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  • 1. Baron, Opher
    et al.
    Berman, Oded
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Chinese Academy of Sciences, China.
    Bargaining within the Supply Chain and Its Implications in an Industry2016In: Decision Sciences, ISSN 0011-7315, E-ISSN 1540-5915, Vol. 47, no 2, p. 193-218Article in journal (Refereed)
    Abstract [en]

    Our main objective is to investigate the influence of the bargaining power within a chain on its industry. As a building block, we first discuss the implications of bargaining within a single chain by considering an asymmetric Nash bargaining over the wholesale price (BW). We show that both Manufacturer Stackelberg (MS) and vertical integration (VI) strategies are special cases of the BW contract. We then develop the Nash equilibrium in an industry with two supply chains that use BW. We identify the profit-maximizing (coordinating) bargaining power within this industry. We show that when a chain is not monopolistic, VI does not coordinate the chain and that the MS contract, where the manufacturer has all the bargaining power, is coordinating when competition is intense. We find that the main determinant of the equilibrium in mature industries is to respond well to the actions of the competing chain rather than to directly maximize the profit of each chain. That is, the equilibrium does not necessarily maximize the profit of the entire industry. While a coordination of the industry could then increase the profitability of both chains, such a coordination is likely against antitrust law. Moreover, if one chain cannot change its actions, the other chain may unilaterally improve its profitability by deviating from the equilibrium. Our results lead to several predictions supported by empirical findings, such as that in competitive industries chains will work close to the MS contract.

  • 2. Chen, Shuzhen
    et al.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    A revealed damage cost method to evaluate environmental performance of production: Evaluating treatment efficiency of emissions and scaling treatment cost bounds2018In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 194, p. 101-111Article in journal (Refereed)
    Abstract [en]

    Environmental performance indices are in great demand for environmental policy support. This paper addresses the particular problem of evaluating environmental performance of industries and identifying the worst performed industries that should be strictly regulated. Specifically, an input-output analysis method is developed to disentangle the environmental pressures of production processes; treatment costs are introduced to reveal the damage costs of relevant pressures which is integrated in the DEA based index to restrict the weight assignment. The proposed method is advantageous in data requirements as well as definition of process boundaries and can alleviate the underestimation of damages from predominant pressures. The results of evaluation provide a more reliable reference to industrial regulation.

  • 3. Chen, Shuzhen
    et al.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Adapting ecological risk valuation for natural resource damage assessment in water pollution2018In: Environmental Research, ISSN 0013-9351, E-ISSN 1096-0953, Vol. 164, p. 85-92Article in journal (Refereed)
    Abstract [en]

    Ecological risk assessment can address requirements of natural resource damage assessment by quantifying the magnitude of possible damages to the ecosystem. This paper investigates an approach to assess water damages from pollution incident on the basis of concentrations of contaminants. The baseline of water pollution is determined with not-to-exceed concentration of contaminants required by water quality standards. The values of damage cost to water quality are estimated through sewage treatment cost. To get a reliable estimate of treatment cost, DEA is employed to classify samples of sewage plants based on their efficiency of sewage treatment. And exponential fitting is adopted to determine the relation between treatment cost and the decrease of COCs. The range of damage costs is determined through the fitting curves respectively based on efficient and inefficient samples.

  • 4. Chen, Shuzhen
    et al.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Connectivity, Netting, and Systemic Risk of Payment Systems2019In: IEEE Systems Journal, ISSN 1932-8184, E-ISSN 1937-9234, Vol. 13, no 2, p. 1658-1668Article in journal (Refereed)
    Abstract [en]

    The stability of payment system is of vital importance to the credit market as well as the economic development. Most researches focus on the effect of system connectivity on systemic risk and demonstrate that connectivity provides both risk-spread channel and risk-sharing mechanism. But the management of systemic risk is quite different in real-time gross settlement system and net settlement system. We provide an integrated analysis of the effect of connectivity and netting on systemic risk in payment systems by considering more detailed network structures of pure creditors and pure debtors. We show that the effect of netting is partly due to the change of network connectivity, which severs the contagion channel of shocks. Moreover, netting can lower the actual magnitude of the shock from the beginning by reducing source bank's debt.

  • 5. Ding, Shuai
    et al.
    Li, Yeqing
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Zhang, Youtao
    Yang, Shanlin
    Time-aware cloud service recommendation using similarity-enhanced collaborative filtering and ARIMA model2018In: Decision Support Systems, ISSN 0167-9236, E-ISSN 1873-5797, Vol. 107, p. 103-115Article in journal (Refereed)
    Abstract [en]

    The quality of service (QoS) of cloud services change frequently over time. Existing service recommendation approaches either ignore this property or address it inadequately, leading to ineffective service recommendation. In this paper, we propose a time-aware service recommendation (taSR) approach to address this issue. We first develop a novel similarity-enhanced collaborative filtering (CF) approach to capture the time feature of user similarity and address the data sparsity in the existing PITs (point in time). We then apply autoregressive integrated moving average model (ARIMA) to predict the QoS values in the future PIT under QoS instantaneity. We evaluate the proposed approach and compare it to the state-of-the-art. Our experimental results show that taSR achieves significant performance improvements over existing approaches.

  • 6. Ding, Shuai
    et al.
    Wang, Zeyuan
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Chinese Academy of Sciences, China.
    Olson, David L.
    Utilizing customer satisfaction in ranking prediction for personalized cloud service selection2017In: Decision Support Systems, ISSN 0167-9236, E-ISSN 1873-5797, Vol. 93, p. 1-10Article in journal (Refereed)
    Abstract [en]

    With the rapid development of cloud computing, cloud service has become an indispensable component of modern information systems where quality of service (QoS) has a direct impact on the system's performance and stability. While scholars have concentrated their efforts on the monitoring and evaluation of QoS in cloud computing, other service selection characteristics have been neglected, such as the scarcity of evaluation data and various customer needs. In this paper, we present a ranking-oriented prediction method that will assist in the process of discovering the cloud service candidates that have the highest customer satisfaction. This approach encompasses two basic functions: ranking similarity estimation and cloud service ranldng prediction that takes into account customer's preference and expectation. The comparative experimental results show that the proposed method outperforms other competing methods.

  • 7. Dong, Junfeng
    et al.
    Wu, Desheng Dash
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Chinese Academy of Sciences, China.
    Two-period pricing and quick response with strategic customers2019In: International Journal of Production Economics, ISSN 0925-5273, E-ISSN 1873-7579, Vol. 215, p. 165-173Article in journal (Refereed)
    Abstract [en]

    This research examines the impact of the strategic customer behavior in two-period pricing and the inventory decisions in a quick response system. A model with a differentiated value period of product is developed when customers are strategic and heterogeneous. Interestingly, the unique equilibrium is proven to exist if and only if the degree of customer strategic behavior is sufficiently high. Otherwise, the dynamic pricing strategy in one selling season is not a suitable choice for a firm. Moreover, the impact of strategic consumers on pricing and inventory strategies is investigated in the case where the clientele's taste for product value follows a uniform distribution. Surprisingly, contrary to previous studies, we found that strategic consumers may yield more revenues in specific scenarios. An extended analysis on Beta distribution is also presented, showing that there is greater chance to obtain the highest profit in the supply chain when all customers are strategic and if more people prefer low-value products.

  • 8. Hnaien, Faicel
    et al.
    Dolgui, Alexandre
    Wu, Desheng Dash
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Single-period inventory model for one-level assembly system with stochastic lead times and demand2016In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 54, no 1, p. 186-203Article in journal (Refereed)
    Abstract [en]

    Replenishment planning of an assembly system with one type of finished product assembled from diverse external suppliers to satisfy finished product demand. It is supposed that the component lead times and finished product demand are random discrete variables. The assembly company must determine what are the best quantities of components and when is the right time to order. The objective is to minimise the total cost which is composed of holding component costs, tardiness penalties, lost sales and surplus item costs for finished products. A single-period analytical model is proposed. Several properties of the objective function are proven. They are used to develop a Branch and Bound algorithm. Numerical tests for the algorithm are presented. Five heuristics based on Newsvendor model for lead time and demand are proposed and compared with the Branch and Bound algorithm. These tests show that the suggested Branch and Bound algorithm can solve large size problems within a short time. The proposed heuristics but one are not competitive with the Branch and Bound algorithm. The truncated version of Branch and Bound gives better results. The model suggested is better adapted to actual contract assembler environments, more realistic and can better approximate real-life industrial situations. The proposed exact algorithm provides optimal solutions for all discrete distributions of probabilities of lead times and demand. A new general approach to design such discrete optimisation algorithms is presented.

  • 9.
    Luo, Cuicui
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School.
    Wu, Dexiang
    Stockholm University, Faculty of Social Sciences, Stockholm Business School.
    A deep learning approach for credit scoring using credit default swaps2017In: Engineering applications of artificial intelligence, ISSN 0952-1976, E-ISSN 1873-6769, Vol. 65, p. 465-470Article in journal (Refereed)
    Abstract [en]

    After 2007-2008 crisis, it is clear that corporate credit scoring is becoming a key role in credit risk management. In this paper, we investigate the performances of credit scoring models applied to CDS data sets. The classification performance of deep learning algorithm such as deep belief networks with Restricted Boltzmann Machines are evaluated and compared with some popular credit scoring models such as logistic regression, multi-layer perceptron and support vector machine. The performance is assessed using the classification accuracy and the area under the receiver operating characteristic curve. It is found that DBN yields the best performance.

  • 10. Pan, Yuchen
    et al.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Luo, Cuicui
    Stockholm University, Faculty of Social Sciences, Stockholm Business School.
    Dolgui, Alexandre
    User activity measurement in rating-based online-to-offline (O2O) service recommendation2019In: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291, Vol. 479, p. 180-196Article in journal (Refereed)
    Abstract [en]

    The increasing popularity of O2O service make more and more people begin seeking and booking services online. After that, they experience the services in brick-and-mortar stores. This new business model has marketing potential and offer various opportunities to different industries. Consequently, various O2O services starting to appear, which results in difficult service selections for customers. Therefore, in this paper, we proposed a novel rating-based O2O service recommendation model considering user activity. In this method, the traditional similarity estimations are substituted by user activity which can better reflect the differentiations of customers' behavioral characteristics. Therefore, recommendations are more accurate. The experimental results show that proposed method outperforms rating-based methods, including widely used collaborative filtering methods and state-of-the-art matrix methods. In addition, we find the optimal parameter values of our model, and explore the influence of Top-k on rating-based recommendation.

  • 11. Pan, Yuchen
    et al.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Olson, David L.
    Online to offline (O2O) service recommendation method based on multi -dimensional similarity measurement2017In: Decision Support Systems, ISSN 0167-9236, E-ISSN 1873-5797, Vol. 103, p. 1-8Article in journal (Refereed)
    Abstract [en]

    With the rapid development of information technology, consumers are able to search for and buy services or products online, and then consume them in an offline store. This emerging ecommerce model is called online to offline (O2O) service, which has attracted business and academic attention. The large number of O2O services on the Internet creates a scalability problem, creating massive but highly sparse matrices relating customers to items purchased. In this paper, we proposed a novel O2O service recommendation method based on multidimensional similarity measurements. This approach encompasses three similarity measures: collaborative similarity, preference similarity and trajectory similarity. Experimental results show that a combination of multiple similarity measures performs better than any one single similarity measure. We also find that trajectory similarity performs better than the rating-based similarity metrics (collaborative similarity and preference similarity) in sparse matrices.

  • 12. Ren, Rui
    et al.
    Wu, Desheng Dash
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Science, China.
    Liu, Tianxiang
    Forecasting Stock Market Movement Direction Using Sentiment Analysis and Support Vector Machine2019In: IEEE Systems Journal, ISSN 1932-8184, E-ISSN 1937-9234, Vol. 13, no 1, p. 760-770Article in journal (Refereed)
    Abstract [en]

    Investor sentiment plays an important role on the stock market. User-generated textual content on the Internet provides a precious source to reflect investor psychology and predicts stock prices as a complement to stock market data. This paper integrates sentiment analysis into a machine learning method based on support vector machine. Furthermore, we take the day-of-week effect into consideration and construct more reliable and realistic sentiment indexes. Empirical results illustrate that the accuracy of forecasting the movement direction of the SSE 50 Index can be as high as 89.93% with a rise of 18.6% after introducing sentiment variables. And, meanwhile, our model helps investors make wiser decisions. These findings also imply that sentiment probably contains precious information about the asset fundamental values and can be regarded as one of the leading indicators of the stock market.

  • 13. Shah, Akber Aman
    et al.
    Wu, Desheng Dash
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Chinese Academy of Sciences, China.
    Korotkov, Vladimir
    Jabeen, Gul
    Do Commercial Banks Benefited From the Belt and Road Initiative? A Three-Stage DEA-Tobit-NN Analysis2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 37936-37949Article in journal (Refereed)
    Abstract [en]

    The data envelopment analysis (DEA) treats decision-making units (DMUs) as black boxes: there is an unknown internal structure and transformation mechanism of input to output. Two-stage models have been proposed to resolve this problem by considering the internal structure of DMUs. However, each DMU has a different structure, and in two-stage models, the poor estimation of sub-models causes conflicts in the intermediate layer. Therefore, it is necessary to use additional tools to extract insight into opportunities to enhance the performance of DMUs. This paper presents a three-stage model employing DEA to evaluate efficiency, a Tobit regression model to identify the determinants, and a neural network (NN) to improve those determinants. Improvement in the determinants of a DMU enhances its efficiency. The developed model is applied to the empirical dataset of commercial banks from the countries that have joined the belt and road initiative (BRI), grouping them based on their economist intelligence unit (EIU) rating. The results provide valuable information on the efficiency enhancement process for banks to benefit from the BRI.

  • 14. Shah, Akber Aman
    et al.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Science, China.
    Korotkov, Vladmir
    Are Sustainable Banks Efficient and Productive? A Data Envelopment Analysis and the Malmquist Productivity Index Analysis2019In: Sustainability, ISSN 2071-1050, E-ISSN 2071-1050, Vol. 11, no 8, article id 2398Article in journal (Refereed)
    Abstract [en]

    Corporate sustainability is the integration of environmental protection, financial benefit, and social responsibility into management and business operations. There is insufficient evidence for its relationship with operating performance and productivity. Furthermore, it becomes doubtful when investors standardize corporate sustainable strategies. This study evaluates the performance and productivity of sustainable banks, exploring practical issues by providing supporting evidence. A two-stage performance evaluation is employed with the integration of data envelopment analysis (DEA) and Malmquist productivity index (MPI) to evaluate sustainable bank performance and productivity for 9 years (2010-2018) in comparison with non-sustainable banks. DEA is used to define dynamic benchmarking, and MPI builds on time-series analysis. The results of our study reveal that sustainable banks are more efficient and productive. The productivity of sustainable banks and non-sustainable banks was influenced by external and internal factors, respectively.

  • 15. Tang, Zijie
    et al.
    Wu, Desheng Dash
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, People´s Republic of China.
    Dolgui, Alexandre
    Option contracts for online celebrities as retailers in supply chains2019In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588XArticle in journal (Refereed)
    Abstract [en]

    The online celebrity economy, also called the internet celebrity economy, is growing rapidly in China. Celebrity retailers are usually demand sensitive and capital constrained. The capital constraints along with information asymmetry often render supply chains inefficient when manufacturers are producing at non-optimal levels. Few studies have shed light on the online celebrity supply chain, especially with respect to options. In this study, we examine how option contracts can coordinate supply chains. We find that a capital-constrained retailer can achieve more profitable orders when given an option. The manufacturer - without the full information of market demand - also benefits from offering an option to the retailer. Our numerical case shows that the options contract generates different payoffs depending on the capital of the retailer.

  • 16.
    Tao, Liangyan
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Nanjing University of Aeronautics and Astronautics, China.
    Wu, Desheng Dash
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Liu, Sifeng
    Dolgui, Alexandre
    Optimal due date quoting for a risk-averse decision-maker under CVaR2018In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 56, no 5, p. 1934-1959Article in journal (Refereed)
    Abstract [en]

    This study investigates a due date quoting problem for a project with stochastic duration, taking the decision-maker's risk attitude into consideration. The project profit is defined as the difference between the price and the cost that is comprised of production cost and earliness-tardiness penalties. In this situation, the due date determination has to be modelled as a stochastic optimisation due to stochastic duration. Conditional value at risk is thus employed as a performance measure to describe the decision-maker's risk attitude. In fixed price contract, when the unit production cost is not smaller than the unit penalty on earliness, the optimal due date increases with the increase of the degree of a decision-maker's risk aversion, the unit penalty on delay, and the decrease of the unit penalty on earliness. Besides, when the price is proportional to the due date and the slope is no bigger than the unit penalty on tardiness, the optimal due date is smaller than the result in fixed price. This is because high price for a short due date encourages a decision-maker to quote a small due date. Further, we compare the optimal due date in different parameter setting where the penalty coefficient of earliness is negative or zero, which means there is reward or no penalty on earliness, respectively. Finally, a case study is conducted to validate the effectiveness and efficiency of the proposed model.

  • 17.
    Tao, Liangyan
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Nanjing University of Aeronautics and Astronautics, China.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Economics and Management School of University of Chinese Academy of Sciences, China.
    Liu, Sifeng
    Lambert, James H.
    Schedule risk analysis for new-product development: The GERT method extended by a characteristic function2017In: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 167, p. 464-473Article in journal (Refereed)
    Abstract [en]

    Schedule risk analysis plays a key role in new product development. A typical project-schedule model using the Critical Path Method (CPM) and Program, Evaluation, and Review Technique (PERT) falls short in many practical situations. Instead, a graphical evaluation and review technique (GERT) has been recommended for its ability to address probability branches and loops. This paper introduces a GERT model based on a characteristic function and designs its numerical solution. First, an inversion formula is applied to derive the probability distribution of the completion time of a product development. Second, to address the implications of a due date, a novel measure of schedule risk is introduced to give a view of both loss and probability. Third, an elasticity analysis is used to identify the network parameters that facilitate the control of schedule risk. A case study of new product development in a high-technology enterprise is presented to demonstrate the proposed methods. The approach will be useful in schedule risk analysis across several problem domains including engineering, environment, management, economic development, etc.

  • 18.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Management School of University of Chinese Academy of Sciences, China.
    Pass-through decision analysis in a supply chain2017In: Annals of Operations Research, ISSN 0254-5330, E-ISSN 1572-9338, Vol. 257, no 1-2, p. 297-316Article in journal (Refereed)
    Abstract [en]

    Firms have seen rising costs on one side of the supply chain, and frugal shoppers on the other end in today's business environment. It is possible that increment of rising costs will be passed on to consumers. How will these organizations that are seeking trade promotion decide on passthrough rate in a supply chain? We build a model to analyze both the own-brand and cross-brand cost pass-through incentives of a supply chain selling two products. The key contributions of this paper are as follows. First, we formulate a general pass-through problem as a comparative static of the price equilibrium in a channel duopoly. Our model considers (1) competition intensity, (2) consumer marginal willingness to pay (MWTP), (3) consumer perceivable difference as a threshold level to compare utility from consuming different products, and (4) product quality difference. We show that whether retail cross-brand passthrough is positive, zero or negative depends on whether the hazard rate of consumer MWTP is increasing, affine or decreasing; whether the supplier own-brand and cross-brand pass-through is strictly increasing, affine or decreasing depends on whether the reciprocal of the consumer MWTP hazard rate is strictly increasing, affine or decreasing. Second, we use this model to compare differences in pricing decisions and in profits, resulting from using a centralized versus a decentralized chain in both monopoly and duopoly markets. Our approach allows us to derive pricing implications in both monopoly and duopoly settings.

  • 19.
    Wu, Desheng
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Chen, Shuzhen
    Benchmarking Discount Rate in Natural Resource Damage Assessment with Risk Aversion2017In: Risk Analysis, ISSN 0272-4332, E-ISSN 1539-6924, Vol. 37, no 8, p. 1522-1531Article in journal (Refereed)
    Abstract [en]

    Benchmarking a credible discount rate is of crucial importance in natural resource damage assessment (NRDA) and restoration evaluation. This article integrates a holistic framework of NRDA with prevailing low discount rate theory, and proposes a discount rate benchmarking decision support system based on service-specific risk aversion. The proposed approach has the flexibility of choosing appropriate discount rates for gauging long-term services, as opposed to decisions based simply on duration. It improves injury identification in NRDA since potential damages and side-effects to ecosystem services are revealed within the service-specific framework. A real embankment case study demonstrates valid implementation of the method.

  • 20.
    Wu, Desheng
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Cui, Yiwen
    Disaster early warning and damage assessment analysis using social media data and geo-location information2018In: Decision Support Systems, ISSN 0167-9236, E-ISSN 1873-5797, Vol. 111, p. 48-59Article in journal (Refereed)
    Abstract [en]

    Societies are confronted with destructive natural disasters of increasing frequency. Social networks are playing an increasingly important role as early warning systems, aiding with rapid disaster assessment and post-disaster recovery. There is a need for both the public and disaster-relief agencies to better understand how social media can be utilized to assess and respond to natural disasters. However, existing research on the role of social media in society's response to natural disasters is neither holistic nor systematic. In this study, we conduct a hierarchical multiscale analysis based on multiple data resources, combining social media data, economic losses, and geo-information. We verify the role played by social media before, during, and after a natural disaster. We investigate whether the combination of social media and geo-location information can contribute to a more efficient early warning system and help with disaster assessment. This paper draws attention to the fact that during a disaster, citizens turn to social media and the majority of tweets contain information about the hurricane and/or its impact with negative sentiment. We demonstrate that the severity of damage in one area is positively correlated with the intensity of disaster-related activity. Meanwhile, the coastal areas and areas with close proximity to Hurricane center tend to suffer from higher losses during a disaster. Our findings explore the role played by social media from individuals in affected populations and how they respond to unfolding natural disasters. Results hold significance with regard to providing timely assistance for both official institutions and netizens.

  • 21.
    Wu, Desheng D.
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Toronto, Canada.
    Olson, David L.
    Luo, Cuicui
    A Decision Support Approach for Accounts Receivable Risk Management2014In: IEEE Transactions on Systems, Man, and Cybernetics: Systems, ISSN 2168-2216, Vol. 44, no 12, p. 1624-1632Article in journal (Refereed)
    Abstract [en]

    Financial disasters in private firms led to increased emphasis on various forms of risk management, to include market risk management, operational risk management, and credit risk management. Financial institutions are motivated by the need to meet increased regulatory requirements for risk measurement and capital reserves. This paper describes and demonstrates a model to support risk management of accounts receivable. We present a decision support model for a large bank enabling assessment of risk of default on the part of loan recipients. A credit scoring model is presented to assess account creditworthiness. Alternative methods of risk measurement for fault detection are compared, and a logistic regression model selected to analyze accounts receivable risk. Accuracy results of this model are presented, enabling accounts receivable managers to confidently apply statistical analysis through data mining to manage their risk.

  • 22.
    Wu, Desheng Dash
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Selling to the Socially Interactive Consumer: Order More or Less?2015In: ieee transactions on systems man cybernetics systems, ISSN 2168-2216, Vol. 45, no 3, p. 399-410Article in journal (Refereed)
    Abstract [en]

    This paper studies the newsvendor problem in the presence of consumer behavior, specifically, social interaction. We show that deterministic consumer valuation on products derived from social interaction can be an advantage for firms. This paper examines the implications of random consumer product valuation and a lower threshold number of subscribers to the proposed deal. Several implications have been yielded.

  • 23.
    Wu, Desheng Dash
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Toronto, Canada.
    Liu, Jia
    Olson, David L.
    Simulation Decision System on the Preparation of Emergency Resources Using System Dynamics2015In: Systems research and behavioral science, ISSN 1092-7026, E-ISSN 1099-1743, Vol. 32, no 6, p. 603-615Article in journal (Refereed)
    Abstract [en]

    This paper establishes a simulation decision system for both emergency resource preparation and emergency resource replenishment. The decision system uses both system dynamics and goal programming. A system dynamics model is then developed and validated with real case data as simulation decision support to emergency resource replenishment. An optimization simulation using the data from the emergency resource preparation process in the Ya'an earthquake in China is reported.

  • 24.
    Wu, Desheng Dash
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Toronto, Canada.
    Olson, David L.
    A System Dynamics Modelling of Contagion Effects in Accounts Risk Management2014In: Systems research and behavioral science, ISSN 1092-7026, E-ISSN 1099-1743, Vol. 31, no 4, p. 502-511Article in journal (Refereed)
    Abstract [en]

    Financial contagion has been with us as long as there has been an economy. The system of collective human behavior usually creates stable markets, but occasionally, this collective behavior results in various bubbles. Financial contagion specifically deals with the domino effect of one banking institution failing, which, as a result of interrelationships with other banks, leads to further failures. The year 1929 was a very bad year, but 2008 had its moments as well. These financial contagions result in undermining confidence in similar institutions. Our research question is to examine whether the role of accounts receivable payments is affected by social interaction of those holding loans from a lending institution. System dynamics modelling is used to demonstrate the impact of word-of-mouth social contacts on accounts receivable, and the ensuing increase in financial risk.

  • 25.
    Wu, Desheng Dash
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Yang, Lipo
    Olson, David L.
    Green supply chain management under capital constraint2019In: International Journal of Production Economics, ISSN 0925-5273, E-ISSN 1873-7579, Vol. 215, p. 3-10Article in journal (Refereed)
    Abstract [en]

    To determine how carbon emissions reduction affects supply chain operations and financing decisions, this paper examines a green supply chain, which consists of one manufacturer (playing the leading role) and one capital-constrained retailer; in this supply chain, bank financing and trade credit financing are viable. This research explores the retailer's optimal order quantity, the manufacturer's optimal wholesale price, the optimal level of carbon emissions (for both bank financing and trade credit financing), and the design of the contract to coordinate the supply chain. We find that the supply chain achieves a win-win outcome in terms of production quantity and emissions reduction when the manufacturer invests in emissions reduction. In addition, we find that a supply chain with a contract outperforms a non-contract supply chain in production quantity and emissions reduction. Furthermore, the effect is more remarkable when trade credit financing is viable.

  • 26.
    Wu, Desheng
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Liu, Tianxiang
    Curve Fitting Method for Implied Volatility2018In: Journal of Derivatives, ISSN 1074-1240, E-ISSN 2168-8524, Vol. 26, no 2, p. 19-37Article in journal (Refereed)
    Abstract [en]

    Curve-fitting methods are widely used in derivatives markets for construction of the implied volatility surface (IVS). Here we discuss the goodness of fit, smoothness, and economic implications of 12 distinctive curve-fitting methods. The choice of method relies on specific requirements. When fitting the Chicago Board Options Exchange data, three interpolation methods were found to provide the best goodness, whereas quadratic regression, the Nadaraya–Watson kernel regression, and the theoretical Carr–Wu model generate the smoothest surfaces. Because of the irregular nature of the emerging options market data, we propose a transformation method to improve three statistical methods to satisfy the Lee’s condition. Empirically, quadratic regression provides the best goodness when fitting the China 50ETF options data. In addition, the Carr–Wu model is a very good alternative because it natively satisfies the Lee’s condition and has economic implications.

  • 27.
    Wu, Desheng
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Liu, Tianxiang
    New Approach to Estimating VIX Truncation Errors Using Corridor Variance Swaps2018In: Journal of Derivatives, ISSN 1074-1240, E-ISSN 2168-8524, Vol. 25, no 4, p. 54-70Article in journal (Refereed)
    Abstract [en]

    An approach to estimating the volatility index (VIX) truncation error using corridor variance swaps (CVSs) is developed. It is shown that the existing VIX approach significantly underestimates option volatility in emerging markets. The truncation error of iVX (a product that mimics VIX in China's options market) is not only significant, but also volatile under different market conditions. It is demonstrated that other emerging markets, such as Korea and Mexico, also have significant VIX truncation errors. A new approach, different from the popular Fast Fourier Transform (FFT), is proposed for the valuation of corridor variance swaps. The Feynman-Kac connection is employed to derive a closed-form result and avoid the arbitrary damping factor (alpha) problem in the FFT approach.

  • 28.
    Wu, Desheng
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Ning, Shuang
    Dynamic assessment of urban economy-environment-energy system using system dynamics model: A case study in Beijing2018In: Environmental Research, ISSN 0013-9351, E-ISSN 1096-0953, Vol. 164, p. 70-84Article in journal (Refereed)
    Abstract [en]

    Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis.

  • 29.
    Wu, Desheng
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Toronto, Canada.
    Olson, David L.
    The State‐Of‐The‐Art Research in ‘Behavioral Risk’: An Introduction to the Special Issue2014In: Systems research and behavioral science, ISSN 1092-7026, E-ISSN 1099-1743, Vol. 31, no 4, p. 483-486Article in journal (Refereed)
    Abstract [en]

    Risks are endemic to doing business. Current events have made enterprise risk management to be even greater in importance. The complexity and interrelated nature of business operations today call for a systems view. This special issue involves seven papers providing tools useful in understanding and analysing systems risk. This introduction summarizes these papers and discusses their common thread of how organizational decisions involving behavioral-oriented risks can be supported.

  • 30.
    Wu, Desheng
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Management School of University of Chinese Academy of Sciences, China.
    Olson, David L.
    Dolgui, Alexandre
    Decision making in enterprise risk management: A review and introduction to special issue2015In: Omega: The International Journal of Management Science, ISSN 0305-0483, E-ISSN 1873-5274, Vol. 57, p. 1-4Article, review/survey (Refereed)
    Abstract [en]

    Risk-based decision making has been always important in everyday business life. Enterprise risk management (ERM) is the state-of-the-art approach to manage risks facing an organization from system perspective. This paper provides a review of popular literature in ERM using management science approaches, and an introduction of the special issue.

  • 31.
    Wu, Desheng
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Olson, David L.
    Wang, Shouyang
    Finance-operations interface mechanism and models2019In: Omega: The International Journal of Management Science, ISSN 0305-0483, E-ISSN 1873-5274, Vol. 88, p. 1-3Article, review/survey (Refereed)
    Abstract [en]

    Financial operations have attracted a great deal of attentions from both academic researchers and industrial practitioners in recent years. This special issue presents the state-of-the-art advances in the interfaces of finance and operations management.

  • 32.
    Wu, Desheng
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Song, Yu
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Wuhan University of Technology, China.
    Xie, Kefan
    Zhang, Baofeng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Science and Technology of China, China.
    Traits and causes of environmental loss-related chemical accidents in China based on co-word analysis2018In: Environmental science and pollution research international, ISSN 0944-1344, E-ISSN 1614-7499, Vol. 25, no 18, p. 18189-18199Article in journal (Refereed)
    Abstract [en]

    Chemical accidents are major causes of environmental losses and have been debated due to the potential threat to human beings and environment. Compared with the single statistical analysis, co-word analysis of chemical accidents illustrates significant traits at various levels and presents data into a visual network. This study utilizes a co-word analysis of the keywords extracted from the Web crawling texts of environmental loss-related chemical accidents and uses the Pearson's correlation coefficient to examine the internal attributes. To visualize the keywords of the accidents, this study carries out a multidimensional scaling analysis applying PROXSCAL and centrality identification. The research results show that an enormous environmental cost is exacted, especially given the expected environmental loss-related chemical accidents with geographical features. Meanwhile, each event often brings more than one environmental impact. Large number of chemical substances are released in the form of solid, liquid, and gas, leading to serious results. Eight clusters that represent the traits of these accidents are formed, including leakage, poisoning, explosion, pipeline crack, river pollution, dust pollution, emission, and industrial effluent. Explosion and gas possess a strong correlation with poisoning, located at the center of visualization map.

  • 33.
    Wu, Desheng
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Zhang, Baofeng
    Baron, Opher
    A Trade Credit Model with Asymmetric Competing Retailers2019In: Production and operations management, ISSN 1059-1478, E-ISSN 1937-5956, Vol. 28, no 1, p. 206-231Article in journal (Refereed)
    Abstract [en]

    We study a supply chain of a manufacturer selling to two asymmetric retailers engaged in inventory (order quantity) competition in the presence of demand uncertainty and an exogenously given retail price. The effective demand of each retailer includes its primary demand and reallocated demand from its competitor. We model two salient features causing asymmetry: (i) the weak retailer is capital-constrained and (ii) the bargaining power of the dominant retailer implies that it enjoys a lower wholesale price. The manufacturer offers trade credit to the weak, capital-constrained retailer. We show that such trade credit can be used by the manufacturer as a strategic response to the bargaining power of its dominant retailer. Computational examples reveal that under inventory competition, the capital-constrained retailer benefits from the trade credit, leaving the dominant retailer worse off. We show that demand substitution increases the profit of the dominant retailer and the manufacturer but, somewhat surprisingly, decreases the weak retailer's profit. When both bank and trade credit are available, we show conditions under which trade credit is preferred over bank credit by the manufacturer. Compared with a trade credit with an endogenous interest rate (and an exogenously given wholesale price), a trade credit with an endogenous wholesale price (and an exogenously given interest rate) is preferred by the manufacturer, but is only preferred by the system when the weak retailer's initial working capital is small.

  • 34.
    Wu, Dexiang
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School.
    Wu, Desheng Dash
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    A Robust Decision Support Approach to Portfolio Risk Reduction Based on Credit Default Swap2018In: Journal of Fixed Income, ISSN 1059-8596, E-ISSN 2168-8648, Vol. 27, no 3, p. 86-95Article in journal (Refereed)
    Abstract [en]

    We construct portfolios from the credit default swap (CDS) market by incorporating cardinality and solvency constraints into mean-variance and conditional value at risk (CVaR) models. Cardinality constraints are applied to limit the portfolio size and improve the allocation structure, while the solvency constraint is used to insulate the default risks of the portfolios under worst scenarios. CDS-based portfolios involve uncertainties that stem from spread changing and jump-to-default volatilities. We show that these uncertainties can be identified and managed using our developed systematic approach. Market data analysis from the CDS portfolios shows that using cardinality constraints reduces counterparty risks significantly. The proposed cardinality constrained CVaR model has robust performance in terms of the portfolio Sharpe ratio and one other metric, and also generally outperforms the associated mean-variance strategy.

  • 35.
    Wu, Dexiang
    et al.
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. Beihang University, China.
    Wu, Desheng Dash
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    An enhanced decision support approach for learning and tracking derivative index2019In: Omega: The International Journal of Management Science, ISSN 0305-0483, E-ISSN 1873-5274, Vol. 88, p. 63-76Article in journal (Refereed)
    Abstract [en]

    Tracking the movement of an index involves the parameter learning from data and algorithm design for solving the decision model. In this paper, we present a factor induced robust index tracking model to protect against the parameter estimation error and immunize both systematic and default risks of tracking portfolios. A Lagrangian-based algorithm is applied to approximate optimal solutions and enhance the capacity of the decision model. Two types of inequalities are derived to strengthen the Lagrangian lower bound and speed up the whole Lagrangian Relaxation (LR) method. With the designed system, we investigate large Credit Default Swap (CDS) dataset that includes 1246 daily observations across near 500 individual contracts. We show that the fluctuation range of portfolio out-of-sample returns can be shrunk significantly by using the proposed robust counterpart, e.g. from [-12%, 12%] to [-4%, 4%] in the second half of 2013, and other comparison metrics such as Sharpe ratio and tracking error to transaction costs (TE/TC) ratio could also be consistently improved.

  • 36. Zhang, Baofeng
    et al.
    Wu, Desheng Dash
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Science, China.
    Liang, Liang
    Optimal Option Ordering and Pricing Decisions With Capital Constraint and Default Risk2017In: IEEE Systems Journal, ISSN 1932-8184, E-ISSN 1937-9234, Vol. 11, no 3, p. 1537-1547Article in journal (Refereed)
    Abstract [en]

    This paper examines a single-period supply chain system consisting of a manufacturer selling an option contract to a capital-constrained retailer who faces stochastic demand. Option contract can transfer partial risk from the retailer to the manufacturer. This paper extends the existing literature of game-theoretic and credit financing models by explicitly incorporating retailer's default risk into the pure option ordering and pricing decision problems. Stackelberg equilibriums under different scenarios, i.e., capital sufficient, capital constraint without credit, bank credit (BC), and trade credit (TC), are derived. The analytic model demonstrates that, under TC, the retailer can behave with and without bankruptcy risk, which depends on the retailer's initial capital. Both the mathematical model and computational experiments reveal that the decisions and profits under BC are independent of retailer's default risk, whereas default risk has a significant impact on the decisions and profits under TC. It shows that TC contract can partially coordinate the supply chain.

  • 37. Zhao, Fuguo
    et al.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
    Liang, Liang
    Dolgui, Alexandre
    Lateral inventory transshipment problem in online-to-offline supply chain2016In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 54, no 7, p. 1951-1963Article in journal (Refereed)
    Abstract [en]

    Online-to-offline (OTO) is a new commercial model with enormous market potential. Online customer orders are forwarded to the offline brick-and-mortar store to fulfil, which is a combination of dual-channel supply chain. OTO overcomes many disadvantages of the traditional dual-channel supply chain, but still faces uncertain market demand. To reduce the inventory risk caused by demand uncertainty, lateral inventory transshipment is employed in this paper to pool inventory risk in OTO supply chain. We model centralised OTO and decentralised OTO with/without transshipment, and then analyse different scenarios. Our results demonstrate that there exists a unique Nash equilibrium of inventory order levels in dual channels and an optimal transshipment price to maximise the profit of the entire supply chain. Finally, we provide a numerical example of uniform demand distribution. Our analyses offer many managerial insights and show that transshipment always benefits the OTO supply chain.

  • 38. Zhaoae, Fuguo
    et al.
    Wu, Desheng
    Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Toronto, Canada.
    Liang, Liang
    Dolgui, Alexandre
    Cash flow risk in dual-channel supply chain2015In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 53, no 12, p. 3678-3691Article in journal (Refereed)
    Abstract [en]

    This paper focuses on multi-period cash flow risk which is measured by the SD in dual-channel supply chain. The manufacturer offers a consignment contract to the retailer, exposing cash flow risk due to the payment delay. We analyze cash inflows, outflows, and netflows of each member in dual-channel supply chain. We also examine different influencing factors on the preference of cash flows in dual-channel supply chain and then provide some managerial implications to deal with cash flow risk.

1 - 38 of 38
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