Designing Incentive Systems for Truthful Forecast Information Sharing Within a Firm. Case Study, Theory and Experiments

In environments with uncertain demand, companies must rely on forecasts to plan and execute their internal supply processes. A phenomenon frequently observed in practice is that demand forecasts are systematically too high. One reason could be incentive systems that motivate employees in Marketing/Sales to maximize their sales volume. In this respect, inflated demand forecasts are a means to ensure sufficient inventory and to minimize the risk of shortages. The objective of this thesis is to design incentive systems that lead to accurate and unbiased demand forecasts. We motivate and contextualize our research question by the practical case of a company in the pharmaceutical industry. To analyze the results of the case study more systematically, we transfer the forecast information exchange into a game-theoretic model. In an environment with stochastic demand, a (better informed) Sales department sends a forecast to an Operations department. To incentivize truthful forecast information sharing, the incentive system of Sales contains a penalty for forecast errors. The utility functions are grounded in behavioral theories of mental accounting, loss aversion and lying aversion. We formalize the setting as a signaling game and derive the Pareto-dominant separating equilibria of the game. In laboratory experiments, we observe behavior that deviates substantially from expected-payoff-maximizing behavior in the directions predicted by our behavioral model. Based on our theory and estimates for the behavioral parameters of our model, we design forecast-error-based incentive systems for truthful forecast information sharing. We validate their effectiveness in a new experiment with out-of-sample treatments and out-of-sample subjects. We further confirm the robustness of our model by additional experiments and analyses

An Investigation of Buyers’ Forecast Sharing and Ordering Behavior in a Two-Stage Supply Chain

Profitably balancing demand and supply is a continuous challenge for companies under changing market conditions, and the potential benefit of collaboration between supply chain partners cannot be overlooked by any firm who strives to succeed. One of the key elements to successful collaboration is sharing of forecast information between supply chain partners. However, when supply shortage is expected, buyers may inflate order quantities and/or order forecasts to secure sufficient supply. An important question that arises is how the supplier should allocate inventory to customers when shortage exists. Literature shows that certain allocation policies can reduce buyers’ order inflation behavior. However, this has not yet been empirically shown for order forecast inflation behavior, nor incorporating the behavioral aspects of decision makers. In this dissertation, through behavioral experiments using a supply chain simulation game, we investigate the impact of different capacity allocation mechanisms and information disclosures of a supplier on buyers’ forecast sharing and ordering behavior. We first investigate the buyers’ order forecast sharing behavior in a single-suppliertwo- buyer supply chain. Our behavioral study shows that forecast-accuracy based allocation, where the supplier allocates more capacity to the buyer with better forecast accuracy, can significantly improve order forecast accuracy relative to uniform allocation, where the supplier equally allocates capacity to the buyers. Under both policies, particularly uniform allocation, the order forecast accuracy is improved with the supplier’s information disclosure on the policy. Next, we focus on buyers’ ordering behavior, and formulate a single-supplier-single-buyer base-stock inventory model under constrained supply. We validate our analytical results through numerical simulation, which is then extended to the single-supplier-two-buyer case. We next compare the buyers’ optimal decisions from the simulation with the actual decisions in our behavioral study, and find that buyers in the experiment show a significantly lower profit performance ranging from 0.8% to 14.1%. Using structural estimation modeling techniques, we estimate the buyers’ perceived overage/underage cost ratios from the experiment, and conclude by conducting a detailed analysis on the factors that affect buyers’ ordering decisions. In addition to academic contributions, our results provide insights for practitioners to understand buyers’ strategic behavior and help with designing capacity allocation strategies

Trust and Trustworthiness

In this chapter, we discuss when, how, and why trust and trustworthiness arise to support cooperation within and across organizations. To do so, we first define trust and trustworthiness, discuss how they can be quantified, and determine key components of trusting and trustworthy behavior. In addition, we identify building blocks of trust and trustworthiness and offer tangible insights about how to establish trusting and cooperative business/interorganizational relationships, based on both academic research and case studies from across industries

Making apartments affordable: moving from speculative to deliberative development

Urban consolidation policies in Australia presuppose apartments as the new dominant housing type, but much of what the market has delivered is criticised as over-development, and as being generic, poorly-designed, environmentally unsustainable and unaffordable. In contrast to the usual focus on planning regulation and construction costs as the primary issues needing to be addressed in order to increase the supply of quality, affordable apartment housing this paper uses Ball’s (1983) ‘structure of provision’ approach to outline the key processes informing apartment development to reveal a substantial gap in critical understanding of how apartments are developed in Australia, and identifies economic problems not previously considered by policymakers. Using mainstream economic analysis to review the market itself, the authors found high search costs, demand risk, problems with exchange, and lack of competition present key barriers to achieving greater affordability and limit the extent to which ‘speculative’ developers can respond to the preferences of would be owner-occupiers of apartments. The existing development model, which is reliant on capturing uplift in site value, suits investors seeking rental yields in the first instance and capital gains in the second instance, and actively encourages housing price inflation. This is exacerbated by lack of density restrictions, such as have existed in inner Melbourne for many years, which permits greater yields on redevelopment sites. The price of land in the vicinity of such redevelopment sites is pushed up as landholders\u27 expectation of future yield is raised. All too frequently existing redevelopment sites go back onto the market as vendors seek to capture the uplift in site value and exit the project in a risk free manner. The paper proposes three major reforms. Firstly, that the market for apartment development be re-designed following insights from the economic field of ‘Market Design’ (a branch of Game Theory). A two-sided matching market for new apartments is proposed, where demand-side risks can be mitigated via consumer aggregation. Secondly, consumers should be empowered through support for  ‘deliberative’, or ‘do-it-yourself’ (DYI) development models, in order to increase competition, expand access, and promote responsiveness to consumer needs and preferences. Finally, planning schemes need to impose density restrictions (in the form of height limits, floor space ratios or bedroom quotas) in localities where housing demand is high, in order to dampen speculation and de-risk development by creating certainty. However restrictions on over-development on larger infill sites needs to be offset by permitting intensification of ‘greyfield’ suburbs. Aggregating existing housing lots to enable precinct regeneration and moderate height and density increases would permit better use of airspace thus allowing design outcomes that can optimise land use while retaining amenity

Risk allocation and the costs and benefits of public-private partnerships

We study the agency costs of delegated public service provision, focusing on the link between organizational forms and uncertainty at project implementation.We consider a dynamic multitask moral hazard environment where the mapping between effort and performance is ex ante uncertain but new information may arise during operations. Our analysis highlights the costs and benefits that bundling planning and implementation—as under public–private partnerships—can bring in terms of project design and operational costs under various scenarios, possibly allowing for asymmetric information, moral hazard and renegotiation. It also shows that relying on private finance enhances the benefits of bundling only if lenders have enough expertise to assess project risks

Collective Outsourcing to Market (COM): A Market-Based Framework for Information Supply Chain Outsourcing

This paper discusses the importance of and a solution to separating the information flow from the physical product flow in a supply chain. Motivated by the inefficient demand forecast caused by information asymmetry and lack of an incentive among supply chain partners to share valuable information, we propose a radically new framework called collective outsourcing to market (COM) to address many information supply chain design challenges. To validate the COM framework, we consider a supply chain with one manufacturer and multiple downstream retailers. Retailers privately acquire demand forecast information that they do not have incentive to share horizontally with other retailers or vertically with the upstream manufacturer. We consider two alternative market mechanisms that can be used to outsource the information-intensive demand forecasting task for the whole supply chain. The specially organized market can be viewed as a cost effective way of acquiring quality information that, at the same time, aligns individual retailers\u27 incentives to credibly share their private information. We further discuss the real world implementation issues including market design and the costs and benefits of proposed solutions

Information leakage and sharing in decentralized systems

This thesis presents two essays that explore firms’ incentive to share information in a multi-period decentralized supply chain and between competing firms. In the first essay, we consider a two-period supply chain in which one manufacturer supplies to a retailer. The retailer possesses some private demand information about the uncertain demand and decides whether to share the information with manufacturer. If an information sharing agreement is achieved, the retailer will share the observed demand information truthfully to the manufacturer. Then the selling season with two periods starts. In each period, the manufacturer decides on a wholesale price, which the retailer considers when deciding on the retail price. The manufacturer can observe the retailer\u27s period-1 decision and the realized period-1 demand, and use this information when making the period-2 wholesale price decision. Thus, without information sharing, the two firms play a two-period signaling game. We find that voluntary information sharing is not possible because it benefits the manufacturer but hurts the retailer. However, different from one-period model, in which no information sharing can be achieved even with side payment, the manufacturer can make a side payment to the retailer to induce information sharing when the demand range is small. Both firms benefit from more accurate information regardless whether the retailer shares information. We also extend the two-period model to three-period model and infinite-period model, we find that the above results are robust. The second essay studies the incentives for information sharing between two competing firms with different production timing strategies. Each firm is planning to produce a new (upgraded) product. One firm adopts routine timing, whereby her production time is fixed according to her tradition of similar or previous models of the product. The other firm uses strategic timing, whereby his production time can be strategically chosen: be it before, simultaneously with, and after the routine firm. The two firms simultaneously choose whether or not to disclose their private demand information, make their quantity decisions based on any demand information available, and then compete in the market. We find that when the demand uncertainty is not high, both firms sharing information is the unique equilibrium outcome. Exactly one firm (the routine firm) sharing information can arise in equilibrium when the demand uncertainty is intermediate. These results are in stark contrast to extant literature which has shown that, for Cournot competitors with substitutable goods, no firm is willing to share demand information. Production timing is thus identified as a key driving force for horizontal information sharing, which might have been overlooked before. Surprisingly, when the competition becomes more intense, firms are more willing to share information. It is the information asymmetry that fundamentally change the strategic firm’s timing. We highlight the impact of signaling demand information for an early-production firm on the timing strategies, under different information sharing arrangements