可持续发展的运营理论, Agency理论, 量化分析


2012 美国印第安纳大学 Kelley商学院 博士
2002 上海交通大学 学士

副教授,上海财经大学, 2014年-至今
助理教授,上海财经大学, 2012年-2013年
  • wang.wenbin@shufe.edu.cn
  • 021 65907161
  • 021 65907458
Shanshan Hu, Gilvan C. Souza, Mark E. Ferguson, Wenbin Wang, (2015), "Capacity Investment in Renewable Energy Technology with Supply Intermittency: Data Granularity Matters!", Manufacturing & Service and Operations Management, vol. 17, No. 4, pp.480-494       
We study an organization’s one-time capacity investment in a renewable energy-producing technology with supply intermittency and net metering compensation. The renewable technology can be coupled with conventional technologies to form a capacity portfolio that is used to meet stochastic demand for energy. The technologies have different initial investments and operating costs, and the operating costs follow different stochastic processes. We show how to reduce this problem to a single-period decision problem and how to estimate the joint distribution of the stochastic factors using historical data. Importantly, we show that data granularity for renewable yield and electricity demand at a fine level, such as hourly, matters: Without energy storage, coarse data that does not reflect the intermittency of renewable generation may lead to an overinvestment in renewable capacity. We obtain solutions that are simple to compute, intuitive, and provide managers with a framework for evaluating the trade-offs of investing in renewable and conventional technologies. We illustrate our model using two case studies: one for investing in a solar rooftop system for a bank branch and another for investing in a solar thermal system for water heating in a hotel, along with a conventional natural gas heating system.
Wang Wenbin, M. Ferguson, Shanshan Hu, G. C. Souza, (2013), "Dynamic Capacity Investment with Two Competing Technologies", Manufacturing & Service Operations Management, vol. 15, No. 4, pp.616–629       
With the recent focus on sustainability, firms making adjustments to their production or distribution capacity levels often have the option of investing in newer technologies with lower carbon footprints and/or energy consumption. These more sustainable technologies typically require a higher up-front investment but have lower operating (fuel or energy) costs. What complicates this decision is the fact that the projected dollar savings from the more sustainable technologies fluctuate considerably due to uncertainty in fuel prices, and the total capacity may not be utilized at 100% because of fluctuations in the demand for the product. We consider the firm’s capacity adjustments over time given a portfolio of technology options when the demand and the fuel costs are stochastic and possibly dependent. Our model also allows for usage-based capacity deterioration. We provide the analytical structure of the optimal policy, which assigns different control limits for investing, staying put, and disinvesting in the capacities of the competing technology choices for each realization of demand and fuel costs at each period. We also present an application of our model to the problem of designing a delivery truck fleet for a beverage distributor.
Capacity Investment Decisions in Renewable Energy Technologies., (2015), Environmentally Responsible Supply Chains,,Springer.  
Ming Hu, Yan Liu, Wenbin Wang, (2016), "Altruistic Rationality: The Value of Strategic Farmers, Social Entrepreneurs and For-Profit Firms in Crop Planting Decisions"        
Price fluctuations in agricultural markets are an obstacle to poverty reduction for small-scale farmers in developing countries. We build a micro-foundation to study how farmers of heterogeneous production costs, under price fluctuations, make crop-planting decisions over time to maximize their incomes. We consider both strategic farmers, who rationally anticipate the near-future prices as a basis for making planting decisions, and na¨ıve farmers, who shortsightedly react to recent crop prices. The latter behavior may cause recurring over- or under-production, which leads to price fluctuations. We find it important to cultivate strategic farmers, because their self-interested behavior alone, made possible by sufficient market information, can reduce price volatility and benefit all farmers. Surprisingly, even a tiny fraction of strategic farmers may be enough to stabilize the market price. In the absence of strategic farmers, an optimally-designed pre-season procurement contract, offered by a social entrepreneur or for-profit firm to a fraction of contract farmers, brings benefit to all the farmers as well as to the firm itself. More strikingly, the optimal contract not only brings equity in the long run among farmers of the same production cost, but also reduces income disparity over time among farmers of heterogeneous costs, regardless of whether they are contract farmers or not. On the other hand, a poorly designed contract may distort the market and drive non-contract farmers out of business.
Yannan Jin, Wenbin Wang, (2016), "On the Adoption of Smart Home Appliance for Energy Shifing"   .
On the adoption for smart home appliance for energy shifting Smart home appliance can shift energy consumption in response to energy price and thus hold great potential for reducing energy cost. We use a game theoretical approach to analyze how the adoption decisions are affected by the pricing decisions of the manufacturer, the utility company and the government subsidy.
Gil Souza, Wenbin Wang, Owen Wu, (2016), "Optimal Size of a Combined Heat and Power Generator for an Industrial Firm"   .
We consider a manufacturer who uses both steam and electricity in its primary production process makes investment on a Combined Heat and Power (CHP) system. We provide a decision model and find the optimal capacity and operating policy for a CHP system that reduce the total investment and energy costs.
Wang Wenbin, (2015), "Using Two-part Trade Credit to Motivate Marketing Effort from A Retailer?"   .
Wenbin Wang, Shanshan Hu, (2015), "Moral Hazard with Limited Liability: The Random-Variable Formulation and Optimal Contract Structures"        
We consider an important category of agency models: the moral hazard problem between a principal and an agent with limited liability. We introduce a new way of formulating the model, where the contract design problem reduces to a problem of constructing the distribution function of a random variable. This formulation allows to directly balance the central tradeoff in the agency problem: maximizing the principal’s payoff as well as incentivizing the agent to exert effort or take proper risk. Our new method overcomes the limitation of the standard first-order-approach in solving the moral hazard problems in practice. Several structural results are established about the optimal contracts. We are the first to report that the optimal contract may involve two tiers of performance-based bonuses. In regard to the widely used bonus contract, we obtain new sufficient conditions for its optimality and provide new insights about setting the bonus-triggering threshold and bonus size.





第七届运营与供应链管理国际学术会议, 最佳论文评比一等奖 (2013)

校嘉奖 (2014, 2015)

本科生优秀论文指导奖 (2015)

校教学成果奖二等奖 (2016)

华人学者管理工程与科学协会最佳论文评比 荣誉奖 (2017)




Wenbin Wang is an Associate Professor of Operations Management at the School of International Business Administration, Shanghai University of Finance and Economics. His research interests lie in two areas. The first area can be labeled as sustainable operations with adaptation to energy markets, and it is mainly concerned with optimizing a firm’s technology and capacity investment choices so that the firm gains the ability to operate sustainably when faced with highly volatile energy prices. The second area of interest is related to inter-firm contracting in the presence of limited financial liability. One of the main challenges in this stream is to solve contract design problem with asymmetric information and limited liability in practical settings where the existing economic method may not directly apply.

Wenbin’s teaching interests include supply chain management, sustainable operations and contract theory.He received his Ph.D. in Operations Management and Decision Science from Kelley School of Business at Indiana University in 2012. He received a B.E. degree in Computer Science from Shanghai Jiaotong University.

浦江人才计划 (No. 14PJC044) 2014-1016

国家自然科学研究青年项目 (No. 71501121) 2016-2018 "可再生能源产能与能源存储技术的综合研究"

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