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Remanufacturing has been studied extensively from an economic modelling perspective. However, the number of studies focusing on models that consider the implementation difficulties in industry, such as data availability and model transparency, is low in comparison. This paper aims to identify how an initiation of remanufacturing can be economically assessed with models particularly suitable for implementation in industry. These models should contribute to spreading the know-how about initiating remanufacturing to transit industries towards more circular resource flows. To target the aim, a systematic literature review was conducted. The search resulted in a total of 964 papers published through August 2021. The relevant papers were categorised into a two-dimensional framework indicating the level of computer support needed to handle the model and the level of requirements to use the model in terms of data requirements, both of which are considered essential in the industrial implementation of the models. The review revealed a further need for research on assessing remanufacturing initiation profitability, especially on economic assessment models designed to assist industries without previous remanufacturing knowledge in such an initiation., Remometer, Mistra REES

Remanufacturing has been modelled extensively from an economic perspective. However, there are relatively few studies focusing on models that consider the implementation difficulties in industry, such as data availability and model transparency. This paper aims to identify how remanufacturing initiations can be economically assessed with models particularly suitable for industry. These models should contribute to disseminating the know-how about initiating remanufacturing to transit industries towards more circular product flows. To fulfil this aim, a systematic literature review was conducted. The search resulted in a total of 964 papers published till August 2021. The results show that assessment models could be categorised into a two-dimensional framework indicating the level of computer support needed to handle the models and the level of data requirements to use the models, both of which are considered essential in the industrial implementation of the models. The review revealed and structured a further need for research on assessing remanufacturing initiation profitability, especially on economic assessment models designed to assist industries without previous remanufacturing knowledge in such an initiation., Remometer, Mistra REES (Resource-Efficient and Effective Solutions)

This article introduces an initiative aimed at improving university-level education, carried out in the context of the Erasmus Plus IE3 project and focused on the renewal of courses in an industrial management master, driven by the need to incorporate new technological aspects, such as digitalization and Industry 4.0. The intention was also to promote a methodological change in the learning process by concentrating on practical project development, paying special attention to the needs of a whole new generation of learners and its particularities. This analysis builds on papers presented at previous INTED conferences that created the competency framework and methodological approach. The paper provides added value by discussing the integrated implementation between theoretical and practical aspects when learners must cooperate with students who do not take part in the course to complete industrial projects. Furthermore, the authors assess both the theoretical knowledge acquired by the learners and their practical performance, while also considering the relationship between them. The learners' perspective, gathered through video testimonies and surveys, is significant, given that they are participants in the education, and serves to point out possible strengths and weaknesses of the initiative, with the aim to further improve this approach. Based on the elements introduced, on the methodology and collected results, some conclusions will be formulated in order to assess the proposed approach, as well as to identify improving vectors to be considered. Recommendations in the context of the IE3 project will also be formulated.

In the era of Industry 4.0 and digitalization, planning solutions need to co-exist with each other and be able to manage higher complexity and with a higher performance. As the concept smart production planning and control is a part of industry 4.0, it is highly relevant to study and is in this paper explored on the four elements of smart PPC (real-time data management, dynamic production planning and re-planning, autonomous production control, and continuous learning). This paper provides a framework for linking the four elements of smart PPC with data quality issues in state-of-the-art production planning and control environments. Maintaining a high standard of data quality in the business processes aids the organization to stay competitive in its market. Hence, our assumption is that a high level of data quality is needed in production planning and control for a high-performance outcome. The empirical part of our study results in a bar-chart of seven data quality problems and their occurrences together with their causes in PPC. According to the empirical data results, inaccurate data entries is the most common data quality problem related to PPC. The causes of the inaccurate data entries can be linked to human resources and organizational control. Future research should strengthen the validity of the proposed linkages between data quality problems and elements of smart PPC and implications on strategic, tactical, and operational planning levels.

On-site activities are typically performed when the end-product is immovable once it has been assembled and/or due to weight and space constraints in the production and transportation system. It is primarily a customer order driven type of production with a high level of customization. However, some customer order driven and/or customization activities can, or should, be performed off-site, but these aspects are typically treated in isolation of each other. There is therefore a need to make a combined assessment of on-site activities, customer order driven production, and customization activities. The purpose of this paper is thus to develop a typology that provides a holistic view of on-site activities in relation to customer order driven and customization activities. A flow-based three-dimensional typology is developed to assess combinations of three dimensions: flow driver, flow differentiation, and flow location. The property of each dimension is determined using decoupling points. The typology represents how on-site activities impact the feasibility of customer order driven and customization activities. “On-site” is defined as pursuing activities at the site where the final delivery is made. The findings show that forecast driven activities are risky to perform on-site and these should instead be performed before delivery to the site (off-site). The typology is applied to three case companies to illustrate its applicability to building construction. Future studies should extend the typology application to other types of construction and ETO industries to enable benchmarking of site-based production to other contexts with similar challenges related to on-site/off-site production.

PurposeThis study explores the impact of carbon neutrality policies on Chinese stock market from a supply chain perspective. Specifically, the carbon policy refers to the Action Plan for Carbon Dioxide Peaking Before 2030 (the Plan) in China.Design/methodology/approachThis paper is based on the resource dependence theory (RDT) and applies the event study methodology to explore the impact. It uses the cross-sectional regression model to reveal the moderating effect of supply chain characteristics on the stock market reaction with a data set of 354 listed companies in A-shares (excluding ChiNext and SME board).FindingsThe promulgation of the Plan shows a significant negative stock market reaction. Customer concentration, out-degree centrality and smart supply chains (SSCs) have a significant negative moderating effect. In-degree centrality and supplier concentration have a significant positive moderating effect. Furthermore, the conclusions concerning out-degree centrality, supplier concentration and SSCs are counterintuitive.Practical implicationsFor policymakers, the study results provide a reference for evaluating the carbon neutrality policy. For managers, this study provides theoretical support for strategically adjusting and designing supply chain structures in the context of advocating peak carbon dioxide emissions and carbon neutrality.Originality/valueThis paper is the first attempt that includes the supply chain structure factors into the impact of carbon neutrality policies on the stock market., Funding Agencies|Major Program of the National Social Science Foundation of China [22ZD139]; National Natural Science Foundation of China [72091210, 72091214]

The main goal of this paper is to present state-of-the-art as to the cutting-edge teaching and learning techniques and tools for delivering innovative higher education and training to the future generation of "knowledge workers". Starting from the best identified education experience, expected development of future digital tools for supporting and improving the learning experience is discussed. Tools, categorized for both hard and soft skills, required by the implementation of the Industry 4.0 concept are introduced. The paper describes how the Erasmus+ project IE3 tries to identify the most appropriate educational methodologies and tools for regular classes and innovative e-learning courses in industrial engineering and management (IE&M) for both university students and industry workforce. Finally, some examples from Italy, Poland, Spain and Sweden are given on how higher education institutions and industry work closer together in order to prepare learners how to handle the knowledge and training requirements related to the realisation of the Industry 4.0 concept., Funding Agencies|European CommissionEuropean Commission Joint Research Centre [EAC-A03-2018-KA]

In this paper, two approaches for measuring the distance between stock returns and the network connectedness are presented that are based on the Pearson correlation coefficient dissimilarity and the generalized variance decomposition dissimilarity. Using these two procedures, the center of the network is determined. Also, hierarchical clustering methods are used to divide the dense networks into sparse trees, which provide us with information about how the companies of a financial market are related to each other. We implement the derived theoretical results to study the dynamic connectedness between the companies in the Swedish capital market by considering 28 companies included in the determination of the market index OMX30. The network structure of the market is constructed using different methods to determine the distance between the companies. We use hierarchical clustering methods to find the relation among the companies in each window. Next, we obtain a one-dimensional time series of the distances between the clustering trees that reflect the changes in the relationship between the companies in the market over time. The method from statistical process control, namely the Shewhart control chart, is applied to those time series to detect abnormal changes in the financial market., Funding Agencies|Örebro University

Nonlinear degradation prediction of lithium -ion batteries is of great value in battery management systems. Knee point in degradation is a significant signal for state of health. However, large data generated by diverse aging mechanisms and dynamic operating conditions cannot be used completely in prediction. Firstly, this paper proposes a novel data -driven discrete grey model for battery degradation with knee point based on small sample modeling. Secondly, combined with four non -numerical differential methods, knee point is identified according to the predicted degradation trajectory. Then, batteries in 24 different fast charging modes are selected as a set of experimental subjects. Results show that 40% data of total cycles is sufficient to effectively predict battery degradation trajectory and identify the knee point. Finally, performance of fast charging modes is analyzed based on the predicted knee point. This work demonstrates the strong applicability of the grey model in reasonably predicting battery degradation trajectory and accurately identifying the knee point, providing a reference for fast charging schemes in complex engineering systems., Funding Agencies|National Natural Science Foundation of China [72171116]; Fundamental Research Funds for the Central Universities [NZ2020022]; The 333 talent project in Jiangsu Province (China)

Enterprises are facing the superimposed challenges of digitalization and greening. The shift from reactive green technology innovation (RGT) to proactive green technology innovation (PGT) has special significance for sustainable economic development. Which strategies will companies choose? Can digital transformation (DT) motivate companies to transform their green innovation strategies? Enterprises' green innovation strategy choices must be explained with regard to digitalization. The purpose of this paper is to reveal how digitalization affects the choice of green innovation strategies and to provide a realistic basis for the sustainable development of heavily polluting enterprises. We formulated a "DT -capability -strategy" theoretical framework incorporating external constraints and internal attitudes to empirically test the microdata of 505 heavily polluting enterprises. The results show that: (1) DT can shift the heavily polluting enterprises' green innovation strategies from RGT to PGT. Endogenous tests and robustness tests support this conclusion. (2) A mechanism test shows that environmental regulations cannot significantly regulate a green innovation strategy. Only a company's capabilities and attitudes can influence PGT but their effects on RGT are not statistically significant. (3) The influence of DT on green innovation strategies shows multi -dimensional heterogeneity in the digital infrastructure, scale, and innovation level of the enterprise. The conclusions provide implications for enterprises to integrate their digital and green behaviors., Funding Agencies|Philosophy and Social Science Foundation of China [22AJY005]; The 2023 Xinjiang Production and Construction Corps (XPCC) Graduate Innovation Project

In this paper, we investigate whether key relations in the crude oil market have been stable over time. This is done by estimating hybrid time-varying parameter structural Bayesian VAR models using monthly data ranging from February 1973 to May 2023. Model selection suggests that while stochastic volatility is preferred over homoscedasticity, the dynamics of the model are best described by constant parameters in all equations.

Remanufacturing has in recent decades become an alternative way for sustainable development to cope with the increasingly resource crisis and environmental pollution problems. The line balancing of remanufacturing is more complex than that of traditional manufacturing due to the uncertainty in the remanufacturing process, especially as the assembly time is uncertain. As a result, the line balancing of the remanufacturing assembly has become a critical issue. This paper evaluates the uncertain assembly time in each station based on an approach of Fuzzy Graphical Evaluation and Review Technology (FGERT) network. A remanufacturing multi-objective mixed-flow assembly model is established by optimizing the cycle time, assembly line smoothing coefficient and balance time loss rate. Then an adaptive bilayer genetic algorithm is proposed to solve the optimization problem. Finally, an example was given to demonstrate the effectiveness of the proposed method. Results show that the production rhythm balance of remanufacturing assembly is significantly improved, and the idle time in each assembly station has been reduced as well. The cycle time of the remanufacturing has reduced from 344s to 336s, with the smoothing coefficient and balance time loss rate of being 8.73 and 1.69% compared to that without assembly line balancing. The proposed method provides a useful tool for improving mixed-flow remanufacturing assembly lines in an electromechanics industry. Copyright (C) 2022 The Authors.

As environmental issues attract more concern, shifting towards sustainable manufacturing that includes remanufacturing has become a strategic solution to enable a profitable business while improving environmental performance. The aim of this paper is to investigate the economic feasibility of remanufacturing at different supply chain locations for a robotic lawn mower manufacturer attempting to expand their business. Through a case study, five potential location categories were identified, of which two were deemed economically feasible: spare parts warehouse (OEM) and decentralized (dealers). The other three alternatives were deemed inferior in comparison, or only plausible, but identified as risky through a sensitivity analysis.

In this paper a mixed-integer linear programming (MILP) model is developed to be used as a decision support tool for the chemical company Perstorp Oxo AB. The intention with the mathematical model is to maximize the profit and the model can be used in the process of planning the supply chain for the company. Perstorp Oxo is classified as a global company in the process industry and is has production sites in Gent, Castellanza, Stenungsund and Perstorp. The site in Stenungsund is in focus in this paper. The company produces chemicals that later are used for example in textiles, plastic and glass production. Perstorp Oxo also uses inventories in other countries for enabling the selling abroad. It has two larger inventories in Antwerp and in Tees and two smaller in Philadelphia and in Aveiro. The larger facilities store five different products and the smaller take care of one type each. To be able to find feasible and profitable production plans for the company we have developed and implemented rolling horizon techniques for a time horizon of one year and used real sales data. The outcomes from the model show the transportation of products between different production sites, the different production rates, the levels of inventory, setups and purchases from external suppliers. The numerical results are promising and we conclude that a decision support tool based on an optimization model could improve the situation for the planners at Perstorp Oxo AB. (C) 2020 by the authors; licensee Growing Science, Canada, Funding Agencies|Swedish Foundation for Strategic Research (SSF)Swedish Foundation for Strategic Research

The cost of public transport has increased more than the supply in recent years in Sweden. One of the main cost drivers identified is peak-hour traffic. The major operating cost factors are the need for a large bus fleet for short periods during mornings and afternoons and the scheduling of drivers for shorter periods than the minimum working hour restriction. The objective of this paper is to study the effect of the number of buses needed (and hence the operating cost) during peak hours when adjusting the bus departure times. The study also analyses the increase in public transport supply and the number of boarding passengers if the cost reduction is re-invested. The analysis is based on case studies and simulated scenarios of possible adjustments in departure times for buses. The results show that by marginally adjusting the departure times, fewer buses are needed which leads to decreased operating costs. Further, the results show that the reduction in costs can be used to improve public transport in the area by expanding the supply of public transport in the long run., Funding Agencies|Swedish Energy Agency [51089-1]

Online reviews contain comparative opinions that reveal the competitive relationships of related products, help identify the competitiveness of products in the marketplace, and influence consumers’ purchasing choices. The Class Sequence Rule (CSR) method, which is previously commonly used to identify the comparative relations of reviews, suffers from low recognition efficiency and inaccurate generation of rules. In this paper, we improve on the CSR method by proposing a hybrid CSR method, which utilises dependency relations and the part-of-speech to identify frequent sequence patterns in customer reviews, which can reduce manual intervention and reinforce sequence rules in the relation mining process. Such a method outperforms CSR and other CSR-based models with an F-value of 84.67%. In different experiments, we find that the method is characterised by less time-consuming and efficient in generating sequence patterns, as the dependency direction helps to reduce the sequence length. In addition, this method also performs well in implicit relation mining for extracting comparative information that lacks obvious rules. In this study, the optimal CSR method is applied to automatically capture the deeper features of comparative relations, thus improving the process of recognising explicit and implicit comparative relations., Funding agencies; This work is supported by the Natural Science Foundation of China [72001215, 71771177], the Fundfrom Chongqing Key Laboratory of Social Economic and Applied Statistics [KFJJ2019099], ShanghaiMunicipal Education Science Research Project (Philosophical and Social Sciences General Project, No.A2023010)

This research paper focuses on the implementation and evaluation of Minervini's momentum analysis techniques in an algorithmic approach. The study aimed to assess the limitations and challenges associated with executing Minervini's strategy in an algorithmic trading system. Several technical restrictions, practical application problems, and the exclusion of fundamental and catalyst aspects contribute to the implementation of a primitive variant of Minervini's strategy. The challenges included the subjective nature of base patterns making bases difficult to identify and limitations in risk and position sizing. However, despite the challenges, the algorithmic approach offers advantages such as the ability to analyze a large number of stocks rapidly. It is suggested to use the algorithm as a tool for stock exclusion rather than fully automating the buying and selling decisions. The research investigates the possibility of generating excess returns in Sweden, Denmark, and Finland using the implemented algorithm over different time periods from 2008 to 2023. Hundreds of stocks were divided up into 18 stock portfolios based on market capitalization size calculations for a given year. These portfolios were traded using both the momentum strategy and an index strategy. The empirical results indicate that small-cap portfolios exhibited consistent excess returns compared to mid-cap and large-cap portfolios, particularly during high volatility periods. However, the research did not account for transaction costs, which are essential to evaluate the strategy's net returns in real-world scenarios. Despite the exclusion of transaction costs in the study, the significant excess returns observed in small-cap portfolios indicate that the implemented momentum strategy performs notably better for small-cap stocks compared to mid-cap and large-cap stocks. This finding contradicts the efficient market hypothesis, assuming equal transaction costs across different market capitalizations. F

The business of two-sided platforms, such as those used for online ride-sharing, has expanded rapidly thanks to opportunities to efficiently match supply- and demand-side users. However, the development of these platforms faces the challenge of complying with corporate social responsibility (CSR) regulations, particularly on the supply side of two-sided platforms. How to improve CSR investment, in order to reduce CSR violations while ensuring profitability, is now an important question. In this paper, we develop a game-theoretic model for a two-sided platform and analyze the impacts of network externalities (including customer network externality and provider network externality) and risk aversion on CSR investment decision-making. The analytical results show that, contrary to our intuition, greater network externalities do not necessarily stimulate the platform to invest in CSR. When the strength of customer network externality is high, investment in CSR may have a "dilution effect", i.e., CSR investment may reduce the platforms number of users and profit. Conversely, risk aversion always has an "incentive effect" on CSR investment, thereby increasing the platforms willingness to invest in CSR. Second, both provider and customer network externalities will increase the platforms prices. Interestingly, when the strength of customer network externality is high, the platform attracts more customers, even at high prices. Finally, our analysis indicates that risk aversion may reduce customer surplus when the strength of customer network externality is high. This result contradicts the initial expectation that risk aversion inspires platforms to invest in CSR, thereby improving customer utility and customer surplus.& COPY; 2022 Elsevier B.V. All rights reserved., Funding Agencies|National Natural Science Foundation of China [18ZDA060]; Major Program of the National Social Science Foundation of China; [71672121]

Comparative relations behind online reviews contain rich information concerning customers assessments of different products or services, thereby supporting upcoming consumers purchase decisions, as well as helping to identify enterprises market competitiveness. Instead of using the pattern recognition method, this paper proposes a hierarchical multi-attention network (HMAN) model to extract the comparative relations, in order to greatly reduce the requirements of artificial features and the manual annotation in the relation mining process. Such model outperforms both traditional classification models and text classification models in terms of accuracy, with its F1-score up to 81%. Besides, the proposed model has a good performance on extracting comparative relations from long texts where comparison information is relatively scattered. In this study, we visualise results of different experiments in order to demonstrate the interpretability of this model, and furthermore explore the mechanism of multi-attention method in comparative relations mining. This study applies the deep learning method instead of pattern recognition to automatically capture deep features of comparative relations, and therefore it redefines the identification process of comparative relations., Funding Agencies|Natural Science Foundation of China [72001215, 71771177]; Innovation Fund for University Production, Education and Research from Chinas Ministry of Education [2019J01012]; Chongqing Key Laboratory of Social Economic and Applied Statistics [KFJJ2019099]; Fundamental Research Funds for the China Information Technology Security Evaluation Centre

Purpose The purpose of this paper is to analyze the influencing factors of new logistics service product design (NLSPD) in China to establish a theoretical framework for the future development of the logistics industry. Design/methodology/approach The paper adopts the multi-case study method based on a sample of four Chinese logistics enterprises, in which the authors consider the logistics service maturity (LSM), a distinct characteristic of logistics enterprises. Findings NLSPD is directly related to the degree of supply-demand matching (SDM) and LSM. Customer demand, service capability and peer competition influence the performance of NLSPD through the SDM degree, whereas LSM moderates these influencing mechanisms. Moreover, the degree of SDM has a positive impact on LSM. Practical implications - The findings can help the managers of logistics enterprises and practitioners in the logistics industry understand the complexity of NLSPD. First, they should broaden and deepen their service offering to enhance the degree of LSM. Second, they should pay attention to the factors that affect SDM systematically. Finally, it is vital to balance the relationship between LSM and SDM. Originality/value NLSPD has become an important tool affecting the competitiveness and sustainability of logistics service enterprises. This is the first paper to propose a theoretical framework for NLSPD that considers the characteristic of the logistics industry. It clarifies the mechanisms of influencing factors, and contributes to the literature by filling the research gap., Funding Agencies|Major Program of the National Social Science Foundation of China [18ZDA060]

The most important and time consuming part of an industrial application of control is the modelling. It may take 50 per cent or more of the entire project. Therefore a major challenge for a control systems supplier like ABB is to constantly try to decrease the engineering effort for modelling. This paper discusses some different aspects of modelling and identification originating from application in many different industries such as pulp and paper, rolling mills, power plants and specialty chemicals.

In the strategic planning of manufacturing, companies should assess their competitive advantage with the means of performance measures (PMs) and achieve a consistency with the decision making. The literature on PMs shows that there are mainly two views of PM development. The first view is the PM diversity view which highlights the importance of using a wide set of PMs. The other view is PM alignment, which advocates the alignment between PMs and manufacturing strategy. Although the rich literature on PMs, research on PMs in Small- and Medium sized enterprises (SMEs) is limited but shows that the use of PMs in SMEs is typically financially focused, informal, and unstructured. The use of this approach in SMEs is likely to hinder the achievement of strategic objectives. This paper contributes to the research of PMs in manufacturing SMEs by analysing the relationships between the use of PMs and certain attributes of the SME. The used approach is multiple case study for exploring linkages between PM diversity and alignment with the manufacturing strategy and firm context. The data collection of each SME includes several strategic manufacturing attributes such as type of production system, manufacturing capabilities, and no. of PMs and specific measurements. The findings indicate a strong relationship between PM diversity and firm turnover, whereas the relationship seems weak between PM diversity and manufacturing capability. Furthermore, the relationship between PM alignment and competitive priorities indicate no alignment for SMEs, whereas the alignment between production system and competitive priorities seems to be stronger.

The process industry in general is very energy-intensive, and therefore models focusing on energy can be very important in order to reach higher profitability. In this study, an optimization model of the supply chain in a pulp company, where energy is included with respect to its revenue generating capabilities, is used. Using real company data, and through an analysis of the model’s results, we show that higher profitability can be achieved when integrating energy into the planning process. Our findings show that when energy-intensive raw materials not only provide fibre to the pulp process but also generate an energy surplus, there is room for different planning approaches in order to maximize the total profit. This paper reveals promising changes that can be made for improving the current planning process. The scenarios considered involve market changes for energy demand and price, and also alternative production opportunities. A cross-analysis compares the scenarios in order to reveal additional relations that are important to consider. Depending on a price change of energy, the model prioritizes in its selection of pulp products to produce. From this we provide guidelines on where and when to increase or decrease pulp production. The model shows that the company can increase its total profit no matter which of the included energy parameters that increase in price. The paper contributes to previous research by enhancing the usefulness of this model for not only the case company as such, but also by illustrating and describing how the approach applied can be useful for other cases within the energy intensive industry., The previous status of this article was Manuscript and the original title was How energy price changes can affect supply chain planningat a pulp company.Funding agencies: Swedish Foundation for Strategic Research (SSF)

This paper provides a systematic literature review of Sales and Operations Planning (S&OP) in process industries. The aim is to investigate the present state of S&OP in process industries in comparison to discrete manufacturing industries and to identify the desired future state of the S&OP process based on the specific characteristics of process industries. The findings of this paper show that this issue has not received much attention in the academic world. Hence there is a need for conceptual models with focus on process industries’ specific characteristics. Process industries are actually hybrids of continuous production and discrete production (respectively, upstream and downstream of the discretization point) and the specific characteristics of process industries are related to the continuous production part. Thus, in this paper, the characteristics upstream of the discretization point are investigated and the integration of them in the S&OP process of the process industries is stressed., The original title in manuskript fiorm of this article was Sales and operations planning in the process industry.Funding agencies: Swedish Foundation for Strategic Research (SSF)

Safety stock calculations are difficult for products with intermittent demand, long production lead times, and high monetary values. Theoretically, forecasts can be used to reduce the need for safety stocks. A high precision forecast minimizes the need for safety stock and forecast evaluation measurements can be used to calculate the safety stock level. However, a more realistic determination of safety stock levels can he obtained by simulation. In this paper, simulation is used to model and experiment on a case with three end products in order to determine the relationship between safety stock levels and service levels. Also, a comparison is made with theoretically calculated safety stocks to see how well basic theoretical models for safety stock calculations fulfill the requirements of service level. The result is that simulation can provide a much more accurate determination of safety stock levels for intermittent demands than theoretical calculations.

Key performance measures (KPMs) play an important role in the management of supply chains. An important integrator of the supply chain management is Sales and Operations Planning (S&OP) that connects the strategic and operational plans. S&OP usually impacts supply chain performance through the management of resources and customer satisfaction. This paper suggests a new classification for S&OP-related KPMs. The classification follows a typology of decision categories which are based on decoupling points. The typology supports a modularized approach to supply chain design and provides the possibility to select the KPMs according to the decision criteria of each module. The KPMs are further linked to the SCOR performance attributes to provide the link to the companies’ strategic directives and the strategic conflicts which appear in the modules of the typology are discussed. The sustainable KPMs have also been included in order to provide opportunities for improved sustainable performance. The integration of sustainable KPMs helps in creating competitive advantages for companies through development of capabilities which are beneficial but hard to replicate by competitors. The paper ends with an example that illustrates how the classification can be applied to a case company.

Liquid financial markets, such as the options market of the S&P 500 index, create vast amounts of data every day, i.e., so-called intraday data. However, this highly granular data is often reduced to single-time when used to estimate financial quantities. This under-utilization of the data may reduce the quality of the estimates. In this paper, we study the impacts on estimation quality when using intraday data to estimate dividends. The methodology is based on earlier linear regression (ordinary least squares) estimates, which have been adapted to intraday data. Further, the method is also generalized in two aspects. First, the dividends are expressed as present values of future dividends rather than dividend yields. Second, to account for heteroscedasticity, the estimation methodology was formulated as a weighted least squares, where the weights are determined from the market data. This method is compared with a traditional method on out-of-sample S&P 500 European options market data. The results show that estimations based on intraday data have, with statistical significance, a higher quality than the corresponding single-times estimates. Additionally, the two generalizations of the methodology are shown to improve the estimation quality further.

Sequential decision problems under uncertainty are commonly studied with stochastic programing. An important modeling choice is the number of stages. More stages allow additional information to be captured, but is associated with a coarser representation of uncertainty may worsen solution quality. In this paper, we study this trade-off, with the objective to advance the understanding of how the number of stages affect solution quality in stochastic programing. We show: (i) how the optimistic bounds from stochastic programing gradually suggest improved performance with more stages, while the real solution quality simultaneously deteriorates; and (ii) that real performance can be improved by adding stages, but only up to some point, after which more stages are detrimental. Further, we highlight the importance of understanding what creates the value of more stages in the problem of interest, and particularly if this can be captured in models with few stages. The numerical experiments are based on the classic portfolio choice problem of an investor with constant relative risk aversion preferences, maximizing the expected utility of terminal wealth. We study instances with proportional transaction costs and predictability in returns, which takes this problem into an inherently multi-stage nature., Funding Agencies|Swedens Innovation Agency [2019-04798]; University of Chicago Booth School of BusinessUniversity of Chicago

In this paper we attempt to derive properties of the distribution of the net present value NPV, when the un-derlying cash flow is affected by stochastic disturbances in the form of a random walk process, the disturbances thus jumping continuously between each of two values. A leverage is introduced, affecting the size of each jump in relation to time.A given time period is split into a number of sub-periods of equal length. During each sub-period, a fraction of altogether one monetary unit is transferred. This cash flow is subject to the random walk, and is discounted by a given constant discount rate. We study consequences on the distribution of the net present value as the number of sub-periods increases beyond all bounds.Two different processes are studied, which turn out to have rather different properties. In the first, Case A, the two levels between each jump, are chosen as each others negative, and in the second, Case B, except for a timing factor, as each others inverse. Among other consequences, it is shown that the probability distribution of the NPV in Case A is close to, but different from, a lognormal distribution, and that in Case B, the NPV indeed has a lognormal distribution, but lies stable at a constant value. Also is shown that in Case A, the leverage must be at least 1/2 for a limiting distribution to exist, and in Case B at least unity. For leverage values above these values, respectively, the random walk will not affect NPV, and the net present value becomes deterministic.

This paper studies the channel choice problem in an e-retailing market when a reseller and an agency seller are experimenting with a new format, i.e., a hybrid retailing strategy. Under this strategy, the reseller not only sells products to consumers directly, but also expands the market in collaboration with the agency seller who operates a platform. However, the motivation and effectiveness of this strategy are not clear. Therefore, we develop game-theoretic models to investigate retail and wholesale prices, and the equilibrium channel choice. First, we find that the hybrid retailing strategy results in a higher retail price for the reseller; in contrast, the agency seller prefers to reduce the retail price when the fraction of market demand through the hybrid retailing channel is large. Second, we find that the hybrid retailing strategy can benefit all stakeholders when the fraction of market demand through the hybrid retailing channel is small. Third, under a dual retailing channel with price competition, a reseller and an agency seller are still willing to collaborate through a hybrid retailing strategy, because the cost of market expansion caused by this strategy is partly transferred to the manufacturer. Our results can provide meaningful decision support and operational rules for stakeholders to make strategic retail decisions., Funding Agencies|National Social Science Foundation of China [18ZDA060]

MRP theory is a theoretical body treating production-inventory systems, in which produced items are made up of sets of produced or purchased sub-items, required to be available a lead-time before each product is completed. The hierarchical dependence between items is captured using input matrices from input-output-analysis, the necessary advanced timing by employing Laplace transform methodology, and the economic consequences by applying the net present value. Little attention has hitherto been given to aspects of a non-empty initial state, e.g. an initial inventory position. Since such states are common in industry, there is a strong need for this theory to include such aspects, in order to gain further practical acceptance. In this paper, theoretical consequences from having a non-empty initial state are investigated. A method for finding the Lot-for-Lot solution is developed using the concept of a truncated monotonically non-decreasing time function, generalising the approach of the generalised Leontief inverse and instrumental for designing plans meeting the necessary inner-corner requirement for optimality. Also the definition of inventory-related costs needs a modification for this concept to be consistent with NPV. These findings are applied in an extensive numerical example. Immediate future research concerns investigating principles for the optimal removal of initial backlogs.

Companies align lean production and sustainability differently depending on organization model. Lean provides social foundation for sustainability and makes it possible to implement sustainability, and integrate lean and sustainability. The work presented here maps a current value stream with measures from different methodologies presented in the literature. The objective of this paper is to integrate sustainability measures with a traditional value stream mapping. Economic, environmental, and societal metrics are presented. The result indicates that the interest of the different metrics depends on the role within the organization.

Core acquisition is essential for the success of remanufacturing business. To describe the current status of the quantitative research in Core Acquisition Management and to indicate possible future research directions, a literature review is conducted in this paper about the quantitative modeling in Core Acquisition Management research area. The activities included in Core Acquisition Management are categorized into topics such as acquisition control, forecasting return, return strategies, quality classification and reverse channel design. While most of the studies focus on acquisition control, studies on return strategies and return forecast are relatively limited. Furthermore, this paper analyzes the research papers according to the key assumptions such as, hybrid/non-hybrid remanufacturing systems, acquisition functions, quality classification methods and perfect/imperfect substitutions. In conclusion, studies based on the assumptions of non-hybrid remanufacturing systems and imperfect substitution should gain more attentions, since these situations frequently occur in practice but are less investigated in the existing literature. In addition, empirical validation of the various forms of the acquisition function (relations between acquisition incentives and acquisition volume) should be important for further investigations., At the time for thesis presentation publication was in status: Manuscript

In this paper we attempt to provide a partial answer to the question of why energy is a scarce resource. Scarcity is a fundamental concept in the science of economics. If resources, goods or services were not in scarce supply, we need not economise when utilising them. Indeed, free commodities we need not pay for, their prices are zero, we attach no economic value to them, and their supply is in abundance - at least beyond the point at which our needs and wants are satisfied. However, energy is regarded as a scarce resource, although energy - as such - is not scarce. To describe energy as a useful and therefore a valuable quantity, to which a price may be attached, energy will thus have to be characterised in further dimensions than energy content alone. Apart from quantity, there is a need for a uniform qualitative measure of energy. The obvious field to revert to for such considerations is thermodynamics, which offers a method for defining a uniform measure for the qualitative content of energy, namely exergy. Although exergy is defined from purely physical properties, it is shown to have an important role to play when comparing the economic value of energy in different forms. In particular, this paper will focus on the economic value of heat, especially heat delivered through a district heating system. The concept of exergy is defined from maximising a work output reversibly taking an infinite time. However, for processes to run within finite horizons, entropy must be generated. This leads us to add finite time considerations from examining consequences from the assumed availability of so-called endo-reversible processes. In a small case example we show that heat appears to be overpriced compared to electricity from an exergetic point of view and that this is even more pronounced adopting finite time considerations. (C) 2015 Elsevier B.V. All rights reserved.

Sequential decision problems under uncertainty are commonly studied with stochastic programing. An important modeling choice is the number of stages. More stages allow additional information to be captured, but is associated with a coarser representation of uncertainty may worsen solution quality. In this paper, we study this trade-off, with the objective to advance the understanding of how the number of stages affect solution quality in stochastic programing. We show: (i) how the optimistic bounds from stochastic programing gradually suggest improved performance with more stages, while the real solution quality simultaneously deteriorates; and (ii) that real performance can be improved by adding stages, but only up to some point, after which more stages are detrimental. Further, we highlight the importance of understanding what creates the value of more stages in the problem of interest, and particularly if this can be captured in models with few stages. The numerical experiments are based on the classic portfolio choice problem of an investor with constant relative risk aversion preferences, maximizing the expected utility of terminal wealth. We study instances with proportional transaction costs and predictability in returns, which takes this problem into an inherently multi-stage nature., Funding Agencies|Swedens Innovation Agency [2019-04798]; University of Chicago Booth School of BusinessUniversity of Chicago

In light of a circular economy, to encourage core returns, the remanufacturer charges a deposit and refund it to the customer based on quality inspection of cores. Generally, two types of classification errors exist and interact with each other during the inspection process: either low-quality cores are sorted as remanufacturable, or high-quality cores are sorted as non-remanufacturable. The remanufacturer needs to choose refund policies and determine a reasonable deposit value, considering customers potential responses. This paper firstly develops analytical solutions for these issues within a game theory framework. The effect of inspection information transparency is evaluated by comparing two settings: the information of inspection errors is available to customers or not. The study results show the advantage of inspection information transparency from the remanufacturers perspective. The analysis indicates the importance of avoiding overestimating customers payoff of products and the significance of inspection accuracy. The study also highlights that the salvage value of different cores significantly influences the remanufacturers profits, and the improvement of inspection accuracy does not necessarily reduce the customers return of low-quality cores.

MRP theory concerns production-inventory systems, in which produced items are made up of sets of sub-items, either produced or purchased (imported into the system) and required to be available a lead-time before the product is completed. The hierarchical dependence of relations between items is captured by the use of input matrices from Input-Output Analysis, the necessary advanced timing by applying the methodology of Laplace transforms, and the production-economic consequences by the net present value (NPV). This theory has been developed for about 40 years, but little attention has been given to transient aspects, i.e. when there happens to be an initial available inventory of items usable in future production. In this paper, we attempt to highlight the theoretical consequences from having a positive initial available inventory.

In the aftermath of large-scale natural disasters, supply shortage and inequitable distribution cause various losses, hindering humanitarian supply chains? performance. The optimal decisions are difficult due to the complexity arising from the multi-period post-disaster consideration, uncertainty of supplies, hierarchal decision levels and conflicting objectives in sustainable humanitarian supply chains (SHSCs). This paper formulates the problem as a fuzzy tri-objective bi-level integer programming model to minimize the unmet demand rate, potential environmental risks, emergency costs on the upper level of decision hierarchy and maximize survivors? perceived satisfaction on the lower level of decision hierarchy. A hybrid global criterion method is devised to incorporate a primal-dual algorithm, expected value and branch-and-bound approach in solving the model. A case study using data from the Wenchuan earthquake is presented to evaluate the proposed model. Study results indicate that the hybrid global criterion method guides an optimal strategy for such a complex problem within a reasonable computational time. More attention should be attached to the environmental and economic sustainability aspects in SHSCs after golden rescue stage. The proposed bi-level optimization model has the advantages of reducing the total unmet demand rate, total potential environmental risks and total emergency costs. If the decision-agents with higher authorities act as the leaders with dominant power in SHSCs, the optimal decisions, respectively taking hierarchical and horizontal relationships into account would result in equal performance., Funding Agencies|National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [71904021]; Social Science Planning Project of Chongqing [2019QNGL27]; Chunhui Plan of the Ministry of Education of the Peoples Republic of China [CQ2019001]; Natural Science Foundation of Chongqing, ChinaNatural Science Foundation of Chongqing [cstc2020jcyj-msxmX0164]; Project of Science and Technology Research Program of Chongqing Municipal Education Commission of China [KJQN201900830]; Key Project of Special Research regarding Response to Major Public Health Emergency of Chongqing Technology and Business University [ctbuyqzx01]; China Scholarship CouncilChina Scholarship Council [202008500051]; Scientific Research Startup Foundation for Introduction of Advanced Talents of Chongqing Technology and Business University [1955011]; Research Project of Chongqing Technology and Business University [1951025]; MOE Layout Foundation of Humanities and Social Sciences [20YJA630079]; International Science and Technology Innovation Cooperation Project of Sichuan Provice [20GJHZ0039]

With the substantial size of the interest rate markets, the importance of accurate pricing, risk measurement and performance attribution can not be understated. However, the models used on the markets often have underlying issues with capturing the market's fundamental behavior. With this thesis, we aim to improve the pricing, risk measurement, and performance attribution of interest rate swap portfolios. The paper is divided into six main parts, by subject, to aid in achieving these goals. To begin with, we validate all cash flows with SEB to increase the validity of the results. Next, we implement an optimization-based model developed by Jörgen Blomvall to estimate multiple yield curves. By considering innovations of the daily in-sample curves, risk factors are computed with principal component analysis. These risk factors are then used to simulate one-day and ten-day ahead scenarios for the multiple yield curves using a Monte Carlo method. Given these simulated scenarios, risk measures are then computed. When backtested, these risk measurements give an indication on the overall accuracy of the methodology, including the estimated curves, the derived risk factors, and the simulation methodology. Along with the simulation, on each out-of-sample day, monetary performance attribution for the portfolios is also performed. The performance attribution indicates what drives the value change in the portfolio. This can be used in order to evaluate the estimated yield curves and derived risk factors. The risk measurement and performance attribution is done for three different portfolios of interest rate swaps on the EUR, USD, and SEK markets. However, the risk factors are only estimated for EUR data and used for all portfolios. The main difference to previous work in this area is that, for all implementations, a multiple yield curve environment is studied. Different PCA algorithms are evaluated to increase the precision and speed of the risk factor calculation. Mean rever

In this paper we compare the two basic risk preference measures suggested independently by John W. Pratt (1964) and Kenneth J. Arrow (1965) as to their impact on simple production decisions with uncertain economic outcomes. We develop a further related concept by introducing a risk aversion leverage measuring the dependence of absolute risk aversion on wealth. We also discover a remarkable approximate relation between risk aversion measures of different leverages making the corresponding risk preference functions similar and leading to a method for estimating different Certainty Monetary Equivalents using zero-leverage expressions. We concentrate on three simple cases of production decisions of the Newsboy type.

In order to eliminate the negative effects of customer strategic behaviour, retailers often adopt quick response or value-added services. While in a luxury market with conspicuous customers, retailers pricing decisions of these two strategies become more complicated. This paper studies a supply chain with a retailer serving a mixture of conspicuous and ordinary strategic customers. We develop three models so that the retailer provides (i) neither quick response nor value-added services; (ii) only quick response; (iii) only value-added services. Subsequently, we analyse the impacts of conspicuous customers on quick response and value-added services by pricing and strategy comparisons. The model further extends to the situation including both strategies. The results show that, firstly, when the proportion is less than a threshold, the retailer should adopt a low price strategy, and vice versa. Besides, the quick response could induce the retailer to adopt high price while value-added services inhibit it. Secondly, the customer conspicuous behaviour can motivate retailers to provide quick response and inhibit their value-added services. Finally, by observing the retailers decisions when they can adopt two strategies simultaneously, we find that the existence of quick response can amplify the benefits of value-added services., Funding Agencies|National Natural Science Foundation of ChinaNational Natural Science Foundation of China [71672121]; Independent Innovation Foundation of Tianjin University [2019XSC-0001]

Determining the economic lot size has always represented one of the most important issues in production planning. This problem has long attracted the attention of researchers, and several models have been developed to meet requirements at minimum cost. In this paper we explore and discuss the evolution of these models during one hundred years of history, starting from the basic model developed by Harris in 1913, up to today. Following Harriss work, a number of researchers have devised extensions that incorporate additional considerations. The evolution of EOQ theory strongly reflects the development of industrial systems over the past century. Here we outline all the research areas faced in the past by conducting a holistic analysis of 219 selected journal papers and trying to give a comprehensive view of past work on the EOQ problem. Finally, a new research agenda is proposed and discussed.

To save energy and reduce costs we suggest production planning to consider issues with clear and large impact on both usage and costs of energy. This paper investigates how the energy system interacts with the production processes early in the value chain at a steel company. A case study at one of the company’s production facilities reveals promising opportunities to achieve increased energy efficiency by considering an energy‐related approach in planning of the continuous slab furnaces and the hot rolling processes. Analysis shows that energy can be saved and costs reduced through an alternative planning approach without taking any noteworthy investment cost. Improved communication within the different parts of the organization plays also a significant part in actualizing the managerial opportunities located. Real company data provided from the case company SSAB is used and analyzed. This paper contributes with a model used for analytical calculations on how market conditions could motivate a company to select different planning approaches. This by choosing a primary and secondary slab furnace based on their energy characteristics. As such, when the opportunities are beneficial enough, the impact of energy issues on production and supply chain planning should not be neglected.

Public procurement is widely used in order to incorporate competition into public services. Competition in procurement often leads to efficiency but the process can also raise some problems. While providing the procurement documents you do not know who will be your upcoming partner. Another aspect is how flexibility can be managed in contract design while maintaining a high service quality. The aim of this study is twofold. Firstly, the aim is to investigate how flexibility has been expressed and historically described in bus tendering documents. Secondly, to explore how the actors define or describe flexibility and its importance in tendering. Data was collected from ten years of tendering documents in the bus sector in Sweden and from interviews and a workshop. The results showed that flexibility in tendering documents has been and still is low for the operators. However, the actors wish for more flexibility and new forms of contracts can make it easier to include higher degrees of flexibility in future contracts. The paper contributes to the ongoing discussion about how to design contracts and to manage flexibility. The study has potential to create knowledge and contribute to better decision making for future procurement of bus transport., Funding Agencies|Vinnova - Swedens Innovation Agency, Sweden [2017-03275]; K2 - The Swedish Knowledge Centre for Public Transport, Lund, Sweden

In this paper, we propose an approach to construct an analytical approximation of the zero-variance importance sampling distribution. We show specifically how this can be designed for the classic intertemporal portfolio choice problem with proportional transaction costs and constant relative risk aversion preferences. We compare the method to standard variance reduction techniques in single-period optimization and multi-stage stochastic programming formulations of the problem. The numerical experiments show that the method produces significant improvements in solution quality. In the single-period setting, the number of scenarios can be reduced by a factor of 400 with maintained solution quality compared to the best standard method; Latin hypercube sampling. Using importance sampling in multi-stage formulations, the gaps between lower and upper bound estimates are reduced by a factor of 26-500 with maintained scenario tree size. On a higher level, we consider analytical approximations of the zero-variance importance sampling distribution to be a promising method to improve solution quality in stochastic optimization. (C) 2019 Elsevier B.V. All rights reserved.

The overall purpose of the PhD project is to develop a framework for making optimal decisions on the equity derivatives markets. Making optimal decisions refers e.g. to how to optimally hedge an options portfolio or how to make optimal investments on the equity derivatives markets. The framework for making optimal decisions will be based on stochastic programming (SP) models, which means that it is necessary to generate high-quality scenarios of market prices at some future date as input to the models. This leads to a situation where the traditional methods, described in the literature, for modeling market prices do not provide scenarios of sufficiently high quality as input to the SP model. Thus, the main focus of this thesis is to develop methods that improve the estimation of option implied surfaces from a cross-section of observed option prices compared to the traditional methods described in the literature. The estimation is complicated by the fact that observed option prices contain a lot of noise and possibly also arbitrage. This means that in order to be able to estimate option implied surfaces which are free of arbitrage and of high quality, the noise in the input data has to be adequately handled by the estimation method. The first two papers of this thesis develop a non-parametric optimization based framework for the estimation of high-quality arbitrage-free option implied surfaces. The first paper covers the estimation of the risk-neutral density (RND) surface and the second paper the local volatility surface. Both methods provide smooth and realistic surfaces for market data. Estimation of the RND is a convex optimization problem, but the result is sensitive to the parameter choice. When the local volatility is estimated the parameter choice is much easier but the optimization problem is non-convex, even though the algorithm does not seem to get stuck in local optima. The SP models used to make optimal decisions on the equity derivatives markets also ne, Det övergripande syftet med doktorandprojektet är att utveckla ett ramverk för att fatta optimala beslut på aktiederivatmarknaderna. Att fatta optimala beslut syftar till exempel på hur man optimalt ska hedga en optionsportfölj, eller hur man ska göra optimala investeringar på aktiederivatmarknaderna. Ramverket för att fatta optimala beslut kommer att baseras på stokastisk programmerings-modeller (SP-modeller), vilket betyder att det är nödvändigt att generera högkvalitativa scenarier för marknadspriser för en framtida tidpunkt som indata till SP-modellen. Detta leder till en situation där de traditionella metoderna, som finns beskrivna i litteraturen, för att modellera marknadspriser inte ger scenarier av tillräckligt hög kvalitet för att fungera som indata till SP-modellen. Följaktligen är huvudfokus för denna avhandling att utveckla metoder som, jämfört med de traditionella metoderna som finns beskrivna i litteraturen, förbättrar estimeringen av ytor som impliceras av en given mängd observerade optionspriser. Estimeringen kompliceras av att observerade optionspriser innehåller mycket brus och möjligen också arbitrage. Det betyder att för att kunna estimera optionsimplicerade ytor som är arbitragefria och av hög kvalitet, så behöver estimeringsmetoden hantera bruset i indata på ett adekvat sätt. De första två artiklarna i avhandlingen utvecklar ett icke-parametriskt optimeringsbaserat ramverk för estimering av högkvalitativa och arbitragefria options-implicerade ytor. Den första artikeln behandlar estimeringen av den risk-neutrala täthetsytan (RND-ytan) och den andra artikeln estimeringen av den lokala volatilitetsytan. Båda metoderna ger upphov till jämna och realistiska ytor för marknadsdata. Estimeringen av RND-ytan är ett konvext optimeringsproblem men resultatet är känsligt för valet av parametrar. När den lokala volatilitetsytan estimeras är parametervalet mycket enklare men optimeringsproblemet är icke-konvext, även om algoritmen inte verkar fastna i lokala