reinforcing vs. balancing). In the contagion phase, policymakers cannot afford to reject extra diagnostic tests and should take what they can get, in line with a competitive mindset. In the recovery phase, policymakers can afford to give away excess inventory to other countries in need (one-sided collaboration). When a country switches between taking and giving, in a form of two-sided collaboration, it can flatten the curve, not only for itself but also for others.
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Engebrethsen, Erna S. & Dauzère-Pérès, Stéphane
(2022)
Transportation strategies for dynamic lot sizing: single or multiple modes?
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Bø, Eirill; Hovi, Inger Beate & Pinchasik, Daniel Ruben
(2022)
COVID-19 disruptions and Norwegian food and pharmaceutical supply chains: Insights into supply chain risk management, resilience, and reliability
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The purpose of this study is to investigate how the COVID-19 crisis affected delivery security and firms’ preparedness and responses in Norway. Investigations focus on supply chains which were critical for maintaining the supply of essential goods when large parts of society closed down. This includes four firms belonging to food and pharmaceutical industries, representing different parts of the respective supply chains, and covering imports, exports, domestic distribution, and home-delivery services.
The originality of this article is that we employ theoretical models on supply chain risk management, resilience and reliability in conjunction, where these are usually used separately. Recognizing links, overlaps, and complementarity between the models, and using them step-by-step, we exploit synergies that enable more comprehensive assessments of strengths and weaknesses in firms’ supply chains, covering gaps, prioritizing between improvement areas, and collecting input towards detailed, actionable risk mitigation actions. Investigations build on semi-structured interviews, systematically covering the formative elements for each of the models. Using the models in conjunction, we compare the firms and identify differences, similarities, strengths, and weaknesses in the consequences of pandemic-related disruptions and how firms approached the challenges.
The main challenges for the firms were sudden demand changes early in the pandemic. While the firms had minor differences, their pre-pandemic contingency plans were generally not actionable or detailed enough, nor prepared for the pandemic's longevity. Therefore, more detailed and long-term guidelines are desirable, noting the importance and interrelationships of elements of supply chain risk management, resilience, and reliability. A common feature for all firms, and crucial for handling disruptions, is the importance of good and long-term relationships with upstream and downstream supply chain partners and the need for improving contingency plans and future resilience.
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Frennesson, Lina; Kembro, Joakim, de Vries, Harwin, Jahre, Marianne & Van Wassenhove, Luk
(2022)
“International humanitarian organizations’ perspectives on localization efforts”
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Lyngstadås, Hakim & Berg, Terje
(2022)
Harder, better, faster, stronger: digitalisation and employee well-being in the operations workforce
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Steen, Riana; Haakonsen, Geir & Patriarca, Riccardo
(2022)
'Samhandling': On the nuances of resilience through case study research in emergency response operations
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Standard emergency-management procedures offer guidance on how organizations can improve their handling of all types of emergencies. However, such a generalization undermines uncertainties and oversimplifies the complexity of real work practices during an emergency response operation (ERO). The handling of the COVID-19 pandemic highlights how uncertainty and escalating consequences reinforce the need for resilience in EROs. To illustrate the key elements of our suggested approach and its practical implications, we discuss the issues in light of a case study related to a COVID-19 outbreak on a floating oil rig in the North Sea. The analysis reveals several instances of creative problem solving, and individual and collective efforts beyond the scope of the standard procedures. It also underlines how the shortcomings of resource allocation and over-planning might lead to inflexibility, thus harming EROs' efficiency. Our analysis highlights that the key to resilient EROs lies in robust coordination, the ability to improvise, transparency, and trusting communication between the actors involved. Greater focus on network building—proactively maintained through regular training and exercise activities—strengthens resilience in emergency-management systems. All these traits link to the Norwegian term “samhandling,” a notion which is here proposed to summarize and connect these resilience capacities.
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Ahlqvist, Victoria; Årdal, Christine Oline, Dube, Nonhlanhla, Jahre, Marianne, Lee, Jin Soo, Melaku, Tsegaye, Moe, Andreas Farstad, Olivier, Max, Selviaridis, Kostas & Viana, Joe
(2022)
Supply chain risk management strategies in normal and abnormal times: policymakers' role in reducing generic medicine shortages
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This paper links supply chain risk management to medicine supply chains to explore the role of policymakers in employing supply chain risk management strategies (SCRMS) to reduce generic medicine shortages.
Using secondary data supplemented with primary data, we map and compare seven countries’ SCRMS for handling shortage risks in their paracetamol supply chains before and during the first two waves of the COVID-19 pandemic.
Consistent with recent research, the study finds that policymakers had implemented few SCRMS specifically for responding to disruptions caused by COVID-19. However, shortages were largely avoided since multiple strategies for coping with business-as-usual disruptions had been implemented prior to the pandemic. We did find that SCRMS implemented during COVID-19 were not always aligned with those implemented pre-pandemic. We also found that policymakers played both direct and indirect roles.
Combining longitudinal secondary data with interviews sheds light on how, regardless of the level of preparedness during normal times, SCRMS can be leveraged to avert shortages in abnormal times. However, the problem is highly complex, which warrants further research Supply chain professionals and policymakers in the healthcare sector can use the findings when developing preparedness and response plans.
The insights developed can help policymakers improve the availability of high-volume generic medicines in (ab)normal times.
We contribute to prior SCRM research in two ways. First, we operationalize SCRMS in the medicine supply chain context in (ab)normal times, thereby opening avenues for future research on SCRM in this context. Second, we develop insights on the role policymakers play and how they directly implement and indirectly influence the adoption of SCRMS. Based on our findings, we develop a framework that captures the diverse roles of policymakers in SCRM.
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van Oorschot, Kim; Nujen, Bella B., Solli-Sæther, Hans Arthur & Mwesiumo, Deodat Edward
(2022)
The complexity of post-mergers and acquisitions reorganization : integration and differentiation
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This article applies a mixed-method approach to explore the complexities of post-mergers and acquisitions (M&A) integration processes. Extant literature provides significant insights regarding the impact of task and human integration and their influence on post-integration processes. However, the literature often fails to differentiate between subelements of these two dimensions. This article investigates task and human integration in a cross-border M&A aimed at efficiency and innovativeness. We highlight the importance of a clear distinction between two subelements of task integration (product harmonization and structural integration) and show that different interorganizational contexts matter. Consequently, we propose a conceptual framework based on two contextual characteristics—source of synergy and choice of location—suggesting that different integration approaches should be applied simultaneously in different contexts of the same post-M&A organization.
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Cantelmi, Raffaele; Steen, Riana, Di Gravio, Giulio & Patriarca, Riccardo
(2022)
Resilience in emergency management: Learning from COVID-19 in oil and gas platforms
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Emergency or crisis management, both in civilian or military context, is regarded as a complex socio-technical system, whose dynamic nature and complexity require a holistic approach. Over time, scholars developed diverse strategies and methods to capture such complexity and effectively design emergency plans for more or less severe disasters scenarios. Nonetheless, planning is not always an omni-comprehensive task, pushing organizations to stretch their adaptive capacities in dynamic and challenging settings.
This manuscript explores such adaptive capacity as put in place by a leading Norwegian organization in providing emergency management solutions, facing unexpected challenges (at the time of the event): handling of Covid-19 infection episodes on offshore oil platforms.
The study, conducted through the Functional Resonance Analysis Method (FRAM) highlights the relevance of organizational learning which allows to handle emergencies by adapting plans to the specific context and by renewing new emergency management procedures derived from lessons learned. The study focuses on three different Covid-19 infection management cases to understand the nuances of actions and emerging adaptations that led to the development of a revised of an emergency plan, seen again through the lens of FRAM. While the methodological approach refers to Covid-19 infection management, we believe it can be extended into larger crisis management, providing a use case for the applicability of FRAM into emergency management scenarios.
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Bleibtreu, Christopher & Stefani, Ulrike
(2022)
The interdependence between market structure and the quality of audited reports: the case of non-audit services
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This paper addresses the effects of a prohibition of providing non-audit services
(NAS) to audit clients. By combining a strategic auditor–client game with a circular market-matching model that has an endogenous number of auditors, we take into account the interdependence between the auditors’ and clients’ incentives, the market structure, and the quality of audited reports. We show that the regulation’s effects depend on the preexisting audit market concentration and the types of blacklisted NAS. In sharp contrast to the effects that regulators desire, a prohibition of providing NAS to audit clients can further increase audit market concentration and decrease the quality of audited reports if the fees that auditors previously earned from providing the blacklisted NAS were relatively high, compared to the reduction in audit costs that result from spillovers. In contrast, a prohibition of the NAS that generate intense spillovers and low NAS fees can have the unexpected—but desired—effect of decreasing market concentration; however, reporting quality also decreases.
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Bø, Eirill & Mjøsund, Christian S.
(2022)
Use of GPS-data to improve transport solutions in a cost and environmental perspective
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In this paper we have utilised GPS data as a base to track truck movements and analyse transport activities. Combined with a Decision Support Tool we have investigated how different transport solutions affect the transport cost and CO2 emissions. The information gained from GPS-data helps firms such as a fruit and vegetables wholesaler to gain better insights into their transport solution and operations from a cost and environmental perspective. This also means that the current analysis remains useful for the transporting company in making strategic decisions as to when and where they should engage in other transport assignments to improve the load factors on their trucks.
This paper presents that the picture the decision-makers had prior to GPS data being used was different from the real situation, and the insights gained lead to new knowledge and actions. As a result, this would contribute to greener and more cost-efficient solutions.
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Bygballe, Lena Elisabeth; Dubois, Anna & Jahre, Marianne
(2022)
The importance of resource interaction in strategies for managing supply chain disruptions
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Dauzère-Pérès, Stéphane & Nonås, Sigrid Lise
(2022)
An improved decision support model for scheduling production in an engineer-to-order manufacturer
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This paper outlines a mathematical model to solve a scheduling problem for a company engineering and producing propellers to order. Nonås and Olsen (Comput Oper Res 32(9):2351–2382, 2005) have previously introduced a Mixed Integer Programming model for this production setting with the objective of minimizing the total tardiness. The mathematical model could however not be used to solve realistic sized problem instances, because of the very large solution time. We propose a new time indexed formulation that can solve most industrial problem instances in less than 10 min. This work is further extended by taking into account limited storage capacity and by proposing different methods to balance between total tardiness and maximum tardiness. We illustrate how the solution time and the criteria change for different setups of the mathematical model and suggest which setup to use for different scenarios. The paper also discusses how the new model can be extended to include unexpected events such as emergency orders and unavailable production equipment.
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Hope, Ole-Kristian; Li, Congcong, Ma, Mark Shuai & Su, Xijiang
(2022)
Is silence golden sometimes? Management guidance withdrawals during the COVID-19 pandemic
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Hope, Ole-Kristian & Liu, Junhao
(2022)
Does stock liquidity shape voluntary disclosure? Evidence from the SEC tick size pilot program
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Ding, Junwen; Dauzère-Pérès, Stéphane, Shen, Liji & Lü, Zhipeng
(2022)
A Novel Evolutionary Algorithm for Energy Efficient Scheduling in Flexible Job Shops
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Improving productivity at the expense of heavy energy consumption is often no longer possible in modern manufacturing industries. Through efficient scheduling technologies, however, we are able to still maintain high productivity while reducing energy costs. This paper addresses a flexible job shop scheduling problem under Time-Of-Use electricity tariffs with the objective of minimizing total energy consumption while considering a predefined makespan constraint. We propose a novel two-individual-based evolutionary (TIE) algorithm, which incorporates several distinguishing features such as a tabu search procedure, a topological order based recombination operator, a new neighborhood structure for this specific problem, and an approximate neighborhood evaluation method. Extensive experiments are conducted on widely used benchmark instances, which show that the proposed TIE outperforms traditional trajectory-based and population-based methods. We also analyze the key features of TIE to identify its critical success factors, and discuss the impact of varying key parameters of the problem to derive practical insights.
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Christ, Quentin; Dauzère-Pérès, Stéphane & Lepelletier, Guillaume
(2022)
A three-step approach for decision support in operational production planning of complex manufacturing systems
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Penz, Louise; Dauzère-Pérès, Stéphane & Nattaf, Margaux
(2022)
Minimizing the sum of completion times on a single machine with health index and flexible maintenance operations
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This paper is motivated by the development of Industry 4.0 and the need to better integrate production and maintenance decisions. Our problem considers a single machine on which jobs of different families are scheduled to minimize the sum of completion times. The machine has a health index which decreases when jobs are processed. To restore the machine health, maintenance operations must be scheduled. Moreover, to be scheduled, each job requires the machine to have a minimum health index which depends on the job family. Two cases are studied: (1) The daily case with a single flexible maintenance operation, and (2) The weekly case with two flexible maintenance operations. The second case is shown to be NP-complete. Two Mixed Integer Linear Programming models are presented for each case. The first model uses ‘‘classical’’ positional variables, while the second model improves the first model by using the notion of master sequence. Different valid inequalities are also proposed. Computational experiments show that the second model is much more efficient than the first model when solved with a standard solver, and the impact of the valid inequalities is
discussed.
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Bleibtreu, Christopher; Königsbruber, Roland & Lanzi, Thomas
(2021)
Financial reporting and corporate political connections: An analytical model of interactions
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We analyze the interactions between accounting institutions and corporate political connections (CPCs). We present a model where a costly policy depends on the perceived economic condition of a firm. This policy and the valuation of the firm by capital market participants create incentives for the firm to manipulate its financial reports. A politician has some discretion over the policy and can use it to favor a connected firm. Our analysis reveals that the firm’s financial reporting is determined by the interplay of an accounting standard, enforcement strictness, and the salience of the policy for the firm. The possibility to manipulate the financial reports imposes an upper boundary on the value of political connectedness which does not exist if only truthful reporting is possible. The reason is that a low credibility of reported figures leads only to a weak revision of the policy. In general, the value of CPCs is highest when the financial reporting regime evenly splits between firms in good and bad economic condition. Our analysis further suggests that while connected firms generally report being in good condition more often than non-connected firms do, the effect of CPCs on absolute reporting manipulation depends on policy salience. If policy salience is low, connected firms exhibit a higher absolute degree of manipulation than non-connected firms do; the opposite holds if policy salience is high.
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de Vries, Harwin; Jahre, Marianne, Selviaridis, Kostas, Van Oorschot, Kim & Van Wassenhove, Luk N.
(2021)
Short of Drugs? Call Upon Operations and Supply Chain Management
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Viana, Joe; van Oorschot, Kimball Elizabeth & Årdal, Christine Oline
(2021)
Assessing Resilience of Medicine Supply Chain Networks to Disruptions: A Proposed Hybrid Simulation Modeling Framework
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Mauritzen, Johannes
(2021)
The Covid-19 shock on a low-carbon grid: Evidence from the nordics
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Steen, Riana; Patriarca, Riccardo & Di Gravio, Giulio
(2021)
The chimera of time: Exploring the functional properties of an emergency response room in action
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Sundgren, Stefan & Svanstrøm, Tobias
(2021)
Regulatory sanction risk and going-concern reporting practices: evidence for privately held firms
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Hope, Ole-Kristian; Huang, Zhongwei & Moldovan, Rucsandra
(2021)
Wall street analysts as investor relations officers
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Steen, Riana; Ribeiro, Hugo & Shukla, Anurag
(2021)
Safety and Security: A cross-professional comparison
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Mauritzen, Johannes & Sucarrat, Genaro
(2021)
Increasing Or Diversifying Risk?Tail Correlations, Transmission Flows And Prices Across Wind Power Areas
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Yang, Wenhui; Chen, Lu & Dauzère-Pérès, Stéphane
(2021)
A dynamic optimisation approach for a single machine scheduling problem with machine conditions and maintenance decisions
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In modern production systems, considering machine conditions is becoming essential to achieving an overall optimisation of the production schedule. This paper studies a single machine scheduling problem, where the actual processing times of jobs depend on their position in the production sequence and maintenance is considered. Moreover, the machine is subject to an uncertain condition variation. There is a trade-off between rejecting a maintenance action, resulting in longer processing times, and accepting a maintenance action, leading to higher processing efficiency for future jobs. The problem is formulated as a finite-horizon Markov Decision Process. The objective is to minimise the makespan. Optimality properties are analysed, based on which a dynamic optimisation approach is developed. Computational experiments demonstrate the effectiveness of the proposed approach.
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Tamssaouet, Karim; Dauzère-Pérès, Stéphane, Knopp, Sebastian, Bitar, Abdoul & Yugma, Claude
(2021)
Multiobjective Optimization for Complex Flexible Job-Shop Scheduling Problems
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Kamsvåg, Vegard; Stensrud, Erik & Myrtveit, Ingunn
(2021)
Safety of Autonomous Ships -INterpreting High Confidence Mistakes of Deep Neural Networks Using Heat Maps
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Flygansvær, Bente Merete; Bygballe, Lena Elisabeth & Harrison, Debbie
(2021)
Hvordan få kraft i bærekraft?
Magma - Tidsskrift for økonomi og ledelse, nr 5, p. 104-110.
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Flygansvær, Bente Merete; Samuelsen, Asta Gjetø & Støyle, Rebecka Våge
(2021)
The power of nudging: how adaptations in reverse logistics systems can improve end-consumer recycling behavior
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Jahre, Marianne & Jensen, Leif-Magnus
(2021)
Coordination at the 10-year mark of the JHLSCM–from global response to local preparedness
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Annelin, Alice & Svanstrøm, Tobias
(2021)
The Triggers and Consequences of Audit Team Stress: Qualitative evidence from engagement teams
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Bruno, Lars Christian & Steen, Riana
(2021)
Norwegian oil market concentration and its effects on the oil service companies 1993–2013
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Bitar, Abdoul; Dauzère-Pérès, Stéphane & Yugma, Claude
(2021)
Unrelated parallel machine scheduling with new criteria: Complexity and models
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Chy, Mahfuz & Hope, Ole-Kristian
(2021)
Real effects of auditor conservatism
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Steen, Riana & Molde, Alf Inge
(2021)
Håndtering av langvarige beredskapshendelser: Læringspunkter etter covid-19-utbrudd på West Phoenix
Magma - Tidsskrift for økonomi og ledelse, p. 70-79.
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Steen, Riana; Ingvaldsen, Geir & Patriarca, Riccardo
(2021)
Engineering resilience in a prison's performance management system
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Viana, Joe; van Oorschot, Kimball Elizabeth & Årdal, Christine Oline
(2021)
Assessing Resilience Of Medicine Supply Chain Networks To Disruptions: A Proposed Hybrid Simulation Modeling Framework
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The objective of the proposed hybrid simulation modeling framework is to improve the understanding and operation of medicine supply chains, to strengthen their resilience to ensure the availability of medicines. The framework draws upon hybrid simulation, supply chain resilience and medicine supply chain literature. The utility of the proposed framework is presented through the development of a case model of a generic (off-patent) case medicine in the Norwegian system to perform scenario-based experiments on disruption events and interventions. Two disruption scenarios are evaluated a demand shock e.g., hoarding, and a supply shock, e.g., a major disruption at a key supplier. The effect of these disruptions on the system without interventions is compared with proactive and reactive interventions, namely prepositioned stock, and flexible ordering. Future directions for framework development have been identified.
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Pinchasik, Daniel Ruben; Hovi, Inger Beate, Bø, Eirill & Mjøsund, Christian S.
(2021)
Can active follow-ups and carrots make eco-driving stick? Findings from a controlled experiment among truck drivers in Norway
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This article presents results from a randomized controlled eco-driving experiment with differential treatment between two groups of truck drivers in Norway. Using data from in-vehicle devices, we investigate whether eco-driving interventions (a course, active monthly follow-ups, and non-monetary incentives) reduce fuel consumption by inducing more efficient driving behavior for drivers in a treatment group, compared to a control group. Hereby, we consider persistence of effects over time and the relative importance of eco-driving factors, while controlling for fixed vehicles, routes, drivers, and weather.
We find significant fuel consumption reductions, persisting over a longer period of time than in most previous studies (where effects fade or disappear), that weather conditions are important, and evidence of an ‘eco-driving learning curve’. This might result from monthly follow-ups and driver rewards. Further, we find spill-over effects through significant fuel savings for drivers in the control group (undergoing no interventions). These are likely the result of them becoming aware that ‘something eco-driving related’ is going on.
Our analysis suggests that improvements on engine and gear management contribute most to fuel savings. We estimate the potential for fuel savings to lie between 5.2 and 7.5% (lower bound, control group) and 9% (upper bound, treatment group). This implies a potential for significant cost savings and emission reductions, which might to some extent be scalable and transferable to other settings. As such, eco-driving may play one part in reducing emissions from road freight, for which much-needed emission reductions are challenging to achieve, especially in the shorter run.
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Steen, Riana & Rønningsbakk, Bernt
(2021)
Emergent Learning During Crisis: A case study of the Arctic Circle border crossing at Storskog in Norway
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Perraudat, Antoine; Dauzère-Pérès, Stéphane & Mason, Scott Jennings
(2021)
Stochastic programming approaches for an energy-aware lot-sizing and sequencing problem with incentive
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Beraudy, Sébastien; Absi, Nabil & Dauzère-Pérès, Stéphane
(2021)
Timed route approaches for large multi-product multi-step capacitated production planning problems
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Deng, Yingwen; Hope, Ole-Kristian, Wang, Cyndia & Zhang, Min
(2021)
Capital market liberalization and auditors’accounting adjustments: Evidence from aquasi-experiment
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Using a shock to the Chinese capital market and unique and detailed audit-adjustment data, this paper investigates the effect of a capital market liberalization program on auditors’ adjustments to their clients’ financial reports. Employing difference-in-differences tests with propensity score matching and firm fixed effects (FE), we find that the capital market liberalization induced by the implementation of the Shanghai-Hong Kong Stock Connect affects auditors’ professional judgment and leads to audit-adjustment changes stimulated by greater reputational and litigation risks for auditors. Specifically, while the liberalization significantly decreases the frequency and magnitude of upward audit adjustments, the probability of downward adjustments remains the same in most cases. Further evidence shows that the effect is more pronounced for companies with high trading volume from Hong Kong investors, audited by the largest audit firms and with low financial transparency.
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Dekeyser, Simon; Gaeremynck, Ann, Knechel, W. Robert & Willekens, Marleen
(2021)
The Impact of Partners’ Economic Incentives on Audit Quality in Big 4 Partnerships
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Economic incentives are fundamental for understanding auditor behavior. In this paper, we investigate the association between the extent of partners’ fee-based compensation, partners’ observable net wealth, and audit quality. Using a sample of Belgian Big 4 audit firms and their predominantly private clients, our results suggest a negative association between audit quality and partner fee-based compensation, and a positive association between audit quality and partner observable net wealth. Moreover, our results show that the latter association is most significant when a partner is carrying a lot of debt, which indicates that a partner’s financial situation may affect audit quality. The extent of fee-based incentives also varies among partners of the same audit firm. Furthermore, partner and client characteristics differ based on the extent of fee-based compensation. Our findings should be of interest to regulators and audit firms as they suggest that audit partner’s economic incentives significantly affect audit quality.
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Che, Limei; Langli, John Christian & Svanstrøm, Tobias
(2021)
Are Audit Partners’ Compensation and Audit Quality related to their consulting revenues?
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Hope, Ole-Kristian & Su, Xijiang
(2021)
Peer-level analyst transitions
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This study examines the effect of peer-level analyst transitions (i.e., switching between brokerage houses) on associated regular incumbent analysts' forecasting performance. We employ a difference-in-differences research design with analyst fixed effects and compare incumbent analysts of different groups within the same broker and same time periods. We find that incumbents who cover at least one common industry as the transiting analyst (i.e., affected incumbents) issue more accurate and timely forecasts after a transiting analyst arrives than incumbents who cover different industries (i.e., unaffected incumbents). Further, affected incumbents issue less accurate forecasts after a transiting analyst leaves than do unaffected incumbents. We also examine potential mechanisms of knowledge spillover and find some evidence that the effect is more salient when the transiting analyst switches from a larger brokerage house, has greater industry scope, or covers geographically linked firms.
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Hope, Ole-Kristian; Jiang, Shushu & Vyas, Dushyantkumar
(2021)
Government transparency and firm-level operational efficiency
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Dekeyser, Simon; Gaeremynck, Ann, Knechel, W. Robert & Willekens, Marleen
(2021)
Multimarket Contact and Mutual Forbearance in Audit Markets
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Barhebwa-Mushamuka, Félicien; Dauzère-Pérès, Stéphane & Yugma, Claude
(2021)
A global scheduling approach for cycle time control in complex manufacturing systems
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Cheng, Stephanie F.; Hope, Ole-Kristian & Hu, Danqi
(2021)
Strategic entry deterrence in the audit industry: Evidence from the merger of professional accounting bodies
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Che, Limei; Hope, Ole-Kristian & Langli, John Christian
(2020)
How Big-4 Firms Improve Audit Quality
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Altazin, Estelle; Dauzère-Pérès, Stéphane, Ramond, François & Tréfond, Sabine
(2020)
A multi-objective optimization-simulation approach for real time rescheduling in dense railway systems
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Hope, Ole-Kristian; Li, Congcong, Lin, An-Ping & Rabier, MaryJane
(2020)
Happy analysts
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Pollock, Kevin & Steen, Riana
(2020)
Total Defence Resilience: viable or not during COVID-19?
A comparative study of Norway and the UK.
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Bø, Eirill & Baxter, John
(2020)
Transparency as a Driver for Logistical Efficiency in WEEE Collection and Transport
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Steen, Riana & Ferreira, Pedro NP
(2020)
Resilient flood-risk management at the municipal level through the lens of the Functional Resonance Analysis Model
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This exploratory study takes a closer look at the flood Risk Management (RM) system at a municipality level. The current practices of RM in municipalities follow to a large extent, a standard structure of RM processes. Their application comes short of addressing the wide range of local specificities and other complexity related socio-technical factors that can have widespread impacts, much beyond the municipal scope. This study uses concepts and ideas from the resilience engineering literature to enhance the practices of the RM system. We apply the Functional Resonance Analysis Method (FRAM) to investigate the extent to which key RM activities are in line with generating anticipating, monitoring, responding and learning capabilities in the flood RM system. We examine the performance of RM functions, how they are coupled, and whether they can be sustained in the wake of a flood event. A triangulation of various qualitative research approaches is adopted, namely using semi-structured interviews, document analysis and workshop. Our findings reveal how the application of FRAM provides a deeper understanding of the underlying factors that shape the resilience of the RM process.
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Wu, Cheng-Hung; Zhou, Fang-Yi, Tsai, Chi-Kang, Yu, Cheng-Juei & Dauzère-Pérès, Stéphane
(2020)
A deep learning approach for the dynamic dispatching of unreliable machines in re-entrant production systems
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Hope, Ole-Kristian; Yue, Heng & Zhong, Qinlin
(2020)
China's Anti-Corruption Campaign and Financial Reporting Quality