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Controllability of Risk and the Design of Incentive-Compensation Contracts

Christopher S. Armstrong, Stephen Glaeser and Sterling Huang

Abstract

We examine how the ability to control firm exposure to risk affects the design of executive compensation contracts. To do so, we use the introduction of exchanged-traded weather derivatives, which significantly increased executives’ ability to control their firms’ exposure to weather risk, as a natural experiment. We find that executives for whom weather derivatives have the greatest impact on the ability to control firm exposure to weather risk experience relative declines in total compensation and equity incentives. The former finding is consistent with a reduction in the risk premium that executives receive for their firms’ exposure to weather risk. The latter finding suggests that risk and incentives are complements when executives can control their firms’ exposure to risk. Collectively, our results show that the executives’ ability to control their firms’ exposure to risk alters the nature of agency conflicts and influences the design of incentive-compensation contracts.

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23 CKGSB Alumni Named on 2021 Forbes China Philanthropy List

In the recent 2021 Forbes China Philanthropy List, 23 of the 100 top Chinese entrepreneurs who had made the most contributions to public welfare were CKGSB alumni. Compiled based on cash donations of individual and corporate donors in China during 2020, this year’s list represents 221.7 billion RMB (approx. US $34.21 billion）cash donations made to charity, in which CKGSB 23 alumni’s contributions of 63 billion RMB (approx. US $9.72 billion) make up 30% of the total amount.

In addition to the Philanthropy List, CKGSB alumni also had a prominent presence in other lists that Forbes China recently released, amplifying CKGSB’s positioning as the preferred choice for business leaders:

  • 2021 Forbes China’s 50 Best CEO: 7 CKGSB alumni listed
  • 2021 Forbes China’s 100 Top Businesswomen: 11 CKGSB alumni listed
  • 2021 Forbes China’s 50 Women in Tech: 2 CKGSB alumni listed
  • 2021 Forbes China’s 20 Up-and-coming Businesswomen: 1 CKGSB alumni listed
  • 2021 Forbes China’s 100 Most Innovative Companies: 6 CKGSB alumni companies were listed

Since its establishment in 2002, philanthropy has been part of CKGSB’s DNA and core responsibility. CKGSB’s vision is to influence the Chinese business community in addressing society’s most challenging problems and sharing best practices in social innovation from China with the world. We are proud of our alumni in their unwavering dedication to give back to society as evidenced in the recent Forbes rankings!

Click here for more information on CKGSB’s efforts in social innovation and social responsibility. 

 

 

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Informational Complementarity

Tony Ke, Lin Song

Many products are correlated because they share some similar or common attributes. We show that when these attributes are uncertain to consumers, a complementarity effect can arise among competing products, in the sense that a lower price of one product may increase the demands of others. The effect occurs when consumers optimally search for information about both common and idiosyncratic product attributes prior to purchase. We characterize the optimal search strategy for the correlated search problem and provide the conditions for the existence of the complementarity effect. We further explore the implications of the effect for firm pricing. When firms compete in price, although product correlation may weaken differentiation between the firms, the complementarity effect due to correlated search may raise equilibrium price and profit.

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Bin KE

Biography

Dr. Ke is a Professor of Accounting, Provost’s Chair, and Director of Asia Accounting Research Centre at the NUS Business School since 2015. He is a holder of the prestigious “Chang Jiang Scholar” (“长江学者”) title awarded by China’s Ministry of Education and the Li Ka Shing Foundation (http://www.lksf.org/eng/project/education/ckh_award/main01.shtml). He was the President of the Chinese Accounting Professors Association of North America (www.capana.net), a leading academic organization that promotes high-quality accounting research on China, the Asia Pacific region, and other emerging market economies.

Dr Ke’s primary teaching interests include financial accounting principles, financial statement analysis, and doctoral seminars on empirical financial accounting research. He has also taught U.S. federal income taxation.

Dr. Ke’s primary research interests focus on the economic forces that determine the production and use of accounting information in business decisions. He is interested in using interdisciplinary approaches to tackle today’s complex business problems. Examples of his research include earnings management, insider trading, institutional investors, and financial analysts. Dr. Ke’s recent research focuses on financial reporting, managerial incentives, and investor protection in emerging markets with a particular focus on China. His research has been published in all major accounting journals, including The Accounting Review, Journal of Accounting and Economics, Journal of Accounting Research, Review of Accounting Studies, and Contemporary Accounting Research.

Dr. Ke is a consulting editor of the China Journal of Accounting Research, a current or former editorial board member of the Journal of American Taxation Association, The Accounting Review, and The International Journal of Accounting. He was an advisory board member of the Accounting Research in China published by the Accounting Society of China. He was an editor of The Accounting Review over June 2011-May 2014.

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LIN Song

Song Lin is an Assistant Professor of Marketing at the Department of Marketing of Hong Kong University of Science and Technology. He holds a PhD in Marketing from Massachusetts Institute of Technology. His research interests include product and pricing polices, platform design, consumer learning and search, new products, and advertising.  He has won the 2013 INFORMS Society for Marketing Science (ISMS) Doctoral Dissertation Proposal Competition, and the finalist for the 2015 John Little Award for the best marketing paper published in Marketing Science and Management Science.

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Letting Logos Speak: A Machine Learning Approach to Data-Driven Logo Design

Ryan Dew, Asim Ansari, Olivier Toubia

Logos serve a fundamental role in branding as the visual figurehead of the brand. Yet, due to the difficulty of using unstructured image data, prior research on logo design has been largely limited to non-quantitative studies. In this work, we explore logo design from a data-driven perspective. In particular, we aim to answer several key questions: first, to what degree can logos represent a brand’s personality? Second, what are the key visual elements in logos that elicit brand and firm relevant associations, such as brand personality traits? Finally, given text describing a firm’s brand or function, can we suggest features of a logo that elicit the firm’s desired image? To answer these questions, we develop a novel logo feature extraction algorithm, that uses modern image processing tools to decompose unstructured pixel-level image data into meaningful visual features. We then analyze the links between firm identity, and the features of its logo, through both predictive modelling, and a probabilistic model which links visual features with textual descriptions of firms. We apply our modeling framework on a dataset of hundreds of logos, textual descriptions from firms’ websites, third party descriptions of firms, and consumer evaluations of brand personality to explore these questions.

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Ryan Dew

Ryan Dew is an Assistant Professor of Marketing at the Wharton School of the University of Pennsylvania. He received his B.A. in Mathematics from the University of Pennsylvania, and his M.Phil. and Ph.D. in Marketing from Columbia University. His research explores how machine learning and Bayesian statistical methodologies can solve real world marketing problems, with a particular interest in the domains of customer relationship management, preference dynamics and estimation, and data-driven design. His recent work, Bayesian Nonparametric Customer Base Analysis with Model-based Visualizations, has been published in Marketing Science. His on-going research focuses on understanding and predicting how consumer preferences change over time, through novel hierarchical nonparametric models, and on understanding the underpinnings of effective logo design from a data-driven perspective, utilizing image processing and machine learning techniques. His dissertation, Machine Learning Methods for Data-driven Decisions, was a winner of the ISMS Doctoral Dissertation Proposal Competition, the Marketing Section of the American Statistical Association’s Doctoral Research Award, and was an honorable mention in the Marketing Science Institute’s Alden G. Clayton Doctoral Dissertation Proposal Competition.

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The Role of the Physical Store: Developing Customer Value through ‘Fit Product’ Purchases

Chun-wei Chang, Jonathan Z. Zhang, Scott Neslin

Recent trends suggest retailers are ambivalent regarding the contribution of the physical retail store.  Ironically, several traditionally offline retailers are closing stores, while some traditionally online retailers are opening them.  This raises the question, what is the role of the physical retail store in today’s multichannel environment?  We posit that the type of product purchased, “fit” or “non-fit”, impacts subsequent customer value, and that purchasing fit products offline is especially effective at creating high value customers. We formulate a multivariate hidden Markov model (HMM) to investigate how customers make product and channel decisions. The HMM identifies two dynamic states – low-value and high-value. We hypothesize and find that fit-product purchases accelerate customer migration to the high-value state, especially if those purchases are made in the physical store. We theorize this occurs because buying fit products requires customer engagement, the physical store excels at providing this engagement, and engagement leads to higher customer satisfaction and hence value.  In addition, we find that offline marketing communication, specifically direct mail, enhances the likelihood the customer buys fit products offline and hence migrates customers to the high-value state, or keeps them at high value if they are already there. Our findings identify a strategic role that fit products and retail stores play in customer development, and show that marketing can help implement this strategy.

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Scott Neslin

Scott A. Neslin is the Albert Wesley Frey Professor of Marketing at the Tuck School of Business, Dartmouth College.  He has been a visiting scholar at the Yale School of Management, the Fuqua School of Business, and Columbia Business School. Professor Neslin’s expertise is in the fields of customer relationship management, measurement of marketing effectiveness, sales promotion, and advertising.  He has published several papers on these topics in leading academic journals.  He is co-author with Robert C. Blattberg and Byung-Do Kim of the book, Database Marketing:  Analyzing and Managing Customers, co-authors with Robert C. Blattberg of the book, Sales Promotion: Concepts, Methods, and Strategies, and author of the Marketing Science Institute monograph, Sales Promotion. Professor Neslin has served as President of the INFORMS Society for Marketing Science (ISMS) and is an ISMS Fellow.