Reward-based Incentive Research Articles

Defects in Value Associated With Hospital-Acquired Conditions: How Improving Quality Could Save U.S. Healthcare $50 Billion.

Hospital-acquired conditions in the United States are considered avoidable complications but remain common statistics reflecting on health system performance and are a leading cause of patient fatality. Currently, over 3.7 million patients experience a hospital-acquired condition in the United States each year, which costs the U.S. healthcare delivery system an excess of $48 billion. Evidence-based clinical practice guidelines for common hospital-acquired conditions (e.g., infections, falls, pressure injuries) to reduce risk to the patient. In each of these instances, preventing the outcome with these guidelines costs less than treating the outcome, in addition to keeping the patient safe from harm. By applying the framework of defects in value to hospital-acquired conditions, we estimate that U.S. health systems could avert this $48 billion in spending on treating harmful hospital-acquired conditions; more so, these systems of care could recuperate over $35 billion after investing proportionally in a system that delivers greater quality by preventing hospital-acquired conditions over treating them. Currently, the Centers for Medicare and Medicaid Services only withholds reimbursements for hospital-acquired conditions and penalizes health systems with high rates of these outcomes. However, payers do not offer any reward-based incentives for hospital-acquired condition prevention. A series of policy and health system solutions, including tracking of hospital-acquired condition rates in electronic health records, identifying centers of excellence at reducing rates of harm with the use of clinical practice guidelines, and rewarding them monetarily for reduced rates could create equal-sided risk and opportunity to engage health systems in improved performance.

The Square Root Agreement Rule for Incentivizing Truthful Feedback on Online Platforms

A major challenge in obtaining evaluations of products or services on e-commerce platforms is eliciting informative responses in the absence of verifiability. This paper proposes the square root agreement rule (SRA): a simple reward mechanism that incentivizes truthful responses to objective evaluations on such platforms. In this mechanism, an agent gets a reward for an evaluation only if the answer matches that of a peer agent, where this reward is inversely proportional to a popularity index of the answer. This index is defined to be the square root of the empirical frequency at which any two agents performing the same evaluation agree on the particular answer across evaluations of similar entities operating on the platform. Rarely agreed-on answers thus earn a higher reward than answers for which agreements are relatively more common. We show that in the many tasks regime, the truthful equilibrium under SRA is strictly payoff-dominant across large classes of natural equilibria that could arise in these settings, thus increasing the likelihood of its adoption. Although there exist other mechanisms achieving such guarantees, they either impose additional assumptions on the response distribution that are not generally satisfied for objective evaluations or they incentivize truthful behavior only if each agent performs a prohibitively large number of evaluations and commits to using the same strategy for each evaluation. SRA is the first known incentive mechanism satisfying such guarantees without imposing any such requirements. Moreover, our empirical findings demonstrate the robustness of the incentive properties of SRA in the presence of mild subjectivity or observational biases in the responses. These properties make SRA uniquely attractive for administering reward-based incentive schemes (e.g., rebates, discounts, reputation scores, etc.) on online platforms. This paper was accepted by Kartik Hosanagar, information systems. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4375 .

Stimuli strategy and learning dynamics promote the wisdom of crowds.

Collective wisdom is the ability of a group to perform more effectively than any individual alone. Through an evolutionary game-theoretic model of collective prediction, we investigate the role that reinforcement learning stimulus may play the role in enhancing collective voting accuracy. And collective voting bias can be dismissed through self-reinforcing global cooperative learning. Numeric simulations suggest that the provided method can increase collective voting accuracy. We conclude that real-world systems might seek reward-based incentive mechanism as an alternative to surmount group decision error.Graphical

Cooperation Promotion from the Perspective of Behavioral Economics: An Incentive Mechanism Based on Loss Aversion in Vehicular Ad-Hoc Networks

As a special mobile ad-hoc network, Vehicular Ad-hoc Networks (VANETs) have the characteristics of high-speed movement, frequent topology changes, multi-hop routing, a lack of energy, storage space limitations, and the possible selfishness of the nodes. These characteristics bring challenges to the design of the incentive mechanism in VANETs. In the current research on the incentive mechanism of VANETs, the mainstream is the reward-based incentive mechanism. Most of these mechanisms are designed based on the expected utility theory of traditional economics and assume that the positive and negative effects produced by an equal amount of gain and loss are equal in absolute value. However, the theory of loss aversion points out that the above effects are not equal. Moreover, this will lead to a deviation between the final decision-making behavior of nodes and the actual optimal situation. Therefore, this paper proposed a Loss-Aversion-based Incentive Mechanism (LAIM) to promote the comprehensive perception and sharing of information in the VANETs. This paper designs the incentive threshold and the threshold factor to motivate vehicle nodes to cooperate. Furthermore, based on the number of messages that the nodes face, the utility function of nodes is redesigned to correct the assumption that a gain and a loss of an equal amount could offset each other in traditional economics. The simulation results show that compared with the traditional incentive mechanism, the LAIM can increase the average utility of nodes by more than 34.35%, which promotes the cooperation of nodes.

Participation in a workplace smoking cessation program incentivized by lowering the cost of health care coverage: Findings from the LLUH BREATHE cohort.

INTRODUCTIONSystematic analyses of workplace smoking cessation programs indicate that efficacy can be enhanced by using incentives. There is variation in the type of incentives used and their effect on participation and efficacy. The aim of our study was to examine whether lowering employee health plan costs (employee contributions, co-pays) encourage employee smokers to participate in workplace smoking cessation.METHODSWe conducted a 2014–2015 prospective cohort study of 415 employee smokers of Loma Linda University Health (LLUH). The employees were offered participation in a workplace smoking cessation program (LLUH BREATHE Initiative) with the incentive of enrollment in an employer-provided health plan that had a 50% lower employee monthly contribution and co-payment relative to the employer-provided health plan for non-participants. Participation rates and variables associated with participation were analyzed.RESULTSIn the LLUH BREATHE cohort, we found a very high rate of participation (72.7%; 95% CI: 69–77%) in workplace smoking cessation that was encouraged by a lower out-of-pocket health plan cost for the participating employee and/or spouse. Participation did, however, vary by gender and spouse, whereby female employee households with a qualifying smoker were more than two times more likely (employee: OR=2.89, 95% CI: 1.59–5.24; or spouse: OR=2.71, 95% CI: 1.47–5.00) to participate in smoking cessation than male employee households. The point prevalence, at four months, of abstinence from smoking among the participants was 48% (95% CI: 42–54%).CONCLUSIONSOur findings indicate that a workplace smoking cessation program that uses a novel reward-based incentive of lower out-of-pocket health plan costs results in a participation rate that is much higher than US norms.

The ESG - Innovation Disconnect: Evidence from Green Patenting

No firm or sector of the global economy is untouched by innovation. In equilibrium, innovators will flock to (and innovation will occur where) the returns to innovative capital are the highest. In this paper, we document a strong empirical pattern in green patent production. Specifically, we find that oil, gas, and energy producing firms – firms with lower Environmental, Social, and Governance (ESG) scores, and who are often explicitly excluded from ESG funds’ investment universe – are key innovators in the United States’ green patent landscape. These energy producers produce more, and significantly higher quality, green innovation. Our findings raise important questions as to whether the current exclusions of many ESG-focused policies – along with the increasing incidence of explicit divestiture campaigns – are optimal, or whether reward-based incentives would lead to more efficient innovative outcomes.

The Square-Root Agreement Rule for Incentivizing Objective Feedback in Online Platforms

A major challenge in obtaining evaluations of products or services on e-commerce platforms is that of eliciting informative feedback in the absence of verifiability. We propose a simple incentive mechanism for obtaining objective feedback on such platforms. In this mechanism, an agent gets a reward only if her answer for an evaluation matches that of her peer, where this reward is inversely proportional to a popularity index of each answer. This index is defined to be the square-root of the empirical frequency at which any two agents performing the same evaluation agree on the particular answer. Rarely agreed-upon answers thus earn a higher reward than answers for which agreements are relatively more common. We call this mechanism the Square-Root Agreement Rule (SRA). A key feature of platforms that SRA leverages is the existence of a large number of similar entities to be evaluated (e.g., restaurants, sellers, services, etc.); in this regime, we show that truthful behavior is a strict Bayes-Nash equilibrium of the game induced by SRA. Further, as the number of evaluation tasks across the platform grows, this equilibrium is asymptotically optimal for the agents across all symmetric equilibria. Moreover, under a mild condition, we show that any symmetric equilibrium that gives a higher expected payoff to the agents than the truthful equilibrium must be close to being fully informative when the number of evaluations is large. SRA can thus be an effective approach for administering reward-based incentive schemes (e.g., rebates, reputation score, etc.) on these platforms.

Incentivizing healthy eating in children: An investigation of the “ripple” and “temporal” effects of a reward-based intervention

Although previous studies have established the effectiveness of using small reward-based incentives in inducing the choice and consumption of healthier foods among children, little is known about their impact outside of experimental settings or their effectiveness over time when administered daily. This paper presents the results of a field experiment conducted to provide insight on these matters. The study employs a removed treatment within-subject design and was conducted at a summer program catering to low-income children between the ages of 5 and 12. The month long experiment—wherein participants were offered a small prize for choosing a fruit cup for dessert after lunch in lieu of cookies—involved 23 children between the ages of 5 and 8. Corroborating existing studies, the introduction of small reward-based incentives in this context was found to induce large increases in the number of children choosing the healthy dessert options after lunch, but disaggregating the results by week and day suggests that their impact diminished over time. Attempts to ascertain their effect outside of experimental settings did not indicate that the introduction of rewards had any adverse effects, but also did not provide definitive conclusions.

Robust fully distributed file caching for delay-tolerant networks: A reward-based incentive mechanism

This article exhibits a reward-based incentive mechanism for file caching in delay-tolerant networks. In delay-tolerant networks, nodes use relay’s store-carry-forward paradigm to reach the final destination. Thereby, relay nodes may store data in their buffer and carry it till an appropriate contact opportunity with destination arises. However, the relays are not always willing to assist data forwarding due to a limited energy or a low storage capacity. Our proposal suggests a reward mechanism to uphold and to sustain cooperation among relay nodes. We model this distributed network interaction as a non-cooperative game. Namely, the source node offers to the relay nodes a positive reward if they accept to cache and to forward a given file successfully to a target destination, whereas the relay nodes may either accept or reject the source deal, depending on the reward attractiveness and on their battery status (their actual energy level). Next, full characterizations of both pure and mixed Nash equilibria are provided. Then, we propose three fully distributed algorithms to ensure convergence to the Nash equilibria (for both pure equilibrium and mixed equilibrium). Finally, we validate our proposal through extensive numerical examples and many learning simulations and draw some conclusions and insightful remarks.

A dynamic reward-based incentive mechanism: Reducing the cost of P2P systems

Reward-based incentive mechanisms are used most commonly to promote cooperation in peer-to-peer (P2P) systems. Specifically, contributing agents are rewarded by the system. For a centralized P2P system, the central server is responsible for implementing the mechanism and rewarding those cooperative agents. Thus, providing incentives could be costly for the system server. In this paper, we propose a dynamic reward mechanism in which the reward changes accordingly as the system evolves, i.e., when there are more cooperative agents, the reward for each agent decreases, and when there are no free-riders, rewards are no longer needed. Through theoretical analysis using replication dynamics, we determined the evolution stable strategy (ESS) for different scenarios and qualitatively proved that our dynamic reward mechanism can reduce the overall cost of the system. The simulation proved that this dynamic reward mechanism can promote cooperation and reduce the cost of the system.

Reward or Punish? Understanding Preferences toward Economic or Regulatory Instruments in a Cross-National Perspective

This study is interested in cross-national differences in public preferences toward different forms of political steering. Using data from the International Social Survey Programme it was found that there is quite substantial variation between countries in policy preferences. It is suggested that this variation can be explained by the variation in the quality of public institutions (i.e. Quality of Government, QoG). Low QoG is associated with a preference for coercive regulatory instruments and an aversion toward reward-based instruments. The explanation provided is that low QoG is correlated with low social trust, which produces suspicion of defection and an urge to punish free-riders with strong or coercive instruments. Meanwhile, the aversion toward reward-based instruments decreases as the level of QoG increases. The public administration then has the bureaucratic capacity to deal with policies that demand bureaucratic discretion and actors are less likely to free-ride, generating a preference for reward-based incentives and less need for regulation.

On the Design of a Reward-Based Incentive Mechanism for Delay Tolerant Networks

A central problem in Delay Tolerant Networks (DTNs) is to persuade mobile nodes to participate in relaying messages. Indeed, the delivery of a message incurs a certain number of costs for a relay. We consider a two-hop DTN in which a source node, wanting to get its message across to the destination as fast as possible, promises each relay it meets a reward. This reward is the minimum amount that offsets the expected delivery cost, as estimated by the relay from the information given by the source (number of existing copies of the message, age of these copies). A reward is given only to the relay that is the first one to deliver the message to the destination. We show that under fairly weak assumptions, the expected reward the source pays remains the same irrespective of the information it conveys, provided that the type of information does not vary dynamically over time. On the other hand, the source can gain by adapting the information it conveys to a meeting relay. For the particular cases of two relays or exponentially distributed intercontact times, we give some structural results on the optimal adaptive policy.

Incentives versus value in manufacturing systems: An application to high-speed milling

Optimal parameter selection is an important aspect of optimizing system performance. This paper examines the effect of different incentive structures, including reward and penalty based structures, for employees within an engineering firm on the value captured by that firm. Incentives are used to communicate the firm's values to the employee without revealing the firm's value function. We use a high-speed milling example to illustrate the approach and derive results. We show that, in certain cases, simple incentive structures can be aligned such that they induce profit maximizing behaviour. In other cases, we show that incentive structures result in a loss of value that we term the value gap. In the milling case considered, reward-based incentives coincide with optimal parameters while penalty-based incentives result in a greater than four-fold increase in costs. The effect of uncertainty within a system can also be analysed. We consider uncertainty in the process dynamics as well as tool life and that the inclusion of uncertainty in the analysis may not change the results in some cases.

Reward-Based Incentives for Smoking Cessation

Health care payers have an increasing interest in using financial incentives to change personal health behaviors, with an estimated 82% of employers using financial incentives for healthy behavior in 2013.1 Several factors are fueling this increased interest: steadily increasing costs that have been resistant to traditional forms of control, the realization that the majority of costs are driven by chronic conditions, which are themselves in large part a result of lifestyle choices, and emerging reports that incentives have successfully modified behaviors in a variety of contexts.2,3 In addition, the Affordable Care Act allows employers to use up to 30% of total premiums (50% if programs include smoking) for outcomes-based rewards or penalties.4

Carrots, Sticks and False Carrots: How high should weight control wellness incentives be? Findings from a population-level experiment.

Employers are increasingly using wellness incentives, including penalties for unhealthy behavior. Survey data suggests that people are willing to accept the principle of penalizing those perceived to take health risks, but the equally relevant question of the magnitude of acceptable penalties is unclear. While the principle of penalizing overweight and obese people has some support, findings from a population-level experiment (n=1,000) suggest that the acceptable size of penalties is comparatively small, around $50: more than 10-fold below levels favored by advocates. Reward-based incentives are favored over penalty-based ones by a factor of 4. Of two different ways of framing penalty programs, poorer and higher weight groups appear to find the one that is more overtly penalizing less acceptable. Levels of incentives matter on effectiveness as well as on ethical grounds, as it cannot be assumed that it is equally easy for all to meet health targets to secure a benefit or avoid a penalty. Programs should be designed to engage, not to frustrate those most in need of health improvement. Employee involvement in determining incentive types and levels, and explicit justification for program design can help both employees and employers to reap benefits.

On horizontal deployment of quality approaches within a firm

Consistency and standardisation are keys to individual as well as group quality improvement. This study investigates group performance, focusing on consistency between plant quality improvement approaches within a firm. In each of five automotive original equipment manufacturing plants, employees were surveyed regarding quality practices. The analysis of results indicate various factors (approaches) were used to improve quality. They included a process-oriented, quality control approach; empowering people for involvement; design and conformance; external quality information; rewards; and a proactive–formal approach. Discriminant function analysis found two independent functions, the first reflecting process and design approaches to quality improvement and the second reflecting external and reward-based approaches. The general results showed that out of five plants, plants 1 and 4 both emphasised process and design over external approaches, but plant 4 also emphasised reward-based incentives. Plants 2 and 3 have emphasised external approaches while discouraging reward-based incentives.