Decision Maker's Willingness Research Articles

An attribution of value framework for combination treatments

The use of cost-effectiveness methods to support policy decisions has become well established but difficulties can arise when evaluating a new treatment which is indicated to be used in combination with an established "backbone treatment." If the latter has been priced close to the decision maker's willingness to pay threshold, this may mean that there is no headroom for the new treatment to demonstrate value, at any price, even if the combination is clinically effective. Without a mechanism for attributing value to component treatments within a combination therapy, the health system risks generating negative funding decisions for combinations of proven clinical benefit to patients. The aim of this work was to define a value attribution methodology which could be used to allocate value between the components of any combination treatment. The framework is grounded in the standard decision rules of cost-effectiveness analysis and provides solutions according to key features of the problem: perfect/imperfect information about component treatment monotherapy effects and balanced/unbalanced market power between their manufacturers. The share of incremental value varies depending on whether there is perfect/imperfect information and balance/imbalance of market power, with some scenarios requiring the manufacturers to negotiate a share of the incremental value within a range defined by the framework. It is possible to define a framework that is independent of price and focuses on benefits expressed as Quality-Adjusted Life-Year (QALY) gains (and/or QALY equivalents for cost-savings), a standard metric used by many HTA agencies to evaluate novel treatments.

Age Matters: How Generational Decision-Making Cohorts Affect Disruptive Technology New Product Development

The Internet of Things (IoT), a worldwide network of interconnected objects uniquely addressable, based on standard communication protocols, has become a disruptive technology, even for decision-makers who develop products based on them. It was reported in 2015 and 2018 that decision-makers associated with the Fortune 1000 firms stated that they were hesitant to use IoT-based value propositions, primarily due to privacy and security concerns. In this article, we view decision-maker willingness to develop IoT-based products through the lens of the social construction of technology (SCOT) theory. We utilize SCOT-based generational cohorts of firm decision-makers to investigate whether generational cohorts of decision-makers are relevant in a firm's decision to launch an IoT value proposition. We argue that it is pertinent to consider age-based generations as stakeholders for IoT, which currently constitutes a gap in the literature on IoT and SCOT. We employ an exploratory survey analysis that supports the relevance of generational decision-making cohorts. We focus on age to the exclusion of other potential decision-maker cohort possibilities and discuss this as a limitation in our conclusion.

A Markov Decision Process Approach for Cost-Benefit Analysis of Infrastructure Resilience Upgrades.

As climate change threatens to cause increasingly frequent and severe natural disasters, decisionmakers must consider costly investments to enhance the resilience of critical infrastructures. Evaluating these potential resilience improvements using traditional cost-benefit analysis (CBA) approaches is often problematic because disasters are stochastic and can destroy even hardened infrastructure, meaning that the lifetimes of investments are themselves uncertain. In this article, we develop a novel Markov decision process (MDP) model for CBA of infrastructure resilience upgrades that offer prevention (reduce the probability of a disaster) and/or protection (mitigate the cost of a disaster) benefits. Stochastic features of the model include disaster occurrences and whether or not a disaster terminates the effective life of an earlier resilience upgrade. From our MDP model, we derive analytical expressions for the decisionmaker's willingness to pay (WTP) to enhance infrastructure resilience, and conduct a comparative static analysis to investigate how the WTP varies with the fundamental parameters of the problem. Following this theoretical portion of the article, we demonstrate the applicability of our MDP framework to real-world decision making by applying it to two case studies of electric utility infrastructure hardening. The first case study considers elevating a flood-prone substation and the second assesses upgrading transmission structures to withstand high winds. Results from these two case studies show that assumptions about the value of lost load during power outages and the distribution of customer types significantly influence the WTP for the resilience upgrades and are material to the decisions of whether or not to implementthem.

A Markov Decision Process Approach for Cost-Benefit Analysis of Infrastructure Resilience Upgrades

As climate change threatens to cause increasingly frequent and severe natural disasters, decision-makers must consider costly investments to enhance the resilience of critical infrastructures. Evaluating these potential resilience improvements using traditional cost-benefit analysis (CBA) approaches is often problematic because disasters are stochastic and can destroy even hardened infrastructure, meaning that the lifetimes of investments are themselves uncertain. In this paper, we develop a novel Markov decision process (MDP) model for CBA of infrastructure resilience upgrades that offer prevention (reduce the probability of a disaster) and/or protection (mitigate the cost of a disaster) benefits. Stochastic features of the model include disaster occurrences and whether or not a disaster terminates the effective life of an earlier resilience upgrade. From our MDP model, we derive analytical expressions for the decision-maker's willingness to pay (WTP) to enhance infrastructure resilience, and conduct a comparative static analysis to investigate how the WTP varies with the fundamental parameters of the problem. Following this theoretical portion of the paper, we demonstrate the applicability of our MDP framework to real-world decision-making by applying it to two case studies of electric utility infrastructure hardening. The first case study considers elevating a flood-prone substation and the second assesses upgrading transmission structures to withstand high winds. Results from these two case studies show that assumptions about the value of lost load during power outages and the distribution of customer types significantly influence the WTP for the resilience upgrades and are material to the decisions of whether or not to implement them.

Surgical Management of Lumbar Radiculopathy: a Systematic Review.

Lumbar radiculopathy is characterized by radiating pain with or without motor weakness or sensory disturbances; the point prevalence ranges from 1.6 to 13.4%. The objective of this review was to determine the efficacy, safety, and cost of surgical versus nonsurgical management of symptomatic lumbar radiculopathy in adults. We searched PubMed from January 1, 2007, to April 10, 2019 with hand searches of systematic reviews for studies prior to 2007. One reviewer extracted data and a second checked for accuracy. Two reviewers completed independent risk of bias and strength of evidence ratings. We included seven RCTs (N = 1158) and three cost-effectiveness analysis. Surgery reduced leg pain by 6 to 26 points more than nonsurgical interventions as measured on a 0- to 100-point visual analog scale of pain at up to 26 weeks follow-up; differences between groups did not persist at 1 year or later. The evidence was somewhat mixed for function and disability in follow-up through 26 weeks (standardized mean difference [SMD] - 0.16 (95% CI, - 0.30 to - 0.03); minimal differences were observed at 2 years (SMD - 0.06 (95% CI, - 0.20 to 0.07). There were similar improvements in quality of life, neurologic symptoms, and return to work. No surgical deaths occurred and surgical morbidity was infrequent. The incidence of reoperations ranged from 0 to 10%. The average cost per quality-adjusted life year gained from a healthcare payor perspective ranged from $51,156 to $83,322 for surgery compared to nonsurgical interventions. Most findings are based on a body of RCT evidence graded as low to very low certainty. Compared with nonsurgical interventions, surgery probably reduces pain and improves function in the short- and medium-term, but this difference does not persist in the long-term. Although surgery appears to be safe, it may or may not be cost-effective depending on a decision maker's willingness to pay threshold.

Optimal LQG Control Under Delay-Dependent Costly Information

In the design of closed-loop networked control systems (NCSs), induced transmission delay between sensors and the control station is an often-present issue which compromises control performance and may even cause instability. A very relevant scenario in which network-induced delay needs to be investigated is costly usage of communication resources. More precisely, advanced communication technologies, e.g. 5G, are capable of offering latency-varying information exchange for different prices. Therefore, induced delay becomes a decision variable. It is then the matter of decision maker's willingness to either pay the required cost to have low-latency access to the communication resource, or delay the access at a reduced price. In this article, we consider optimal price-based bi-variable decision making problem for single-loop NCS with a stochastic linear time-invariant system. Assuming that communication incurs cost such that transmission with shorter delay is more costly, a decision maker determines the switching strategy between communication links of different delays such that an optimal balance between the control performance and the communication cost is maintained. In this article, we show that, under mild assumptions on the available information for decision makers, the separation property holds between the optimal link selecting and control policies. As the cost function is decomposable, the optimal policies are efficiently computed.

Cost-effectiveness of forced air warming during sedation in the cardiac catheterisation laboratory.

The aim of this study was to determine the cost-effectiveness of forced air warming (FAW) during sedation in a cardiac catheterisation laboratory. Forced air warming improves thermal comfort in comparison with standard care. It is not known whether the extra costs required for FAW are good value. Cost-effectiveness analysis alongside a randomized controlled trial conducted in 2016-2017. A cost-effectiveness analysis was undertaken using Monte Carlo simulations from input distributions to estimate costs and effects associated with using FAW to reduce risk of thermal discomfort for patients receiving sedation in a cardiac catheterisation laboratory. A range of willingness to pay threshold values were tested with results plotted on a cost-effectiveness acceptability curve. Costs were calculated in Australian currency ($AUD). Estimated total costs were $5.21 (SD 3.26) higher per patient for FAW in comparison to standard care. Estimated probability of success (rating of thermal comfort) was 0.16 (0.06) higher for FAW. Forced air warming becomes more likely to result in a net benefit than standard care at a willingness to pay threshold of $34. Forced air warming could be considered cost-effective for procedures performed with sedation in a cardiac catheterisation laboratory if the extra cost of an incremental gain in thermal comfort is less than the decision maker's willingness to pay for it. Therefore, those responsible for decision-making regarding use of FAW in the cardiac catheterisation laboratory can use results of our model to decide if it represents good value for their organisation.

Cost-effective strategy to mitigate transportation disruptions in supply chain

Supply chain disruptions have gained significant attention by scholars. But, even though transportation plays a central role in supply chain, only few studies address transportation disruptions. This research demonstrates a real case of an order delivery process from a focal company (FC) to a single distributor, where transportation disruptions stochastically occurs. Considering the possibility of sales loss during the disruption duration, we proposed a redundant stock, flexible route, and combined flexibility-redundancy (ReFlex) as mitigation strategies and a base case as a risk acceptance strategy. The objective is to find out the best strategy that promotes cost-effectiveness against transportation disruptions. To fulfill this objective, we use simulation modeling and cost-effectiveness analysis (CEA) as our research method. We simulate the delivery process of 5 brands using each strategy to produce two different responses: loss of sales percentage and the incurred costs. Next, using these responses, we evaluate and compare the cost-effectiveness ratio of each strategy using CEA. We found that redundant stock gave the best effectiveness on all brands, ReFlex as the second best, while flexible route gave the least effectiveness. Finally, we recommend which strategy should be applied based on the decision maker willingness to pay.

The Effects of a Shared Interest and Regret Salience on Tax Evasion

ABSTRACTThis study examines whether sharing the potential tax savings and the risk of penalties associated with tax evasion with another individual affects a decision maker's willingness to evade taxes. This study also explores whether increasing the salience of potential regret from an adverse audit decreases tax evasion behavior. Using a 2 × 2 experimental design with experienced taxpayers as participants, this study finds that participants are less willing to evade taxes when they share the potential tax savings and risk of penalties with another taxpayer compared to when the reporting decision affects solely the decision maker. Supplemental analysis shows that participants feel that tax evasion is more unethical when a shared interest is present. In addition, this study demonstrates that increasing regret salience from an adverse audit decreases participants' willingness to evade taxes. This study contributes to multiple literature streams, including taxpayer compliance, ethical decision making, and decision making under risk.

Bayesian evaluation of budgets for endemic disease control: An example using management changes to reduce milk somatic cell count early in the first lactation of Irish dairy cows

The aim of this research was to determine budgets for specific management interventions to control heifer mastitis in Irish dairy herds as an example of evidence synthesis and 1-step Bayesian micro-simulation in a veterinary context. Budgets were determined for different decision makers based on their willingness to pay. Reducing the prevalence of heifers with a high milk somatic cell count (SCC) early in the first lactation could be achieved through herd level management interventions for pre- and peri-partum heifers, however the cost effectiveness of these interventions is unknown. A synthesis of multiple sources of evidence, accounting for variability and uncertainty in the available data is invaluable to inform decision makers around likely economic outcomes of investing in disease control measures. One analytical approach to this is Bayesian micro-simulation, where the trajectory of different individuals undergoing specific interventions is simulated. The classic micro-simulation framework was extended to encompass synthesis of evidence from 2 separate statistical models and previous research, with the outcome for an individual cow or herd assessed in terms of changes in lifetime milk yield, disposal risk, and likely financial returns conditional on the interventions being simultaneously applied. The 3 interventions tested were storage of bedding inside, decreasing transition yard stocking density, and spreading of bedding evenly in the calving area. Budgets for the interventions were determined based on the minimum expected return on investment, and the probability of the desired outcome. Budgets for interventions to control heifer mastitis were highly dependent on the decision maker's willingness to pay, and hence minimum expected return on investment. Understanding the requirements of decision makers and their rational spending limits would be useful for the development of specific interventions for particular farms to control heifer mastitis, and other endemic diseases.

거부 및 무차별 선호 조건을 고려한 다기준 그룹 의사결정

The paper deals with the development of a model for group decision making under multiple criteria. The Multi-criteria group decision making (MCGDM) is the process to determine the best compromise solution in a set of competing alternatives that are evaluated by decision makers having their own preferences on conflicting objectives. For MCGDM, we propose a Mixed-Integer Programming (MIP) model that implements a revised median approach by noticing that the original median approach cannot consider the willingness to reject and the indifferent preference conditions. The proposed MIP model tries to select a common best Pareto-optimal solution by maximizing the overall desirability considering the willingness to reject and the indifferent preference that represent the tolerance measure of each decision maker. To evaluate the effectiveness of the proposed model, we compared the results of the proposed model with those of the median approach. The results showed that the proposed MIP model produces more realistic and better compromised alternative by incorporating the decision maker's willingness to reject and the indifferent preferences over each criteria.

Explaining the harmonic sequence paradox

According to the harmonic sequence paradox, an expected utility decision maker's willingness to pay for a gamble whose expected payoffs evolve according to the harmonic series is finite if and only if his marginal utility of additional income becomes zero for rather low payoff levels. Since the assumption of zero marginal utility is implausible for finite payoff levels, expected utility theory - as well as its standard generalizations such as cumulative prospect theory - are apparently unable to explain a finite willingness to pay. This paper presents first an experimental study of the harmonic sequence paradox. Additionally, it demonstrates that the theoretical argument of the harmonic sequence paradox only applies to time-patient decision makers, whereas the paradox is easily avoided if time-impatience is introduced.

Incremental Cost-effectiveness of Combined Therapy vs Medication Only for Youth With Selective Serotonin Reuptake Inhibitor–Resistant Depression

Many youth with depression do not respond to initial treatment with selective serotonin reuptake inhibitors (SSRIs), and this is associated with higher costs. More effective treatment for these youth may be cost-effective. To evaluate the incremental cost-effectiveness over 24 weeks of combined cognitive behavior therapy plus switch to a different antidepressant medication vs medication switch only in adolescents who continued to have depression despite adequate initial treatment with an SSRI. Randomized controlled trial. Six US academic and community clinics. Three hundred thirty-four patients aged 12 to 18 years with SSRI-resistant depression. Participants were randomly assigned to (1) switch to a different medication only or (2) switch to a different medication plus cognitive behavior therapy. Clinical outcomes were depression-free days (DFDs), depression-improvement days (DIDs), and quality-adjusted life-years based on DFDs (DFD-QALYs). Costs of intervention, nonprotocol services, and families were included. Combined treatment achieved 8.3 additional DFDs (P = .03), 0.020 more DFD-QALYs (P = .03), and 11.0 more DIDs (P = .04). Combined therapy cost $1633 more (P = .01). Cost per DFD was $188 (incremental cost-effectiveness ratio [ICER] = $188; 95% confidence interval [CI], -$22 to $1613), $142 per DID (ICER = $142; 95% CI, -$14 to $2529), and $78,948 per DFD-QALY (ICER = $78,948; 95% CI, -$9261 to $677,448). Cost-effectiveness acceptability curve analyses suggest a 61% probability that combined treatment is more cost-effective at a willingness to pay $100,000 per QALY. Combined treatment had a higher net benefit for subgroups of youth without a history of abuse, with lower levels of hopelessness, and with comorbid conditions. For youth with SSRI-resistant depression, combined treatment decreases the number of days with depression and is more costly. Depending on a decision maker's willingness to pay, combined therapy may be cost-effective, particularly for some subgroups. clinicaltrials.gov Identifier: NCT00018902.

The Consequences of Completion: How Level of Completion Influences Information Concealment by Decision Makers

Numerous studies have demonstrated that decision makers will allocate additional resources to failing projects if those projects are close to completion, as opposed to far from completion. The present work considers whether high project completion leads to other effects; namely, decision-maker willingness to conceal negative information about a project. Three studies (1 at the group level, 2 at the individual level; 1 using qualitative data, 2 using quantitative data) established a link between project completion, incremental investment behavior, and the tendency to conceal negative information.

POWERFUL AND UNPERSUADED: THE IMPLICATIONS OF POWER FOR CONFIDENCE, ADVICE TAKING, AND ACCURACY.

The article discusses how internal psychological states or mindsets that are triggered by the social environment may influence the taking of advice. A decision maker's willingness to revise his or her judgment in response to input from others is examined. Drawing from research suggesting that power can reduce sensitivity to one's social environment, a hypothesis is presented that greater power will be associated with less advice taking, despite the advice being freely available and presented to the decision maker. The extent to which reduced advice taking will result in less accurate judgments is also assessed.

Unpacking the uncertainty construct: Implications for entrepreneurial action

Uncertainty is central to entrepreneurship; however robust and generalizable findings that explain the conditions in which uncertainty may impede [or promote] entrepreneurial action remain elusive. We operationalize uncertainty as a multi-dimensional construct composed of state, effect, and response types of uncertainty (Milliken, 1987) to investigate the relationship between uncertainty and entrepreneurial action. We decompose more than 2800 exploitation decision policies nested within a sample of new product decision-makers working in entrepreneurial software firms. We focus on the primary decision-maker's willingness to exploit a given opportunity in the face of varying combinations and manifestations of uncertainty and find that the type of uncertainty experienced influences the willingness to engage in entrepreneurial action differently. Further, we find that differences in how each type of uncertainty is manifested in the environment, the scale of exploitation (i.e. large vs. small), and the entrepreneur's expertise serve to moderate the relationship between uncertainty and action in counter-intuitive ways. We discuss the implications for both theory and practice.

Cost-effectiveness of a supplementary class-based exercise program in the treatment of knee osteoarthritis

The aim of this study was to assess the cost-effectiveness of a class-based exercise program supplementing a home-based program when compared with a home-based program alone. In addition, we estimated the probability that the supplementary class program is cost-effective over a range of values of a decision maker's willingness to pay for an additional quality-adjusted life-year (QALY). The resource use and effectiveness data were collected as part of the clinical trial detailed elsewhere. Unit costs were estimated from published sources. The net benefit approach to cost-effectiveness analysis is used to estimate the probability of the intervention being cost-effective. The addition of a supplementary class-based group results in an increase in QALYs and lower costs. For all plausible values of a decision maker's willingness to pay for a QALY, the supplementary class group is likely to be cost-effective. The addition of a class-based exercise program is likely to be cost-effective and, on current evidence, should be implemented.

Incorporating reliability evaluation into the uncertainty analysis of electricity market price

A novel model and algorithm for analyzing the uncertainties in electricity market is proposed in this paper. In this model, bidding decision is formulated as a probabilistic model that takes into account the decision-maker's willingness to bid, risk preferences, the fluctuation of fuel-price, etc. At the same time, generating unit's uncertain output model is considered by its forced outage rate (FOR). Based on the model, the uncertainty of market price is then analyzed. Taking the analytical results into consideration, not only the reliability of the power system can be conventionally analyzed, but also the possible distribution of market prices can be easily obtained. The probability distribution of market prices can be further used to calculate the expected output and the sales income of generating unit in the market. Based on these results, it is also possible to evaluate the risk involved by generating units. A simple system with four generating units is used to illustrate the proposed algorithm. The proposed algorithm and the modeling technique are expected to helpful to the market participants in making their economic decisions.

Changes in Background Risk and the Demand for Insurance

The demand for insurance against loss from a particular risky asset is likely to depend on other risks the decision-maker faces. For independently distributed other risks, referred to as background risk, Eeckhoudt and Kimball [1992] determine the effect on insurance demand of introducing background risk. Recently, Eeckhoudt, Gollier, and Schlesinger [1996] determine conditions on preferences such that first- and second-degree stochastic deteriorations in background risk lead to a decrease in the decision-maker's willingness to accept other risks. These results, although formulated in a general decision model, also apply to insurance demand. This article continues analysis of this question by determining the effect on insurance demand of several other general changes in background risk.

On the Test-Retest Reliability of Perceived Usefulness and Perceived Ease of Use Scales

systems is increasingly important (Jarvenpaa, et al., 1985; Straub, 1989). An underlying tenet of IS success is the decision maker's willingness to adopt and utilize these systems. Measures that predict and explain use are important in determining what causes people to accept or reject information technology. This note reports on the test-retest reliability of the perceived usefulness and perceived ease of use scales. Davis (1989) developed and validated two scales for assessing user acceptance of information technology-perceived usefulness and perceived ease of use. Adams, et al. (1992) replicated the work of Davis (1989) to demonstrate the validity and reliability of these scales. While replicating the study, Adams, et al. (1992) also extended it to different settings and found both scales to have the same validity and reliability characteristics as the Davis (1989) study. Using two different samples, they demonstrated the internal consistency and replication reliability of the two scales.