Optimal Information Acquisition Research Articles

Optimal Information Acquisition and Sharing Decisions

The acquisition and sharing of reviews have significant ramifications for the selection of crowdsourcing designs before mass production. This article studies the optimal decision of a brand enterprise regarding the acquisition/sharing of crowdsourcing design reviews in a supply chain. The authors consider an analytical model where the brand enterprise can privately acquire the manufacturer's review (MR) of crowdsourcing product designs and choose one of two information-sharing schemes—optional or mandatory sharing—to disclose MR to the key opinion leaders (KOLs), which help them to produce fans' reviews (FR). MR and FR integrate into the joint reviews (JR) that impact prospective consumers' purchase intention. The authors find that mandatory sharing significantly harms the brand enterprise's motivation to obtain MR, yet optional sharing is conducive to boosting JR on crowdsourcing designs. In addition, JR has a ceiling value, implying that excessively high FR and MR could not always enhance the effect of JR on crowdsourcing designs.

Search with two stages of information acquisition: A structural econometric model of online purchases

This paper presents a methodology for estimating a sequential model of online consumer search. The literature on such structural econometric models typically assumes that, for each alternative, there is only one stage of optimal information acquisition. For many e-commerce websites, however, there are two stages: obtaining information from (1) the search results page and (2) clicking on an alternative. We develop a methodology for estimating a model with two stages, in which the consumer makes optimal decisions in each stage. The search problem is viewed as a variant of a multi-armed bandit problem. We estimate this model using a dataset of clicks and purchases on the website expedia.com. In contrast to models with one stage of optimal information acquisition, our model can be used to analyse not only the clicking and purchasing behaviour of consumers but also the extent to which they browse alternatives on the search results page.

Altered eye movements during reading under degraded viewing conditions: Background luminance, text blur, and text contrast.

Degraded viewing conditions caused by either natural environments or visual disorders lead to slow reading. Here, we systematically investigated how eye movement patterns during reading are affected by degraded viewing conditions in terms of spatial resolution, contrast, and background luminance. Using a high-speed eye tracker, binocular eye movements were obtained from 14 young normally sighted adults. Images of text passages were manipulated with varying degrees of background luminance (1.3–265 cd/m2), text blur (severe blur to no blur), or text contrast (2.6%–100%). We analyzed changes in key eye movement features, such as saccades, microsaccades, regressive saccades, fixations, and return-sweeps across different viewing conditions. No significant changes were observed for the range of tested background luminance values. However, with increasing text blur and decreasing text contrast, we observed a significant decrease in saccade amplitude and velocity, as well as a significant increase in fixation duration, number of fixations, proportion of regressive saccades, microsaccade rate, and duration of return-sweeps. Among all, saccade amplitude, fixation duration, and proportion of regressive saccades turned out to be the most significant contributors to reading speed, together accounting for 90% of variance in reading speed. Our results together showed that, when presented with degraded viewing conditions, the patterns of eye movements during reading were altered accordingly. These findings may suggest that the seemingly deviated eye movements observed in individuals with visual impairments may be in part resulting from active and optimal information acquisition strategies operated when visual sensory input becomes substantially deprived.

Information acquisition for service contract quotations made by repair shops

Component maintenance, repair and overhaul is often performed under long-term service agreements with service providers. After receiving a request for quotation, the provider can quote a price for the contract. When the contract is awarded, the profit depends on the quoted price. To gain such contracts and make profit, service providers have to make an accurate estimation of the value of the contract. Therefore, it is crucial to collect attributes from multiple sources that improve the knowledge about the specific contract. However, due to time and effort investment, it is preferred to collect this information in a smart and dynamic way, i.e., responsive to the available collected information. This paper introduces a model of optimal information acquisition for profit maximization that can be used for such situations. Moreover, we introduce a specific model refinement that can be used for quotation optimization. The model utilizes a function that includes the information attributes as variables and returns the profit. Each piece of information is modelled as an attribute for which the true value can be retrieved and the corresponding retrieval effort is translated in a cost. We introduce three heuristic policies with different levels of dynamism for the order and the number of information attributes to be retrieved. We find out that fixing the order in which attributes are retrieved decreases the expected profit by only 4%, while also fixing the number of attributes has much worse consequences.

Dynamically Aggregating Diverse Information

An agent has access to multiple information sources, each modeled as a Brownian motion whose drift provides information about a different component of an unknown Gaussian state. Information is acquired continuously—where the agent chooses both which sources to sample from, and also how to allocate attention across them—until an endogenously chosen time, at which point a decision is taken. We demonstrate conditions on the agent's prior belief under which it is possible to exactly characterize the optimal information acquisition strategy. We then apply this characterization to derive new results regarding: (1) endogenous information acquisition for binary choice, (2) the dynamic consequences of attention manipulation, and (3) strategic information provision by biased news sources.

Information Acquisition and Its Incentives in an E-Commerce Supply Chain under the Offline Showroom Model

Recently, the showroom model has developed fast for allowing consumers to evaluate a product offline and then buy it online. This paper aims at exploring the optimal information acquisition strategy and its incentive contracts in an e-commerce supply chain with two competing e-tailers and an offline showroom. Based on signaling game theory, we build a mathematical model by considering the impact of experience service and competition intensity on consumers’ demand. We find that, on the one hand, information acquisition promotes supply chain members to obtain demand information directly or indirectly, which leads to forecast revenue. On the other hand, information acquisition promotes supply chain members to distort optimal decisions, which results in signal cost. The optimal information acquisition strategy depends on the joint impact of forecast revenue, signal cost and demand forecast cost. Notably, in some conditions, the offline showroom will not acquire demand information even when its cost is equal to zero. We also design two different information acquisition incentive contracts to obtain Pareto improvement for all supply chain members.

The Status Quo and Belief Polarization of Inattentive Agents: Theory and Experiment

We show that rational but inattentive agents can become polarized, even in expectation. This is driven by agents’ choice of not only how much information to acquire, but also what type of information. We present how optimal information acquisition, and subsequent belief formation, depends crucially on the agent-specific status quo valuation. Beliefs can systematically update away from the realized truth and even agents with the same initial beliefs might become polarized. We design a laboratory experiment to test the model’s predictions; the results confirm our predictions about the mechanism (rational information acquisition) and its effect on beliefs (systematic polarization). Keywords: polarization, beliefs updating, rational inattention, status quo, experiment. JEL codes: C92, D72, D83, D84, D91

Information Acquisition in Matching Markets: The Role of Price Discovery

We explore the acquisition and flow of information in matching markets through a model of college admissions with endogenous costly information acquisition. We extend the notion of stability to this partial information setting, and introduce regret-free stability as a refinement that additionally requires optimal student information acquisition. We show regret-free stable outcomes exist, and finding them is equivalent to finding appropriately-defined market-clearing cutoffs. To understand information flows, we recast matching mechanisms as price-discovery processes. No mechanism guarantees a regret-free stable outcome, because information deadlocks imply some students must acquire information sub optimally. Our analysis suggests approaches for facilitating efficient price discovery, leveraging historical information or market sub-samples to estimate cutoffs. We show that mechanisms that use such methods to advise applicants on their admission chances yield approximately regret-free stable outcomes. A survey of university admission systems highlights the practical importance of providing applicants with information about their admission chances.

More or Less Data? Information Acquisition in Asymmetric Elections

We demonstrate that a candidate competing in an asymmetric Tullock election contest may prefer that their rival candidate has access to information they themselves do not have. In the model, the extent of asymmetry between the candidates is ex-ante uncertain, but candidates can acquire information about it. We study the interaction between the incentives to acquire the information and candidates' spending and winning likelihoods. For a range of moderately close elections, an asymmetric equilibrium can arise where both candidates prefer that only the underdog candidate acquires the information. The optimal information acquisition strategy may consequently exhibit discontinuities in candidates' winning probabilities as a function of the competitiveness of the election.

Observability of retailer demand information acquisition in a dual-channel supply chain

This study considers a retailer’s optimal endogenous demand information acquisition format decision in a dual-channel supply chain setting. Two information acquisition formats are examined, depending on whether the outcome of information acquisition is observable to the manufacturer. We explicitly characterize the manufacturer’s optimal contract provision under each acquisition format, and derive the retailer’s optimal endogenous information acquisition format choice. Two underlying driving forces for the retailer’s preference for the observable acquisition are derived. On one hand, observable acquisition makes the retailer lose some informational advantage, which is detrimental to the retailer. On the other hand, observable acquisition may alleviate the ordering quantity distortions, which is beneficial to the retailer. In equilibrium, we show that the retailer with an inferior acquisition capability might be pleased to choose observable acquisition when the market dispersion is in the middle range. Although the manufacturer consistently obtains more profit under observable acquisition, the supply chain may still prefer unobservable acquisition because the observability of information acquisition may aggravate double marginalization under certain conditions. Moreover, the introduction of the direct sales channel may dampen the retailer’s incentive to choose the observable acquisition format.

Optimal Saving and the Timing of the Resolution of Uncertainty in Capital Return

What is the effect of the optimal information acquisition at date t+1 regarding the uncertainty at date t+2 on the saving behavior date t? This paper explores how agents choose the timing of uncertainty resolution and its effect on ex ante consumption-saving decisions. Under rational inattention, agents can optimally decide the information acquisition regarding future capital return, or the timing of uncertainty resolution. We find that, for relative risk aversion degree larger than unity, (i) households with higher initial endowment prefer to have later resolution of uncertainty in future capital return, and (ii) they save at a higher rate due to prudence. We also provide empirical evidence from Michigan Survey of Consumers (MSC) to support these model results.

Dynamically Aggregating Diverse Information

An agent has access to multiple information sources, each of which provides information about a different attribute of an unknown state. Information is acquired continuously---where the agent chooses both which sources to sample from, and also how to allocate attention across them---until an endogenously chosen time, at which point a decision is taken. We provide an exact characterization of the optimal information acquisition strategy under weak conditions on the agent's prior belief about the different attributes. We then apply this characterization to derive new results regarding: (1) endogenous information acquisition for binary choice, (2) strategic information provision by biased news sources, and (3) the dynamic consequences of attention manipulation.

Dynamically Aggregating Diverse Information

An agent has access to multiple information sources, each of which provides information about a different attribute of an unknown state. Information is acquired continuously -- where the agent chooses both which sources to sample from, and also how to allocate attention across them -- until an endogenously chosen time, at which point a decision is taken. We provide an exact characterization of the optimal information acquisition strategy under weak conditions on the agent's prior belief about the different attributes. We then apply this characterization to derive new results regarding: (1) endogenous information acquisition for binary choice, (2) strategic information provision by biased news sources, and (3) the dynamic consequences of attention manipulation.

Cardiac ultrasound: a true haemodynamic monitor?

Cardiac ultrasound has been used in the critically ill for more than thirty years. The technology has made enormous progression with respect to image quality and quantity, various Doppler techniques, as well as connectivity, the transfer of data and offline calculations. Some consider cardiac ultrasound as the stethoscope of the Twenty-first century. The potential of eye-balling moving cardiac structures gives undeniable power to this diagnostic and monitoring tool. The main shortcoming is the discontinuous mode of monitoring and the fact that optimal information acquisition can only be obtained when one is well-trained and experienced. Cardiac ultrasound has become an indispensable tool, especially in haemodynamically unstable patients. This review summarizes some important aspects of cardiac ultrasound with use of Doppler monitoring for assessment of the three most important pillars of haemodynamics, namely cardiac preload, afterload and contractile function.

Information Acquisition and Technology Adoption in a Partnership

We study information acquisition and technology adoption decisions in a partnership. Using classical information acquisition and technology adoption results for a single decision-maker (SDM policy; McCardle 1985) as a benchmark, we establish that it could be optimal for the partnership to prematurely adopt/reject the technology. Furthermore, anticipating premature decisions in a later period could trigger unraveling which leads to a series of premature decisions in earlier periods. Finally, for a given precision of the partnership’s belief of the success probability of the technology, the structure of the optimal policy may be non-monotonic in the belief, due to the non-convexity and discontinuity of the associated coupled optimization problem. Thus, the presence of a partner may have a non-trivial and profound impact on the prescribed optimal information acquisition and technology adoption decisions.

A New Theory of Information Acquisition and Recovery: Intrinsic Geometry Approach with Asset Pricing Applications

We introduce a novel geometry-based method of modelling information that encompasses entropy-based approaches. A key contribution is that we explicitly construct the optimal path to acquire information. The economic driver of this geometry-based framework is knowledge state dependent marginal cost of information acquisition. The modelling benefits of our framework is exemplified by studying an extended myopic portfolio choice problem in asset pricing with information acquisition. We show using theory and empirical evidence that return and volatility curvatures, derived from the optimal information acquisition path, significantly explain equilibrium risky asset return level and volatility level. Another key contribution of our framework is information recovery. When an econometrician only observes the agent’s portfolio allocations, we provide geometric conditions for which the agent’s mean-variance information dynamics can be successfully recovered. Beyond asset pricing, our method of information acquisition and information recovery is applicable to general expected utility maximization problems within a general stochastic environment.

A linear-quadratic Gaussian approach to dynamic information acquisition

We consider optimal information acquisition for the control of linear discrete-time random systems with noisy observations and apply the findings to the problem of dynamically implementing emissions-reduction targets. The optimal policy, which is provided in closed form, depends on a single composite parameter which determines the criticality of the system. For subcritical systems, it is optimal to perform “noise leveling,” that is, to reduce the variance of the state uncertainty to an optimal level and keep it constant by a steady feed of information updates. For critical systems, the optimal policy is “noise attenuation,” that is, to substantially decrease the variance once and never acquire information thereafter. Finally for supercritical systems, information acquisition is never in the best interest of the decision maker. In each case, an explicit expression of the value function is obtained. The criticality of the system, and therefore the tradeoff between spending resources on the control or on information to improve the control, is influenced by a “policy parameter” which determines the importance a decision maker places on uncertainty reduction. The dependence of the system performance on the policy parameter is illustrated using a practical climate-control problem where a regulator imposes state-contingent taxes to probabilistically attain emissions targets.

Mid-auction information acquisition

An English auction is studied in which bidders can acquire information during the bidding process, allowing for heterogeneity both in ex-ante private information and the cost of information acquisition. The best response has a simple characterization where the optimal information acquisition time is unaffected by the other bidders’ strategies. We prove the existence of an equilibrium in a novel way by characterizing it as a fixed point in the space of bid distributions rather than the space of bid functions. Furthermore, we show that when bidders have homogeneous ex-ante private information about valuations: (1) The English auction generates more revenue than the Vickrey auction when the number of bidders is sufficiently large; and (2) the English auction is more efficient than the Vickrey auction when the information acquisition cost are relatively small. We present numerical simulations that show that these effects can be large. Our findings provide an additional explanation for the popularity of the English auction, even in settings where the bidders’ valuations are independent.

The heterogeneity of inflation expectation: An empirical analysis based on optimal information acquisition

This paper firstly estimates the inflation expectation of households by improved probability method and then estimates the inflation expectation of experts by VAR(2) Model. Based on these two estimations, we find that expert expectation has a higher precision but it does not act in a rational way as household expectation acts. There is a bi-directional Granger Causality link between households’ expectation and actual inflation. But the expert expectation is only the Granger reason of actual inflation. There is an obvious feedback mechanism between the inflation of household and expert. This heterogeneity of inflation may be the result of optimal information acquisition during the formation of private sector’s expectation.

Optimal Learning from Multiple Information Sources

We consider the problem of optimal dynamic information acquisition from many correlated information sources. Each period, the decision-maker jointly takes an action and allocates a fixed number of observations across the available sources. His payoff depends on the actions taken and on an unknown state. In the canonical setting of jointly normal information sources, we show that the optimal dynamic information acquisition rule proceeds myopically after finitely many periods. If signals are acquired in large blocks each period, then the optimal rule turns out to be myopic from period 1. These results demonstrate the possibility of robust and simple optimal information acquisition, and simplify the analysis of dynamic information acquisition in a widely used informational environment.