The impact of operational decisions on the design of salesforce incentives

When facing high levels of overstock inventories, firms often push their salesforce to work harder than usual to attract more demand, and one way to achieve that is to offer attractive incentives. However, most research on the optimal design of salesforce incentives ignores this dependency and assumes that operational decisions of production/inventory management are separable from design of salesforce incentives. We investigate this dependency in the problem of joint salesforce incentive design and inventory/production control. We develop a dynamic Principal‐Agent model with both Moral Hazard and Adverse Selection in which the principal is strategic and risk‐neutral but the agent is myopic and risk‐averse. We find the optimal joint incentive design and inventory control strategy, and demonstrate the impact of operational decisions on the design of a compensation package. The optimal strategy is characterized by a menu of inventory‐dependent salesforce compensation contracts. We show that the optimal compensation package depends highly on the operational decisions; when inventory levels are high, (a) the firm offers a more attractive contract and (b) the contract is effective in inducing the salesforce to work harder than usual. In contrast, when inventory levels are low, the firm can offer a less attractive compensation package, but still expect the salesforce to work hard enough. In addition, we show that although the inventory/production management and the design of salesforce compensation package are highly correlated, information acquisition through contract design allows the firm to implement traditional inventory control policies: a market‐based state‐dependent policy (with a constant base‐stock level when the inventory is low) that makes use of the extracted market condition from the agent is optimal. This work appears to be the first article on operations that addresses the important interplay between inventory/production control and salesforce compensation decisions in a dynamic setting. Our findings shed light on the effective integration of these two significant aspects for the successful operation of a firm. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 320–340, 2014Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/107557/1/nav21585.pd

Compensation and price delegation for heterogeneous sales force

A heterogeneous sales force may not be as desirable as a homogeneous sales force for two reasons: premiums are required for all except from one agent type, and only the highest type would work as hard as though they were from a homogeneous sales force. This study revisits the heterogeneous sales force compensation and price delegation problem with type-dependent reservation. We find that an equilibrium separating or pooling compensation contract always exists. Different types of agents may receive premiums, and there are scenarios when no premiums are paid. Retaining centralized pricing provides a tool for regulating agent behavior. More than one or even all agent types may work as hard as though they were members of a homogeneous sales force. These findings differ from existing results and their driving force is the dynamics between the differences in reservations and agents’ effort costs arising from concealing their true types

Designing multi-target salesforce incentive contract

Multi-target incentive contracts are widely observed in practice to stimulate salesforce effort. However, little is known about their effectiveness and the issues involved in designing them. In this thesis, we investigate the incentive contracting problem between a manufacturer and an agent when the realized sales of a product are affected by both the agent\u27s selling effort and the type of the agent. The agent\u27s type is uncertain to the manufacturer, whereas the agent can observe the actual type when exerting her selling effort. Again, this is unobservable by the manufacturer. For contract design problem, we develop a principal-agent model with both moral hazard and adverse selection. We examine the manufacturer\u27s optimal contract parameter decisions employing a single multi-target contract for the agent who can be of different types. Because menu contracts are commonly studied in literature for the adverse selection problem, we also study a menu of single-target contracts; and examine the manufacturer\u27s optimal contract parameter decisions. We then compare the performance between the two types of contract. We arrive at a number of managerial insights regarding the design and the performance of multi-target contract and menu contract

Modeling the Psychology of Consumer and Firm Behavior with Behavioral Economics

Marketing is an applied science that tries to explain and influence how firms and consumers actually behave in markets. Marketing models are usually applications of economic theories. These theories are general and produce precise predictions, but they rely on strong assumptions of rationality of consumers and firms. Theories based on rationality limits could prove similarly general and precise, while grounding theories in psychological plausibility and explaining facts which are puzzles for the standard approach. Behavioral economics explores the implications of limits of rationality. The goal is to make economic theories more plausible while maintaining formal power and accurate prediction of field data. This review focuses selectively on six types of models used in behavioral economics that can be applied to marketing. Three of the models generalize consumer preference to allow (1) sensitivity to reference points (and loss-aversion); (2) social preferences toward outcomes of others; and (3) preference for instant gratification (quasi-hyperbolic discounting). The three models are applied to industrial channel bargaining, salesforce compensation, and pricing of virtuous goods such as gym memberships. The other three models generalize the concept of gametheoretic equilibrium, allowing decision makers to make mistakes (quantal response equilibrium), encounter limits on the depth of strategic thinking (cognitive hierarchy), and equilibrate by learning from feedback (self-tuning EWA). These are applied to marketing strategy problems involving differentiated products, competitive entry into large and small markets, and low-price guarantees. The main goal of this selected review is to encourage marketing researchers of all kinds to apply these tools to marketing. Understanding the models and applying them is a technical challenge for marketing modelers, which also requires thoughtful input from psychologists studying details of consumer behavior. As a result, models like these could create a common language for modelers who prize formality and psychologists who prize realism

Mechanism Design of Fashion Virtual Enterprise under Monitoring Strategy

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A Field Study of the Impact of a Performance-Based Incentive Plan

Much management accounting research focuses on design of incentive compensation contracts. A basic assumption in these contracts is that performance-based incentives improve employee performance. This paper reports on a field test of the multi-period incentive effects of a performance-based compensation plan on the sales of a retail establishment. Analysis of panel data for 15 retail outlets over 66 months indicates a sales increase when the plan is implemented, an effect that persists and increases over time. Sales gains are significantly lower in the peak selling season when more temporary workers are employed

Incentive Design for Operations-Marketing Multitasking

A firm hires an agent (e.g., store manager) to undertake both operational and marketing tasks. Marketing tasks boost demand, but for demand to translate into sales, operational effort is required to maintain adequate inventory. The firm designs a compensation plan to induce the agent to put effort into both marketing and operations while facing “demand censoring” (i.e., demand in excess of available inventory is unobservable). We formulate this incentive-design problem in a principal-agent framework with a multitasking agent subject to a censored signal. We develop a bang-bang optimal control approach, with a general optimality structure applicable to a broad class of incentive-design problems. Using this approach, we characterize the optimal compensation plan, with a bonus region resembling a “mast” and “sail,” such that a bonus is paid when either all inventory above a threshold is sold or the sales quantity meets an inventory-dependent target. The optimal “mast and sail” compensation plan implies non-monotonicity, where the agent can be less likely to receive a bonus for achieving a better outcome. This gives rise to an ex post moral hazard issue where the agent may “hide” inventory to earn a bonus. We show this ex post moral hazard issue is a result of demand censoring. If available information includes a waitlist (or other noisy signals) to gauge unsatisfied demand, no ex post moral hazard issues remain

Distributionally Robust Principal-Agent Problems and Optimality of Contracts

We propose a distributionally robust principal agent formulation, which generalizes some common variants of worst-case and Bayesian principal agent problems. We construct a theoretical framework to certify whether any surjective contract family is optimal, and bound its sub-optimality. We then apply the framework to study the optimality of affine contracts. We show with geometric intuition that these simple contract families are optimal when the surplus function is convex and there exists a technology type that is simultaneously least productive and least efficient. We also provide succinct expressions to quantify the optimality gap of any surplus function, based on its concave biconjugate. This new framework complements the current literature in two ways: invention of a new toolset; understanding affine contracts' performance in a larger landscape. Our results also shed light on the technical roots of this question: why are there more positive results in the recent literature that show simple contracts' optimality in robust settings rather than stochastic settings? This phenomenon is related to two technical facts: the sum of quasi-concave functions is not quasi-concave, and the maximization and expectation operators do not commute

The Effect of Behavioral Biases on Supply Chain Decisions

Traditional work in operations management has focused on topics such as supply chain contracts and pricing, studying design of efficient contracts and optimal pricing policies. After these optimal solutions and recommendations are derived, they must be implemented properly by managers in practice. Because this process is subject to behavioral decision biases, work in behavioral operations management has begun to connect theories of decision biases to behavior in classical operations management. My dissertation focuses in this area by studying how decisions are made by suppliers and retailers in B2B settings. In essay one, I investigate the effect of effort-dependent demand on supply chain contracts. It is found that the actual cost of effort affects the retailer's optimal level of effort and subsequently determines when a supplier should prefer a wholesale price contract to a buyback contract. As the retailer's cost of effort increases, the retailer's optimal level of effort decreases, leading the supplier to prefer the wholesale price contract. It is verified experimentally that retailer and supplier decisions are driven by cost of retailer effort. Furthermore, I demonstrate that suppliers' contract preferences are influenced by effort cost, not expected profit. In essay two, I look at the link between two supply chain decisions that have previously not been connected before. In this this essay, I study how the contract type (wholesale price or buyback) offered to the retailer affects his decision about which product to stock, particularly when one product is obviously riskier than another. I find, experimentally, that while contract type should make no difference in preferences between a safe and risky product, the retailer displays markedly different preferences arcoss contract type. I propose that this difference in preference structure can be explained by a model that incorporates a Prospect Theory weighting function. Finally, I demonstrate experimentally that this behavioral model of choice explains retailer product choice both when making the isolated product choice decision and the joint product/quantity decision

Supply Chain Contracting for After-sales Service and Product Support

Abstract Over the past decades, business model innovation in product and its service has been growing rapidly, especially for durable goods. Companies shift their strategies from selling physical products to delivering solutions and performance for customers. Within this context, the outcome-based service contracts, such as Performance-based Logistics and Power-by-the-Hour, have been developed in both public and commercial industry. At the same time, traditional service contracts such as Warranty and Time & Material contracts are still being used in many occasions. Under various business models, managing the after-sales service and product support becomes increasingly challenging. In this thesis, we study several important service contracting problems concerning optimal design of contract terms, spare parts inventory and service capacity ma