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Lyngstadås, Hakim & Berg, Terje
(2024)
The C-Suite of Supplier Collaboration: A Configurational Analysis of the How’s and Why’s.
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Steen, Riana; Roud, Ensieh , Mikkelrud Torp, Trude & Hansen, Thor-Arild
(2024)
The impact of interorganizational collaboration on the viability of disaster response operations: The Gjerdrum landslide in Norway
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van Oorschot, Kim E.; Aas Johansen, Vilde, Lynes Thorup, Nanna & Aspen, Dina Margrethe
(2024)
Standardization cycles in sustainability reporting within the Global Reporting Initiative
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Melaku, Tsegaye; Mekonnen, Zeleke, Terefe Tucho, Gudina, Mecha, Mohammed, Årdal, Christine Oline & Jahre, Marianne
(2024)
Availability of essential, generic medicines before and during COVID-19 at selected public pharmaceutical supply agencies in Ethiopia: a comparative cross-sectional study
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Torba, Rahman; Dauzère-Pérès, Stéphane, Yugma, Claude, Gallais, Cédric & Pouzet, Juliette
(2024)
Solving a real-life multi-skill resource-constrained multi-project scheduling problem
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Melaku, Tsegaye; Mekonnen, Zeleke, Tucho, Gudina Terefe, Årdal, Christine Oline & Jahre, Marianne
(2024)
Availability of essential, generic medicines before and during COVID-19 at selected public pharmaceutical supply agencies in Ethiopia: a comparative cross-sectional study
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Steen, Riana; Norman, James, Bergström, Johan & Damm, Gitte F.
(2024)
Dark knights: Exploring resilience and hidden workarounds in commercial aviation through mixed methods
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Corral de Zubielqui, Graciela & Steen, Riana
(2024)
The Impact of Adaptation on Performance Through Business Resilience in Times of Crisis
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Hovi, Inger Beate & Bø, Eirill
(2024)
Unlocking the potential: How can parcel lockers drive efficiency and environmental friendliness in E-commerce?
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This paper analyses the efficiency and carbon footprint of different last-mile delivery solutions, including parcel lockers, pick-up points, and home deliveries. A Decision Support Tool (DST) is developed, utilizing real data on parcel deliveries and time allocation. The DST distinguishes between fixed, variable, and salary costs, revealing that time spent on delivery tasks and associated salary costs are the primary cost drivers. Deliveries to pick-up points are more efficient than deliveries to parcel lockers, but this efficiency depends on the number of parcels delivered. The environmental footprint of the solutions is influenced by how recipients collect their parcels.
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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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Mustafee, Navonil; Harper, Alison & Viana, Joe
(2023)
Hybrid Models with Real-time Data: Characterising Real-time Simulation and Digital Twins
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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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Fiechter, Peter; Landsman, Wayne, Peasnell, Ken & Renders, Annelies
(2023)
Do industry-specific accounting standards matter for capital allocation decisions?
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Liu, Junhao; Hope, Ole-Kristian & Hu, Danqi
(2023)
Earnings announcements in China: Overnight-intraday disparity
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Based on a unique arrangement of trading and disclosure times around earnings announcements in the Chinese stock market, we provide evidence of a striking overnight-intraday disparity in terms of the reaction to earnings news. Specifically, we find that the overnight period exhibits a strong and consistent reaction to earnings announcements, whereas the intraday period trades against both the earnings news and the prior market reaction during the overnight period. In addition, we show that abnormal overnight returns on earnings announcement days exhibit strong predictability for future stock returns, consistent with the overnight returns containing value-relevant signals. In contrast, we observe no return predictability for abnormal intraday returns on earnings announcement days, which as a result, also undermines the return predictability of abnormal daily returns. We propose possible explanations for the overnight-intraday disparity. We conclude that the differences in trading mechanisms between the two periods as well as in investor composition likely drive the phenomenon.
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Hope, Ole-Kristian; Porumb, Vlad-Andrei, Rusanescu, Simona & Vyas, Dushyantkumar
(2023)
Private information and bank-loan pricing: The effectof upcoming corporate spinoffs
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Pruijssers, Jorien; Simac, Ines & Willekens, Marleen
(2023)
Strength of Audit Firms’ Human Resource Systems and Client-Level Audit Outcomes: Evidence from a Multiple Source Study
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Mustafee, Navonil; Viana, Joe & Harper, Alison
(2023)
Hybrid Models with Real-Time Data in Healthcare: A Focus on Data Synchronization and Experimentation
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Hope, Ole-Kristian; Yue, Heng & Zhong, Qinlin
(2023)
Public Communication of Audit Risks and Related-Party Transactions: Evidence from China
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This paper examines whether and how firms’ engagement in related-party transactions (RPTs) is shaped by public communication of audit risks as required by the expanded audit report. Using the phased regulatory changes in China and a difference-in-differences design with firm fixed effects and matching, we find that firms significantly reduce their RPTs after the adoption of expanded audit reports (EARs). To investigate potential mechanisms, we find that (1) investor scrutiny increases after the adoption of EARs, (2) the reduction of RPTs is more pronounced when EARs are more likely to attract investor attention, and (3) the reduction of RPTs is weaker when firms are less concerned about investor scrutiny. The results suggest that EARs can attract investor scrutiny and increase the possible penalty associated with self-dealing, thus motivating firms to reduce RPTs.
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Arnulf, Jan Ketil; Rasmussen, Janicke, Hjersing, Sandra & Berner, Thea
(2023)
CEO dismissal as an act of human sacrifice: Metaphor or reality?
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Berterottière, Lucas; Dauzère-Pérès, Stéphane & Yugma, Claude
(2023)
Flexible job-shop scheduling with transportation resources
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This paper addresses an extension of the flexible job-shop scheduling problem where transportation resources are explicitly considered when moving jobs from one machine to another. Operations should be assigned to and scheduled on machines and vehicles and the routes of vehicles should be determined. We extend the classical disjunctive graph model to include transportation operations and exploit the graph in an integrated approach to solve the problem. We propose a metaheuristic using a neighborhood function that allows a large set of moves to be explored. As the exact computation of the makespan of every move is time-consuming, we present a move evaluation procedure that runs in constant time (which does not depend on the size of the instance) to choose a promising move in the neighborhood of a solution. This move evaluation procedure is used in a tabu search framework. Computational results show the efficiency of the proposed approach, the quality of the move evaluation procedure and the relevance of explicitly modeling transportation resources. New benchmark instances are also proposed.
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Shukla, Anurag; Solbakken, Even André & Steen, Riana
(2023)
On the cyber-emergency preparedness in a resilient organization
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In recent years, the scientific fields of cyber-security and resilience engineering have emerged as new ways to deal with emerging risks in cyber-socio-technical systems. Unlike conventional security management approaches, focusing on historical data to provide an accurate risk picture, resilience engineering aims to enhance an organization's capacity to anticipate, monitor, and adapt to disruptions and surprises. However, with the increasing cyber threats and changes in national and international security policies, there is a pressing need to examine the resilience characteristics of cyber emergency preparedness in both public and private sectors. To address this need, this study adopts a triangulation method, through online survey and interview with two subject matter experts in the cyber-domain and explore factors that might contribute to enhancing cyber emergency preparedness in dealing with potential cyber threats and attacks. Findings suggest that front-line operators have limited information and capacity to process existing data in the domain of cyber security, highlighting a need for enhancing cyber-related knowledge across organizations. Furthermore, 25% of enterprises in the sample update their cybersecurity risk picture only once a year. The lack of more frequent updates downscales the contingency plans' thoroughness and puts companies in a vulnerable situation given the increasing trend of cyber-attacks.
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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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This paper discusses several issues that were raised by the International Accounting Standards Board (IASB) in their request for information for the post-implementation review (PIR) of the International Financial Reporting Standard (IFRS) 9: Financial instruments – Classification and Measurement. In doing so, we first review the related academic literature and present empirical evidence on the post-adoption impact of IFRS 9. We then discuss conceptual issues associated with the business model and cash flow characteristics assessment in IFRS 9, as well as issues associated with the presentation of fair value changes in other comprehensive income (OCI) and modifications to contractual cash flows. Finally, we identify gaps in the literature and provide suggestions for future research that can help inform accounting standard setters.
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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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This paper aims at linking the work presented in Dauzère-Pérès et al. (1998) and more recently in Kasapidis et al. (2021) on the multiresource flexible job-shop scheduling problem with nonlinear routes or equivalently with arbitrary precedence graphs. In particular, we present a mixed integer linear programming (MIP) model and a constraint programming (CP) model to formulate the problem. We also compare the theorems introduced in Dauzère-Pérès et al. (1998) and Kasapidis et al. (2021) and propose a new theorem extension. Computational experiments were conducted to assess the efficiency and effectiveness of all propositions. Lastly, the proposed MIP and CP models are tested on benchmark problems of the literature and comparisons are made with state-of-the-art algorithms.
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Rodoplu, Melek; Dauzère-Pérès, Stéphane & Vialletelle, Philippe
(2023)
Integrated planning of maintenance operations and workload allocation
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Motivated by a practical problem, this paper investigates the integrated planning of maintenanceoperations and workload allocation on a set of machines in a workshop. Given quantities of productsto be produced per period on a planning horizon must be processed on unrelated flexible machines.Moreover, each machine has to undergo one or more maintenance operations that must be plannedwithin a given time window and impact products differently. The main goal is to find a feasible planthat satisfies the machine capacity by allocating the production quantities to machines and assign-ing maintenance operations as late as possible in their time windows. Various original mathematicalmodels are presented. In particular, we propose models that allow maintenance operations andsome production quantities to overlap two consecutive periods. Computational experiments basedon industrial data show that allowing this overlapping helps the earliness of maintenance opera-tions to be significantly reduced in the most difficult instances, going for example from a total of 14periods to only 1 period, and by more than 35% on average.
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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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This study examines the impact of regulations and standard procedures on safety outcomes in unmanned aerial vehicle (UAV) operations, specifically focussing on Norwegian military UAV systems, from a high-reliability organization (HRO) perspective. By analyzing data from existing regulations, accident reports, and interviews with military drone pilots using thematic analysis, we identify key recurring themes. Our findings highlight the importance of fatigue and exhaustion due to the absence of regulations on resting time for military drone pilots. This poses substantial risks and increases the likelihood of accidents and incidents in UAV operations. Additionally, we uncover gaps in safety reporting and accountability for military UAV pilots, indicating the need for improved reporting procedures that consider the unique operational elements of UAVs. Effective communication between stakeholders, including drone pilots, ground crew, and air traffic controllers, emerges as a critical factor in maintaining situational awareness. This emphasis on communication is consistent with HRO principles and supports the essential safety tasks of UAV pilots, namely sense-making, decision making, and performance. By uncovering the impact of regulations and operational procedures on safety outcomes and addressing fatigue in UAV operations, this research contributes to enhancing the safety and reliability of Norwegian military UAV systems.
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Steen, Riana; Haug, Ole Jacob & Patriarca, Riccardo
(2023)
Business continuity and resilience management: A conceptual framework
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The overall objective of business continuity management (BCM) systems is to provide guidance and analytical subcomponents on how to assess and manage risk and sustain operations when facing a disruptive event. Current BCM practices largely follow a standard structure for formal planning processes and risk-assessment activities. An underlying assumption in standard practices is that systems can be decomposed in subsystems in a meaningful way, as they are tractable and data are available to predict the system's future functionality. However, the reality is much more complex in our volatile world. Standard BCM approaches do not pay adequate attention to the treatment of uncertainties. Thus, they fall short of addressing the complexity of operations involved with emergencies and crisis. Lack of focus on uncertainty hampers the ability of BCM systems to provide sufficient support for decision making in highly uncertain situations. Dealing with such situations necessitates a shift from a defensive risk-management approach, grounded on an illusion of control and accountability, to a proactive stance based on resilience thinking. Responding to this call, we use concepts from the resilience engineering (RE) field and link them to different components of a BCM system. We develop a novel BCM framework and identify a set of resilience influence factors to enhance resilience in BCM systems. We use a case-example, hosted by a leading organization in a second-line emergency response operation in Norway to reflect on the application of a suggested BCM framework.
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Zuiderwijk, Dianka; Steen, Riana & Pedro, Ferreira
(2023)
Learning from Operational planning
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Institutional and regulatory approaches to planning are still primarily based on linearity and predictability and show a trend towards centralised control and prescriptive planning. A second trend recognises unpredictability in complex operations and focuses on dealing with the changeable nature of work. We refer to this adaptive type of planning as operational planning (OP). In this paper, we argue that a shift towards more control and prescriptive planning can undermine this critical adaptive capability in the completion of complex operations. Triggered by lessons drawn from three different studies, we demonstrate that fostering this adaptive capability in complex operations necessitates a shift in how uncertainty is addressed in institutional and regulatory systems. While exploratory, our findings add to a more complete picture of OP and its relevance to the reliability of complex operations.
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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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This paper considers the flexible job-shop scheduling problem with stochastic processing times. To find a sequence insensitive to shop floor disturbances, the available probabilistic information related to the variability of processing times is taken into account by maximizing the makespan service level for a given deadline. This corresponds to the probability of the makespan to be smaller than a given threshold. After showing why this criterion makes sense compared to minimizing the average makespan, a solution approach relying on a tabu search and a Monte Carlo sampling-based approximation is presented. Then, new instances are generated by extending the deterministic benchmark instances. Extensive computational experiments are conducted to evaluate the relevance of the makespan service level and the performance of the proposed solution method. The drawbacks of a number of reference scenarios, including worst-case and best-case scenarios, in addressing effectively the problem under study are presented. A numerical analysis is also performed to compare the scope of the proposed criterion against the minimization of the expected makespan. The accuracy of the proposed solutions induced by the hyper-parameters of the Monte Carlo approximation is explicitly analyzed.
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Hung, Chung-Yu & Shi, Zhenyang
(2023)
Peer-Specific Knowledge and Peer Group Properties in Relative Performance Evaluation
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Although relative performance evaluation (RPE) represents an important compensation practice, selecting a relevant peer firm poses a challenge for compensation committees. We study the implications of a committee’s peer-specific knowledge for the peer group property (i.e., RPE relevance). Committees likely know more about firms within their networks, and such peer-specific knowledge increases with their connections to potential peer firms. Our findings suggest that peer-specific knowledge facilitates not only the inclusion of more relevant peer firms, but also the exclusion of less relevant ones. Moreover, the committees incorporate connected peers’ performance information to a greater extent for risk removal. We address identification challenges by including an intensive set of fixed effects to control for characteristics of the focal and the peer firms and by exploiting exogenous changes to the connections between the committees and the peer firms. Our findings suggest that the compensation committee’s peer-specific knowledge facilitates the RPE practice.
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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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This paper addresses a tactical joint inventory and transportation planning problem for multiple items with deterministic and time-varying demand, considering different transportation modes and item fragmentation. The latter corresponds to the splitting of the same item ordered quantity between several trucks or containers. On the one hand, fragmenting the items potentially reduces the number of containers used. On the other hand, loading the item lot fragments on several containers may negatively impact the handling and shipping operations. This new problem is proposed as a way to tackle such conflict. Several Mixed Integer Linear Programming models are proposed for the problem, which rely on two multi-item lot-sizing models with mode selection and two bin-packing models with item fragmentation. A relax-and-fix heuristic is also proposed. Using realistic instances, computational experiments are first conducted to identify the most efficient model in terms of computational time, to study the impact of key parameters on the computational complexity and to analyze the efficiency of the heuristic. Then, managerial insights are derived through additional computational experiments, in particular, to identify contexts requiring joint optimization of lot-sizing and bin-packing decisions, as well as the impact of item fragmentation constraints. Directions for future research are finally proposed.
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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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This article introduces a framework that unifies and generalizes well-known literature results related to local search for the job-shop and flexible job-shop scheduling problems. In addition to the choice of the metaheuristic and the neighborhood structure, the success of most of the influential local search approaches relies on the ability to quickly and efficiently rule out infeasible moves and evaluate the quality of the feasible neighbors. Hence, the proposed framework focuses on the feasibility and quality evaluation of a general move when solving the job-shop and flexible job-shop scheduling problems for any regular objective function. The proposed framework is valid for any scheduling problem where the defined neighborhood structure is appropriate, and each solution to the problem can be modeled with a directed acyclic graph with {non-negative weights on nodes and arcs}. The feasibility conditions and quality estimation procedures proposed in the literature rely heavily on information on the existence of a path between two nodes. Thus, based on an original parameterized algorithm that asserts the existence of a path between two nodes, novel generic procedures to evaluate the feasibility of a move and estimate the value of any regular objective function of a neighbor solution are proposed. We show that many well-known literature results are special cases of our results, which can be applied to a wide range of shop scheduling problems.
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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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We use a novel dataset that links audit-firm and client-firm financial statement information from the U.K.’s largest audit firms to examine drivers of audit-firm profitability and its implications for audit outcomes. We first explore the determinants of audit-firm profitability and conclude that Big-4 and non-Big-4 audit firms have fundamentally different profitability structures. Big-4 firms have higher profit margins than non-Big-4 firms. Furthermore, Big-4 profitability increases with client size and complexity, while non-Big-4 profitability is higher for smaller, private-firm clients. Next, we examine the relation between audit-firm profitability and audit outcomes. Using a battery of alternative outcome measures, we find that more profitable audit firms deliver higher audit quality. In supplemental analyses we show that the positive relation between audit-firm profitability and audit outcomes is generally stronger for more influential and illiquid clients (i.e. when auditors are exposed to more litigation risk). Our inferences are robust to several endogeneity controls, such as using an instrumental variables approach, controlling for client-firm and audit-firm fixed effects, employing lead-lag and changes specifications, and assessing bias from correlated omitted variables. Our study contributes to the literature by being the first to provide insights into audit-firm profitability and examine in detail its implications for audit quality.
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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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This paper studies the problem of determining energy efficient schedules in a flexible job shop. The goal is to minimize the total energy cost, given a time-of-use pricing scheme, while ensuring that the schedule does not violate a maximum makespan. The problem is first formalized as a mixed integer program. Because it is already difficult to solve, the simpler problem with a fixed sequence of operations is then extensively studied. Some properties are derived for the specific problem with a fixed sequence. These properties show that the complexity of the problem depends on the structure of the energy pricing scheme. They are also used to propose two heuristic approaches. Relying on these heuristics, we further develop an iterative tabu search for the general problem. Extensive computational experiments are carried out to evaluate the solution methods and the potential gains on the total energy cost, depending on the flexibility associated to the maximum allowed makespan and on the time-of-use structures.
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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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COVID-19 pandemic posed a major impact on the availability and affordability of essential medicines. This study aimed to assess the knock-on effects of the COVID-19 pandemic on the supply availability of non-communicable chronic disease (NCD) medicines and paracetamol products in Ethiopia.
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Anchev, Stefan & Lapanan, Nicha
(2023)
Investor Base Size and Underreaction-Consistent Stock Return Anomalies
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We find that several well-documented underreaction-consistent stock return anomalies, such as those based on stocks' earnings-to-price ratios, returns on assets and past returns, arise and persist only among stocks with smaller (institutional) investor bases, which are presumably stocks that are neglected by investors. These results are driven by the short side of our long-short trading strategies (i.e., by the seemingly overpriced stocks from the bottom quantiles of the anomaly variables), they appear even after controlling for several stock characteristics (e.g., market capitalization and institutional ownership) and potential risk factors, and they are considerably more pronounced during periods with more information and/or less technology. Overall, these findings suggest that the incomplete dissemination of (negative) information across investors helps in explaining the occurrence and the persistence of the anomalies.
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Berg, Terje & Lyngstadås, Hakim
(2023)
We’re only in it for the money? Developing sustainable literacy through management accounting curriculum
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This article addresses how and why introductory management accounting courses could contribute to sustainable literacy. Drawing on pragmatic constructivism we develop a course design. We base our discussions on teaching experience from two Business Schools. The proposed course design discusses sustainability around five common themes; (i) fundamental concepts, (ii) what are ‘net income’ and ‘value creation’, (iii) product costing and short-term decision-making, (iv) capital budgeting decisions, and (v) performance measurement. We demonstrate that it is possible to introduce sustainability and how it also allows for a better understanding of management accounting as such. Fundamentally, it is illustrated that critical thinking can be integrated at an introductory level in a management accounting course. As such, this study helps develop students’ sustainable literacy. By allowing sustainability to be a natural part of the standard subjects, the article claims that the subject area contributes to the future demands on management accountants as well.
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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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Crisis-induced learning (CIL), as a concept, has an ancient history. Although the academic literature offers a range of sophisticated approaches to address CIL, it is still not quite clear how we learn, how we know we have learned, and what challenges and opportunities are involved in the CIL process. To address these questions and navigate ways forward, we need to use a specific real-world subject to capture contextual issues involved in a crisis cycle, which affects the learning process. In this paper, we uncover patterns of learning by exploring contextual issues involved with “actual scenarios” related to three COVID-19 episodes (emergencies) between August and December 2020. To analyze the study’s findings, we use three different themes from the DARWIN Generic Resilience Management Guidelines: (1) supporting the coordination and synchronization of emergency-response operation activities, (2) managing adaptive capacity, and (3) developing and revising procedures and checklists. Looking into these “real scenarios” seems fruitful for understanding patterns of learning, and it results in several learning recommendations. Among others, this study reveals how the uncertainty involved in emergency-response operations creates cognitive demands for emergent problem-solving.
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Wood, David A.; Kulset, Ellen Hiorth Marthinsen, Kuruppu, Gowindage Chamara Jayanath, Lyngstadås, Hakim, Madsen, Dag Øivind, Sundkvist, Charlotte Haugland, Allee, Kristian D., Allen, Abigail M., Almer, Elizabeth D., Ames, Daniel, Arity, Viktor, Achhpilia, Muskan, Barr-Pulliam, Dereck, Basoglu, K. Asli, Belnap, Andrew, Bentley, Jeremiah W., Berglund, Nathan R., Berry, Erica, Bhandari, Avishek, Bhuyan, Md Nazmul Hasan, Black, Paul W., Blondeel, Eva, Adams, Mollie T., Bond, David, Bonrath, Annika, Borthick, A. Faye, Boyle, Erik S., Bradford, Marianne, Brandon, Duane M., Brazel, Joseph F., Brockbank, Bryan G., Burger, Marcus, Byzalov, Dmitri, Aghazadeh, Sanaz, Cannon, James N., Caro, Cecil, Carr, Abraham H., Cathey, Jack, Cating, Ryan, Charron, Kimberly, Chavez, Stacy, Chen, Jason, Chen, Jennifer C., Chen, Jennifer W., Akinyele, Kazeem, Cheng, Christine, Wright, Nicole S., Woolley, Darryl, Wood, Jessica, Wood, Bryan D., Witte, Annie L., Wiseman, Denise, Winrow, Tasia S., Winrow, Timothy, Winrow, Brian, Akpan, Mfon, Berg, Terje, Heinzelmann, Rafael & Johanson, Bjørn Daniel
(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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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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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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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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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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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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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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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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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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Hope, Ole-Kristian; Wang, Danye, Yue, Heng & Zhao, Jianyu
(2022)
Information Quality and Workplace Safety
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This paper examines the effect of internal information quality on workplace safety. Using establishmentlevel data on workplace injuries from the Occupational Safety and Health Administration (OSHA) and employing a strict
fixed-effects structure, we show that higher information quality is associated with significantly lower work-related injury
rates. Further investigation reveals that the effect is stronger when more decision rights reside in headquarters, weaker
when employees have greater bargaining power, and weaker when firms are subject to financial constraints. Our
findings are robust to the use of two plausibly exogenous shocks and other robustness checks. Our study suggests an
important economic consequence of information quality not examined by prior literature.
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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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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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Renders, Annelies; Fiechter, Peter & Novotny-Farkas, Zoltán
(2022)
Are Level 3 fair value remeasurements useful? Evidence from FAS 157 rollforward disclosures.
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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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Che, Limei; Myllymäki, Emma-Riikka & Svanstrøm, Tobias
(2022)
Auditors’ self-assessment of engagement quality and the role of stakeholder priority
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This study investigates auditors’ assessment of the quality of their own audit engagements, utilising survey data gathered from a Big Four audit firm in Sweden. We first examine to what extent auditors’ self-reported audit quality threatening behaviours (AQTBs) in the audit process are reflected in their assessment of overall audit quality (OAQ). The results indicate that AQTBs overall and all individual AQTBs are associated with quality assessment, though with variations in their significances. Second, we examine whether AQTBs and OAQ are associated with an auditor’s stakeholder priority, i.e. which stakeholder the auditor considers as her highest priority in the audit work. We find that auditors who consider the employer as the highest priority report more AQTBs. However, priorities are not related to OAQ. Furthermore, auditors prioritising the client or employer tend to assess the overall audit quality as being higher than what the AQTBs would suggest (i.e. they over-assess the quality). Interestingly, the findings regarding priorities are only evident among partners. In sum, the findings of this study provide important insights on how auditors themselves assess their audit quality, and on the role of auditors’ stakeholder priorities.
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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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Purpose
Due to the complexity of digital services, companies are increasingly forced to offer their services “in permanent beta”, requiring continuous fine-tuning and updating. Complexity makes it extremely difficult to predict when and where the next service disruption will occur. The authors examine what this means for performance measurement in digital service supply chains.
Design/methodology/approach
The authors use a mixed-method research design that combines a longitudinal case study of a European digital TV service provider and a system dynamics simulation analysis of that service provider's digital service supply chain.
Findings
With increased levels of complexity, traditional performance measurement methods, focused on detection of software bugs before release, become fragile or futile. The authors find that monitoring the performance of the service after release, with fast mitigation when service incidents are discovered, appears to be superior. This involves organizational change when traditional methods, like quality assurance, become less important.
Research limitations/implications
The performance of digital services needs to be monitored by combining automated data collection about the status of the service with data interpretation using human expertise. Investing in human expertise is equally important as investing in automated processes.
Originality/value
The authors draw on unique empirical data collected from a digital service provider's struggle with performance measurement of its service over a period of nine years. The authors use simulations to show the impact of complexity on staff allocation.
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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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Increasingly, the development of today’s “smart” products requires the integration of both software and hardware in embedded systems. To develop these, hardware firms typically enlist the expertise of software development firms to offer integrated solutions. While hardware firms often work according to a plan-driven approach, software development firms draw on Agile development methods. Interestingly, empirically little is known about the implications and consequences of working according to contrasting development methods in a collaborative project. In response to this research gap, we conducted a process study of a collaborative development project involving a software firm and a hardware firm, within which the two firms worked according to contrasting development methods. We found that the software firm was gradually compelled to forgo its Agile method, creating a role conflict in terms of its way of working. As such, our results contribute to the literature on Agile–Stage-Gate hybrids by demonstrating how, in collaborative embedded systems development, hybridization of development methods may cause projects to fail. Our main practical implication entails the introduction of the “sequential Agile approach.”
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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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Combining the conceptual tools and methods of resilience engineering (RE) with naturalistic decision-making (NDM), in the context of police critical incident command, this study explores the capacity of individual commanders to manage occupational stress during a critical incident or crisis. A case scenario and interviews, together with cognitive task analysis (CTA), are used to investigate how stress affects decision making and performance. The analysis shows: (1) As a social process, sensemaking goes beyond an individual's cognitive capacity. It depends on teams and involves collaboration, sharing and assessing risks and uncertainties. (2) In terms of improvisation, decision-making requires organisational support in training and authorisation. (3) The mechanisms that ensure the synchronisation of activities link to an operational communication strategy grounded on transparency and trust between the parties involved. (4) Individual adaptive capacity also has organisational characteristics. It improves by facilitating and stimulating proactive learning across the organisation. Bringing RE and NDM together clarifies interdependencies. Thus, the gap between the organisational system and the individual's performance might be closed, which improves performances at the sharp end by a feedback loop that reconciles bottom-up and top-down views.
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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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Employing the SEC Tick Size Pilot Program, which increases the minimum trading unit of a set of randomly selected small-capitalization stocks, we examine whether and how an exogenous change in stock liquidity affects corporate voluntary disclosure. Using difference-in-differences analyses with firm fixed effects, we find that treatment
firms respond to the liquidity decline by issuing fewer management earnings forecasts, while, in contrast, control firms do not exhibit a significant change. Next we show that
the effect is more pronounced when firms experience more severe liquidity decreases during the TSPP and rule out a set of alternative explanations. Further strengthening the
identification, we find a consistent reversal effect after the end of the pilot program. To generalize our findings, we use voluntary 8-K filings and conference calls as alternative
voluntary disclosure proxies and find similar effects. Overall, these findings show how an exogenous change in stock liquidity shapes the corporate information environment.
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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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The objective of this thought leadership article is to create a systems view of drug shortages based on the perceptions of practitioners and policymakers. We develop a comprehensive framework describing what stakeholders are currently doing when faced with drug shortages and show the outcomes of their actions. In a review of practitioner literature and public reports published from 2010 to 2020, we identify cause-and-effect relationships related to generic drug shortages in six high-income European countries (Belgium, France, the Netherlands, Norway, Sweden, and the UK) in normal times. By combining and connecting data from these different sources, we develop a systems view of the current state. Though several of the associations covered in the systems view are well known, putting them all together and considering their interrelationships is what is offered by this research. Based on this systems view, we derive three basic solution archetypes for drug shortages: (1) let the market handle it; (2) search for alternatives; and (3) bend the rules. The interactions between these archetypes generate causal ambiguity making it harder to understand and solve the problem as the side effects of solutions can be missed. We show how the interaction of archetypes can compromise intended behavior or escalate unintended behavior. However, our systems view allows us to suggest higher-level solution archetypes that overrule such side effects. The basic and higher-order solution archetypes can provide baselines for research and support the development of future interventions.
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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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The turbulent business environment highlights the need for strategies for mitigating, responding to, and recovering from (that is, managing) supply chain disruptions. Resources are central in these strategies but remain unspecified in the literature. This paper shows how the resource interaction approach (RIA) can help understanding resources in this setting by acknowledging their interactive and networked nature. Based on a conceptual discussion that compares key assumptions within the supply chain risk management (SCRM) and supply chain risk resilience (SCRes) literatures with the RIA, we propose an alternative approach to strategies for managing supply chain disruptions. We challenge the SCRM and SCRes literatures by emphasizing interdependence (as opposed to independence) and pointing to relationships as key resources in strategies for managing supply chain disruptions. Collaboration relying on an interplay between temporary and permanent organizing is suggested as a starting point instead of being just one of several alternative strategies.
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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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This paper examines whether there is information sharing between mutual funds and their auditors about the auditors’ other listed firm clients. Using data from the Chinese market, we find that mutual funds earn higher profits from trading in firms that share the same auditors. The effects are more pronounced when firms have a more opaque information environment and when the audit partners for the fund and the partners for the listed firm share school ties. The evidence is consistent with information flowing from auditors to mutual funds, providing mutual funds with an information advantage in firms that share the same auditors. Our findings are robust to the use of audit-firm mergers and acquisitions (M&As) as exogenous shocks and several other robustness checks. We further find that auditors benefit by charging higher audit fees for mutual fund clients and by improving their audit quality for listed firm clients. Our study provides evidence of bi-directional information sharing between two important market intermediaries.
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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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The humanitarian sector has formulated a collective strategic intent to localize. This involves delegating responsibilities and transferring capacities and resources to national and local actors. However, progress is slower than expected. Strategy execution is hard, and translating a general strategic intent to the actual way humanitarian organizations operate is not obvious. To suggest remedies for the slow progress, this paper investigates drivers and barriers for international humanitarian organizations (IHOs) to localize their logistics preparedness capacities. It is essential to understand IHOs' perspectives as they are global and powerful actors in the humanitarian sector and by far represent the largest recipients of donor funds. We focus on logistics since it constitutes key activities of strong local contextual character, such as procurement, warehousing, and transport. By interviewing practitioners from a representative set of large IHOs, and connecting the empirical insights with relevant theory, we unravel reasons that hinder localization. These include IHOs' strategic choices due to context-sensitive benefits of localization, mandated expectations on IHOs, the lack of internal drivers for IHOs to localize, and resistance to localize due to IHOs’ desire and motives for continued engagement in humanitarian aid. Based on these insights, actionable propositions are developed to help accelerate progress toward localization.
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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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Operations management is experiencing a digital transformation that affects the entire industry landscape. There has been scant research on how digitalisation affects employee well-being in the operations workforce. Using self-determination theory, we bridge this research gap by examining how basic psychological needs among the operations workforce are affected by digitalisation. Our empirical data is collected by a survey from 132 employees in the operations job function in the U.S. The empirical evidence is analysed in a configurational manner by using a fuzzy set Qualitative Comparative Analysis. Our findings suggest there are five empirical important empirical solutions for explaining the presence of employee well-being, as well as four important empirical solutions for the absence (negation) of employee well-being. Our configurational solution consists mostly of both digital competence, social relatedness, and digital autonomy. This is in accordance with the self-determination theory. However, there are several alterations to how important they are among different configurational solutions. The presence of well-being in life and psychological well-being seems less relevant for obtaining well-being at work. We discuss the theoretical and practical implications of our findings and provide recommendations to managers for how to promote employee well-being.
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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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The complexity of decision-making for companies buying transportation services has increased due to the presence of more options and pricing schedules for transportation. Many companies make transportation and inventory decisions in an uncoordinated way and select only one transportation mode, missing opportunities for logistics cost savings. The experimental study in this paper is based on a real-world decision problem faced by a Scandinavian company that distributes fast-moving consumer goods and wants to determine its transportation strategy. We propose a novel multi-mode lot-sizing model with dynamic deterministic demand to illustrate the cost impact of accurately modelling piecewise-linear transportation costs and allowing a more flexible usage of transportation modes when planning order replenishments. We compare three transportation strategies with increasing degrees of flexibility: two single mode strategies, where one strategy is more flexible than the other, and a multi-mode strategy. We conclude that managers can significantly reduce costs by increasing the flexibility of mode selection in transportation strategies.
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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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We examine how the extent and distribution of industry knowledge within an audit team affect audit outcomes. While prior research examining the role of auditors' industry knowledge focuses mainly on audit firms, audit offices, and audit partners, audits are conducted by audit teams. Using an audit framework and proprietary data from a Big 4 firm that includes audit hours for each team member, we find that Big 4 audit teams with higher average industry knowledge are associated with more audit effort. In contrast, we find mixed evidence on the relation between the average hourly internal cost rate and team knowledge. Furthermore, we find that balanced teams, which have at least one team member who qualifies as an industry specialist at both the senior rank and junior rank, produce higher-quality audits than teams that have no specialists. In contrast, the audit quality of unbalanced teams, which have a specialist at the senior rank but not the junior rank or vice versa, is not statistically different than teams with no specialists. Overall, our evidence suggests that both the extent and distribution of industry knowledge within a team matter for audit production and that industry knowledge is utilized more effectively when it is spread throughout the team. The findings have useful implications for audit firms and regulators regarding how team composition and industry knowledge affect audit outcomes.
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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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The recent debate on urban vibrancy and its associated spatial characteristics worldwide has increasingly attracted the attention of planners and decision-makers in Norway and the European Union seeking to develop compact cities. This study investigated the spatial pattern of urban vibrancy associated with urban form and the determinants in Oslo, Norway. A total of 552 km2 of the Oslo central metropolitan area was classified into 12 neighborhood groups and a data-driven methodology was applied via SPSS, Python, and ArcGIS to analyze urban vibrancy, where each cell was denoted as a 1 km2 area of 24 variables. As a result of clustering via principal component analysis, six principal components were extracted with 12 critical factors. Results indicated that the location and distribution of commercial buildings, public buildings, residential buildings, and companies and the total population are the most important drivers of neighborhood vibrancy in Oslo. Vibrant neighborhoods usually appear in high-density, central urban areas with a high concentration of commercial and public buildings with various functions along main streets. In contrast, less vibrant neighborhoods have fewer service facilities and are surrounded by single residential areas, large venues, green spaces, vacant land, or land for transportation in the low-density suburban and semi-urbanized areas. This research offers a quantitative basis for a wider range of neighborhood performance assessments, provides a discussion of compact city theory, and draws the attention of decision-makers on planning policy at the neighborhood level, which can also be adapted to other European cities.
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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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This research explores supply resilience through an equifinality lens to establish how buying organizations impacted differently by the same extreme event can strategize and all successfully secure supply. We conduct case study research and use secondary data to investigate how three European governments sourced for ventilators during the first wave of COVID-19. The pandemic had an unprecedented impact on the ventilator market. It disrupted already limited supply and triggered a demand surge. We find multiple paths to supply resilience contingent on redundant capacity and local sourcing options at the pandemic's onset. Low redundancy combined with limited local sourcing options is associated with more diverse strategies and flexibility. The most notable strategy is spurring supplier innovation by fostering collaboration among actors in disparate industries. High redundancy combined with multiple local sourcing options is associated with more focused strategies and agility. One (counter-intuitive) strategy is the rationalization of the supply base.
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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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In some manufacturing contexts, such as semiconductor manufacturing, machines must be qualified, or eligible, to process a product, and machines cannot be qualified for all products. This paper investigates the problem of optimizing a given number of new qualifications of products to machines to maximize a flexibility measure that evaluates the balance of the qualification configuration of a work center in terms of utilization rate of machines on a set of non-identical parallel machines. Motivated by empirical observations, new solution approaches, notably inspired by heuristics for discrete location problems and based on the analysis of dual variables, are proposed and compared on industrial data from a semiconductor manufacturing facility and on randomly instances. The use of dual variables leads to heuristics that are effective both in terms of solution quality and computational time. The best proposed approach is currently used in the decision support system of a semiconductor manufacturing facility.
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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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The many management guidance withdrawals during the COVID-19 pandemic have attracted considerable attention from the media, investors, and regulators. This study analyzes the determinants and consequences of these withdrawals. We find that guidance withdrawals are due to economic uncertainty, resulting from firms’ exposure to the COVID-19 pandemic rather than poor financial performance. Also, the effect of COVID-19 exposure on guidance withdrawals is stronger when firms face higher litigation risk. Further, guidance withdrawals result in abnormally large trading volumes and high analyst forecast dispersion but do not harm stock prices or the level of analyst earnings forecasts. Overall we believe the findings have implications for understanding corporate disclosure practices during periods with heightened economic uncertainty.
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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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In this paper, a practical relevant operational production planning problem in complex manufacturing systems is addressed. In this problem, lots are planned individually to provide a more detailed plan than approaches that only consider production quantities. A three-step approach, which is currently fully integrated and used in a Decision Support System, is then introduced. This work follows the one of Mhiri et al. [2018. “Heuristic Algorithm for a WIP Projection Problem at Finite Capacity in Semiconductor Manufacturing.” IEEE Transactions on Semiconductor Manufacturing 31 (1): 62–75] who addressed this problem. We push the approach a step further by introducing new optimisation possibilities through new smoothing rules, whose performance is studied according to different indicators. Furthermore, we present the production planning process in which the decision support tool is embedded and how it bridges the gap between the upper and lower planning levels.
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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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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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Sundgren, Stefan & Svanstrøm, Tobias
(2021)
Regulatory sanction risk and going-concern reporting practices: evidence for privately held firms
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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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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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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.