Multiple Price Research Articles

Individual preferences and the exponential growth bias

The exponential growth bias (EGB) refers to individuals’ underestimation of the effects of exponential growth and has been shown to affect important financial decisions such as retirement savings. We develop and test a novel experimental design to evaluate the magnitude of the EGB based on multiple price lists. Our design simultaneously elicits the EGB as well as subjects’ utility curvatures and time preferences. Allowing for non-linear utility, we structurally estimate the magnitude of the EGB as about half as large as when linear utility is assumed. These results shed light on the relationship between individual preferences and the EGB.

Multiple Switching and Data Quality in the Multiple Price List

Researchers working with the widely used Multiple Price List (MPL) instrument have found that a substantial proportion of subjects switch back and forth between the safe and the risky choice columns in the instrument, which is behavior believed to indicate low quality decision-making (e.g. Charness et al. (2013)). In this study we develop a conceptual framework defining decision-making quality to test three leading explanations for the nature of low quality decision-making in the MPL using the covariance of responses in the MPL with a second, simpler risk instrument. We finding evidence in support of task-specific miscomprehension of the MPL. Our novel nudge treatment reduced multiple switching behavior (MSB) from 31% to 10% (p-value $<$ 0.001) and increased the proportion of high quality responses by 152%, according to the data quality metric we propose. We find that MSB does not capture the full extent of low quality decision-making, as even non-multiple switchers generate relatively low data quality under the standard protocol. We also find that while cognitive ability explains MSB, it does not predict higher data quality. This suggests that comprehension of the MPL can be a problem even with high cognitive ability subjects exhibiting low multiple switching rates. We further suggest several general applications of our framework and experimental design:a test of relative complexity between two tasks and a test of the effectiveness of various devices for improving task comprehension.

Price differentiated channel switching in a fixed period fast fashion supply chain

Fashion products are characterized by short product life cycles and high market success uncertainty. An unsuccessful product requires multiple price discounts to clear inventory. Fast-fashion retailers use a variety of strategies to counter these uncertainties including: frequently changing collections, quick response sourcing, and data driven channel switching. This paper proposes a switching solution for the Fast Fashion Supply Chain (FFS) of retailers who have preordered an initial or block inventory, and plan to use channel switching as opposed to multiple discounting steps. We consider a retailer which ships product from a central warehouse to store/clearance and outlet channels. The FFS Multi-Channel Switching (MCS) problem then is to monitor market demand data, such that at the optimal period the store inventory is switched to clearance, and the warehouse inventory is switched to the outlet channel. Using a linear projection of the moving average demand trend, we estimate the remaining cycle revenue at any time in the cycle. Channel prices are fixed, and the remaining revenue is a concave function of switching time. Using a set of conditions the objective is further simplified into cases. The Linear Moving Average Trend (LMAT) heuristic prescribes whether a channel switch should be made in the next period. The LMAT was compared with the optimal decision, the No-Switch rule and an intuitive heuristic using a simulation experiment. The LMAT performed well and for most problems provided a solution within 0.4% of the optimal. Confirming the LMAT can readily and effectively be applied to real time decision making in a FFS.

Tight Weight-Dependent Competitive Ratios for Online Edge-Weighted Matching, with Application to Revenue Management

Motivated by the dynamic assortment offerings and item pricings occurring in e-commerce, we study a general problem of allocating finite inventories to heterogeneous customers arriving sequentially. We analyze this problem under the framework of competitive analysis, where the sequence of customers is unknown and does not necessarily follow any pattern. Previous work in this area, studying online matching, advertising, and assortment problems, has focused on the case where each item can only be sold at a single price, resulting in algorithms which achieve the best-possible competitive ratio of 1-1/e. In this paper, we extend all of these results to allow for items having multiple feasible prices. Our algorithms achieve the best-possible weight-dependent competitive ratios, which depend on the sets of feasible prices given in advance. Our algorithms are also simple and intuitive; they are based on constructing a class of universal ``value functions'' which integrate the selection of items and prices offered. Finally, we test our algorithms on the publicly-available hotel data set of Bodea et al. (2009), where there are multiple items (hotel rooms) each with multiple prices (fares at which the room could be sold). We find that applying our algorithms, as a ``hybrid'' with algorithms which attempt to forecast and learn the future transactions, results in the best performance.

New innovations in agricultural biotech: Consumer acceptance of topical RNAi in rice production

To test the market viability of a non-GMO topical RNAi insect control, we conducted a Willingness-To-Pay (WTP) survey in the USA, Canada, Australia, France, and Belgium to elicit whether consumers need a premium or discount for: (1) a hypothetical GMO rice variety using the Bacillus thuringiensis (Bt) gene for insect control; and (2) a hypothetical non-GMO rice variety using topical RNAi spray for insect control. The survey was designed based on a Multiple Price List (MPL) format where respondents selected their preferred insect control technology; i.e., conventional, GMO Bt, or non-GMO RNAi, at different prices. Participants' responses were analyzed using an interval regression model to generate WTP premiums and discounts for each country with control variables for demographic influences. Further, we asked consumers their Willingness-To-Consume (WTC) food produced with GM and RNAi technologies respectively and evaluated WTC differences using a McNemar matched pairs test in each country. The results from our study clearly show that: (1) consumers in the USA, Canada, Australia, and France still require a discount for rice produced with topical RNAi compared to conventionally-produced rice (p < 0.05), (2) consumers in the USA, Canada, Australia, France, and Belgium would need an additional 30–40% discount to purchase Bt rice over rice produced with topical RNAi (p < 0.05), and (3) consumers in all countries were more willing to consume rice produced with non-GM RNAi than with GM Bt technology (p < 0.05). These findings suggest consumers differentiate among biotechnology solutions and consumers may prefer topical RNAi insect control to transgenic GMO insecticides.

Effect of Normative and Affective Aspects on Willingness to Pay for Domestic Food Products—A Multiple Price List Experiment

ABSTRACTThere is limited knowledge about which factors underlie consumers’ preferences for domestic food products. We used a non-hypothetical multiple-price list experiment to investigate the effect of affective (product-related emotions) and normative (consumer ethnocentrism and subjective norms) factors on consumer willingness to pay for domestic food products. A total of 166 Croatian consumers were given a choice between domestic and foreign food products with different price premiums for domestic food. The results indicate that consumers are willing to pay a premium for both low- and high-involvement domestic food products. Consumer willingness to pay for domestic products is influenced by ethnocentrism, product-related emotions, and sociodemographic variables, but not by social norms.

Chinese Super League: attendance, pricing, and team performance

PurposeThe purpose of this paper is to examine the impact of team performance, price dispersion – having multiple ticket prices for a single event, and market characteristics on fan attendance. By considering the context of the Chinese Super League (CSL), this study considers multiple strategies for enhancing the demand for sport in relation to factors on- and off-the-field of play.Design/methodology/approachThis study uses economic demand theory to examine consumer interest in sporting events in relation to pricing. Through employing econometric modeling, regression analysis is used to estimate results from match-level data encompassing multiple seasons.FindingsThe findings estimated from the linear regressions indicate that using multi-tiered pricing for sporting events does not significantly enhance demand in this context. Furthermore, it is found that consumers are responsive to matches against rival teams and strong opponents.Research limitations/implicationsThe results run counter to prior literature on price dispersion, indicating that attendance demand may not always be influenced by the number of price points.Practical implicationsThe findings help to develop an understanding of how team performance and pricing are important parts of meeting organizational goals in sport. From this, strategies can be formed to help stakeholders and managers in improving organizational performance.Originality/valueThis research is one of the first to consider the CSL, where both single and multiple price points exist for sporting events. Thus, it helps to build both theoretical and empirical knowledge in regards to the importance of pricing systems.

How does the ordering of questions affect elicited time preferences?

ABSTRACTSince time preferences constitute a concept fundamental to economics, many economists have attempted to elicit time preferences by using multiple price lists. In such endeavours, however, little attention has been paid to the effect of the ordering of questions on elicited time preferences although the ordering effect is well known. We analysed a representative sample of the Indonesian population (13,870 men and 15,858 women) by applying censored maximum likelihood regressions. We exploited the randomized ordering of two series of delay questions (1- and 5-year delays) and estimated the causal effect of the ordering on elicited time preferences. Respondents who considered the longer-delay questions exhibited more patience, and the effects were larger for women. Economists need to take into account the ordering effect as they design experiments by which to elicit time and other preferences.

Convex Time Budgets and Individual Discount Rates in the Long Run

The purpose of this study is to use experimental data to estimate individual discount rates and test for hyperbolic discounting over a long time horizon. To do this, we employ the convex time budget experimental approach with cash payments over a 20 year time horizon. To date, there are few experimental studies that explore discount rates beyond a 1 year time horizon. Previous experimental studies that focus on short time horizons find high discount rates, which may not be applicable to decisions that affect outcomes in the distant future. Our findings are quite similar to the average rate of 4.9% found by Grijalva et al. (Environ Resour Econ 59:39–63, 2014), who similarly use a 20 year time horizon, but use the multiple price list elicitation method along with payment via government savings bonds. We find annual discounts rates in the range of 1.9–5.5%, depending on the specific model used. We also find evidence for declining discount rates, and that this hyperbolic pattern of behavior is related to the confidence subjects have in receiving distant-future payments.

Trader matching and the selection of market institutions

We analyze a stochastic dynamic learning model with boundedly rational traders who can choose among trading institutions with different matching characteristics. The framework allows for institutions featuring multiple prices (per good), thus violating the “law of one price.” We find that centralized institutions are stochastically stable for a broad class of dynamics and behavioral rules, independently of which other institutions are available. However, some decentralized institutions featuring multiple prices can also survive in the long run, depending on specific characteristics of the underlying learning dynamics such as fast transitions or optimistic behavior.

Bounded awareness and anomalies in intertemporal choice: Zooming in Google Earth as both metaphor and model

This paper draws on recent developments in the theory of choice under uncertainty to model anomalies in intertemporal choice. Cognitive limitations leading to hyperbolic discounting and magnitude effects in intertemporal choice may be described in terms of bounded awareness, and represented by phenomena familiar from visualization software such as Google Earth. Cognitive limits on visualization impose constraints on both the area being viewed and the level of detail of the view, with a trade-off between the two. Increasing detail at the expense of limiting the area viewed may be described as zooming. Data from a field experiment were used to assess the theory with an incentive-compatible multiple price list approach involving magnitude levels of 5x, 10x and 20x the basic magnitude level with time horizons of one, three, six and 12 months. Without zooming adjustments in base consumption, very strong hyperbolic and magnitude effects were found, and present bias could not explain the hyperbolic effects. The zooming model provides an explanation of what appear to be significant intertemporal anomalies in the data.

Activation of the DLPFC Reveals an Asymmetric Effect in Risky Decision Making: Evidence from a tDCS Study.

The phenomenon of loss aversion (the tendency for losses to have a greater impact than comparable gains) has long been observed in daily life. Neurocognitive studies and brain imaging studies have shed light on the correlation between the phenomenon of loss aversion and the brain region of the prefrontal cortex. Recent brain stimulation studies using bilateral transcranial magnetic stimulation or transcranial direct current stimulation (tDCS) have obtained various results showing the causal relationship between brain regions and decision making. With the goal of studying whether unilateral stimulation can change participants’ risky decision making in the frames of gains and losses, we applied different polarities of tDCS over the regions of the right or left prefrontal cortex. We also designed a risk measurement table (Multiple Price List) to reflect the participants’ attitudes toward risky decision making via the crossover point including the frames of gains and losses. The results of our experiment indicated that the participants tended to be more risk averse in the gain frame after receiving left anodal tDCS and more risk seeking in the loss frame after receiving right cathodal tDCS, which was consistent with the hypothesis that the process of risky decision making was correlated with the interaction of multiple systems in the brain. Our conclusion revealed an asymmetric effect of right/left DLPFC when the participants faced gains and losses, which partially provided the neural evidence and a feasible paradigm to help better understand risky decision making and loss aversion. The current study can not only expand the traditional understanding of the behavioral preferences of humans in economics but also accommodate empirical observations of behavioral economists on the preferences of humans.

Liquidity Effects of Earnings Announcements in Stock Limit Order Markets: Empirical Evidence from NASDAQ Nordic

Information arrivals may drive investors to require immediacy, generating sudden liquidity demand across multiple price levels in limit order books. We document significant intraday changes in stock limit order book characteristics and liquidity beyond the best levels around scheduled and non-scheduled company announcements. At aggregated level, liquidity beyond the best levels behaves quite differently from the bid-ask spread around scheduled announcements. Moreover, scheduled announcements improve multi-level liquidity to an exceptionally good level. We also provide evidence for pre-reactions in order books before non-scheduled announcements, which suggest the possibility of information leakage.

Payoff and presentation modulation of elicited risk preferences in MPLs

Since Holt and Laury (Am Econ Rev 92(5):1644–1655, 2002), the multiple price list (MPL) procedure has widely been used to elicit individual risk preferences. We assess the impact of varying list order and spacing, and of presentation via text or graphs. Relative to the original MPL baseline, some non-linear transformations of lottery prices systematically increase elicited risk aversion, while some graphical displays tend to reduce it.

Limit order books and liquidity around scheduled and non-scheduled announcements: Empirical evidence from NASDAQ Nordic

Information arrivals may drive investors to require immediacy, generating sudden liquidity demand across multiple price levels in limit order books. We document significant intraday changes in stock limit order book characteristics and liquidity beyond the best levels around scheduled and non-scheduled company announcements. At aggregated level, liquidity beyond the best levels behaves quite differently from the bid–ask spread around scheduled announcements. Moreover, scheduled announcements improve multi-level liquidity to an exceptionally good level. We also provide evidence for pre-reactions in order books before non-scheduled announcements, which suggest the possibility of information leakage.

What can multiple price lists really tell us about risk preferences?

Multiple price lists have emerged as a simple and popular method for eliciting risk preferences. Despite their popularity, a key downside of multiple price lists has not been widely recognized — namely that the approach is unlikely to generate sufficient information to accurately identify different dimensions of risk preferences. The most popular theories of decision making under risk posit that preferences for risk are driven by a combination of two factors: the curvature of the utility function and the extent to which probabilities are weighted non-linearly. In this paper, we show that the widely used multiple price list introduced by Holt and Laury (The American Economic Review 92(5) 1644–1655 2002) is likely more accurate at eliciting the shape of the probability weighting function, and we construct a different multiple price list that is likely more accurate at eliciting the shape of the utility function. We show that by combining information from different multiple price lists, greater predictive performance can be achieved.

How to reveal people's preferences: Comparing time consistency and predictive power of multiple price list risk elicitation methods.

The question of how to measure and classify people’s risk preferences is of substantial importance in the field of economics. Inspired by the multitude of ways used to elicit risk preferences, we conduct a holistic investigation of the most prevalent method, the multiple price list (MPL) and its derivations. In our experiment, we find that revealed preferences differ under various versions of MPLs as well as yield unstable results within a 30-minute time frame. We determine the most stable elicitation method with the highest forecast accuracy by using multiple measures of within-method consistency and by using behavior in two economically relevant games as benchmarks. A derivation of the well-known method by Holt and Laury (American Economic Review 92(5):1644–1655, 2002), where the highest payoff is varied instead of probabilities, emerges as the best MPL method in both dimensions. As we pinpoint each MPL characteristic’s effect on the revealed preference and its consistency, our results have implications for preference elicitation procedures in general.Electronic supplementary materialThe online version of this article (doi:10.1007/s11166-016-9247-6) contains supplementary material, which is available to authorized users.

의사결정스타일과 위험성향의 측정, 분포, 그리고 그 관계 : 한국인 표본을 대상으로

We measure individuals' decision making styles and risk attitudes from a sample of Korean adults using the general decision making styles (GDMS) and the multiple price list design (MPLD), respectively. With the measurement results, we identify the distributions of the decision making styles and risk attitudes, and explore the relationship between them. Specifically, we conduct an exploratory experiment to find out some meaningful characteristics of the Korean adults in terms of their decision making styles and risk attitudes. The results of the experiment show that the distribution of the five decision making styles turns out to be different by the demographic characteristics of the sample. In addition, risk attitudes of the Korean people are quite distinct from those shown in the previous studies which were mostly conducted in the United States with the samples of college students. It is also shown that each of the five decision making styles has a different distribution of risk attitudes, which is statistically verified. The results of this study make a meaningful addition to the literature of this kind by providing the rationale for understanding the decision making styles and the risk attitudes of the Korean adults, which may serve as grounds for predicting the behaviors of the key individuals in various public and private sectors.

Coordinated pricing and inventory decisions for perishable products

We investigate the problem of jointly determining the optimal pricing and inventory replenishment strategy for a deterministic perishable inventory system in which demand is time and price dependent. The inventory is also assumed to decay at a certain rate. The seller has the opportunity to adjust prices for a discrete number of times at a certain cost during the sales season to influence demand and to improve revenues. We develop a mathematical model to find the optimal times to change the prices, the optimal prices and the optimal order quantity. We present analytical results to find the optimal prices when the times of price changes are given and design heuristic algorithms to determine the optimal times to change the prices. We analyze the efficiency of multiple pricing strategy by comparing the profits obtained by single pricing case and also analyze the effect of different parameters on the optimal solution through numerical experiments.

Coalition Formation and Surplus Sharing in Repeated Multi-Coalitional Games

We consider an intertemporal game-theoretic framework in which different coalitions interact repeatedly over time. Both the terms of trade and the endogenous cooperation structure arising in this setup are characterized, in a protocol-free manner, when just three natural conditions are satisfied:(C1) A coalition is formed with positive probability if, and only if, the shares obtained in this case by its members weakly exceed their respective share expectations.(C2) Each matched coalition distributes the entire surplus among its members.(C3) Members of any coalition are treated symmetrically with respect to their share expectations when the surplus of this coalition is distributed.Our analysis primarily focuses on the limit scenario where the game ends each date with a vanishing probability. We show that, in this case, the cooperation structure and the shares are unique and display a number of interesting properties. In an application to trade networks, we show that, in a complete network, a unique price arises and agents specialize in either buying or selling. In an incomplete network, on the other hand, transactions occur, generally, at multiple prices and some agents become arbitrageurs that buy and sell at different prices.