Asymmetric Preferences Research Articles

The Tipping Points of Video Conferencing Solutions

ABSTRACT Video conferencing solutions have been used to support remote work and distance education but have not yet been widely adopted. This study aims to contribute to the development and proliferation of video conferencing solutions for remote work and education by analyzing consumer preferences. For this purpose, a survey of 1,018 people was conducted in July and August 2021 in Korea. As the use of video conferencing became enforced due to COVID-19, the analysis reflected previous user experiences. In addition, various scenario-specific market share simulations were performed, assuming future video conferencing solutions. The survey results showed that several factors, including technology attributes, cost, and market share, influence consumers’ choice of video conferencing solutions. The survey also found that consumers have asymmetric preferences regarding video conferencing solutions depending on their previous experience. Finally, the study identified tipping points companies could use to gain a significant market share.

Interaction of Cognitive and Motivational Processes in Asymmetric Preferences for Gains and Losses

An experiment on repetitive decision-making was conducted to explore the interaction between cognitive and motivational processes in decision-making. The gain-loss framing of risky choice options was manipulated to investigate cognition, and participants’ chronic regulatory focus was measured to assess motivation. Risky choice demonstrated interactive effects between gain-loss framing and regulatory focus. Participants made less risky or riskier choices in the gain or loss condition, respectively. Furthermore, promotion or prevention-focused individuals chose the risky option more frequently in the gain or loss condition, respectively. The results for response times showed the main effects for the two factors, with no interaction. These results, along with supplementary post-hoc analyses, provide evidence that cognitive and motivational processes are simultaneously involved in risky decision-making.

A Multi-Criteria Method Integrating Distances to Ideal and Anti-Ideal Points

Multi-criteria decision-making methods based on reference points and distances from them are essential for evaluating alternatives across multiple criteria. These methods provide structured approaches to comparing and ranking alternatives relative to specified reference points. The main objective of this paper is to present the Multi-Criteria Method Integrating Distances to Ideal and Anti-ideal Points (MIDIA), which, through a weighted system, allows for the consideration of balance and asymmetry in assessing alternatives based on their distances from the ideal and anti-ideal points. As a multi-criteria algorithm, MIDIA is user-friendly and reflects the human mind’s natural tendency to assess objects based on fundamental concepts—comparison with the ideal solution and the anti-ideal solution—that are familiar from everyday experiences and provide valuable insights from a behavioral perspective. Moreover, the proposed method can be seen as an extension of Hellwig’s approach, designed to facilitate the ranking of alternatives based on two reference points: the ideal point and the anti-ideal point, measuring the distance between the alternative and the ideal point and the distance between the ideal and anti-ideal points. The MIDIA method integrates elements from both TOPSIS and VIKOR, by incorporating the structure of TOPSIS and the compromise perspective of VIKOR, offering a balanced approach to multi-criteria decision-making by focusing on the distances from ideal and anti-ideal points. Illustrative examples are given to demonstrate the usability of the proposed tool in situations where the decision-maker has asymmetrical preferences concerning the importance of ideal and anti-ideal points in ranking alternatives. Moreover, the MIDIA method is applied to one of the Sustainable Development Goals, in the area of education (SDG4), to obtain the rankings of EU member countries in 2022. The results obtained using the MIDIA method were compared with those obtained using the TOPSIS and VIKOR approaches. The study concludes that the ranking of alternatives depends on the coefficients of the importance of the distances to reference points and the data setup.

A novel iterative double auction design and simulation platform for packetized energy trading of prosumers in a residential microgrid

AbstractPacketized energy encapsulates energy into modulated, routable, and trackable energy packets, enhancing the flexibility of managing distributed energy resources and expediting prosumers’ participation in transactive energy markets. In the context of packetized energy trading (PET), energy prosumers are naturally deemed as self‐interested agents seeking to obtain their own benefits. To align with prosumers’ demand, supply, quality of service (QoS), and system‐level social welfare, it is necessary to explore the design of prosumers’ bidding strategies and the market clearing methods, considering prosumers’ utility and the best demand response to markets. This study addresses challenges arising from prosumers’ selfishness and asymmetric preferences by proposing a PET‐oriented iterative double auction (IDA‐PET) design, where prosumers are allowed to iteratively change the bids before the auctioneer clears the market. Moreover, IDA‐PET accommodates system capacity constraints, energy balance, and economic constraints, providing cooperative strategies for both prosumers and the auctioneer. To validate the effectiveness of IDA‐PET, a novel and dedicated co‐simulation platform based on the hierarchical engine for large‐scale infrastructure co‐simulation platform is developed and case studies are conducted within a residential microgrid. The simulation results demonstrate that IDA‐PET can efficiently enhance the revenue of the auction market while meeting prosumers’ QoS requirements.

Exploring reference-dependency in route switching behavior on intercity travel: Endowment effect and disparities between willingness to pay and willingness to accept

This study explores asymmetric preferences in route switching behavior on intercity travel. A reference-dependent travel choice model reflecting the endowment effect is empirically compared with the classical symmetric travel choice model to investigate the significance of the reference-dependency. Based on the application to stated preference data, our results reveal that the reference-dependent travel choice model outperforms the classical symmetric travel choice model in route switching decision, indicating the significant disparities between WTA and WTP. It implies that policy making based on the results of the classical symmetric model assuming equivalent WTA and WTP could lead to the overestimation of switching demand. Furthermore, our results show that drivers are more heterogeneous in terms of WTA than WTP. Moreover, our applications of the latent class mixed logit structure indicate that most of the responded drivers show reference-dependency in route switching decision. Our findings in this study are essential in transport network policy making.

Giver‐receiver discrepancy in decisions between probabilistic and regular gifts

AbstractPrevious research has identified discrepancies between gift givers and receivers in their attitudes towards certain types of gifts, such as self‐improvement gifts. However, it remains unexplored whether there are divergent preferences between givers and receivers regarding probabilistic gifts (i.e., gifts involving probabilistic goods), despite the growing popularity of such goods. To address this gap, we conducted five studies. Study 1 revealed that when presented with a choice between probabilistic gifts and regular gifts, givers were less likely than receivers to select probabilistic gifts. This discrepancy was replicated in two contexts: vertical outcomes of probabilistic gifts (e.g., travel packages with varying prices) in Study 2, and horizontal outcomes of probabilistic gifts (e.g., T‐shirts with different patterns) in Study 3. Study 4 identified that this asymmetrical preference occurred due to different regulatory focus and perceptions of norm violations among individuals when engaging in gift giving. Givers exhibited a higher inclination towards prevention‐focused strategies, whereas receivers displayed a stronger preference for promotion‐focused strategies. Moreover, givers tend to significantly overestimate the extent to which receivers perceive probabilistic gifts as violating gifting norms. These disparities resulted in an asymmetrical preference for probabilistic gifts between givers and receivers. In Study 5, we found that consideration of creativity in gifting moderated the giver‐receiver asymmetrical preference for probabilistic gifts. Specifically, givers with heightened consideration of creativity were more likely to choose probabilistic gifts. These findings imply that gift givers could give greater consideration to probabilistic gifts, and marketers can capitalize on this by promoting probabilistic goods as viable gift options.

Linking the preference in a bilateral asymmetric task with handedness, footedness, and eyedness: The case of ice-hockey.

Most people know whether they are left-handed or right-handed, and usually base this assessment on preferences during one-handed tasks. There are several manual tasks that require the contribution of both hands, in which, in most cases, each hand plays a different role. In this specific case, holding an ice-hockey stick is particularly interesting because the hand placement may have an incidence on the playing style. In this study (n = 854), the main objective was to determine to what extent the way of holding an ice-hockey stick is associated with other lateralized preferences. Amongst the 131 participants reporting a preference for the left hand in unilateral tasks, 70.2% reported a preference for shooting right (placing the right hand in the middle of the stick); and amongst the 583 participants reporting a preference for writing with the right hand, 66.2% reported a preference for shooting left. 140 (16.4%) participants were classified as ambidextrous and 61.4% of them reported a preference for shooting right. This preference on the ice-hockey stick is closely correlated (uncrossed preference) to the way one holds a rake, shovel, or broom, or a golf club, but inversely related to the way one holds an ax and a baseball bat. The link between the way of holding the ice-hockey stick and eyedness or footedness is weak. These results are contrasted with the results reported by Loffing et al. (2014) and reveal the need to clarify the exact nature and requirements of the targeted tasks when studying bilateral asymmetric preferences.

Asymmetric leader-laggard cluster synchronization for collective decision-making with laser network

Photonic accelerators have recently attracted soaring interest, harnessing the ultimate nature of light for information processing. Collective decision-making with a laser network, employing the chaotic and synchronous dynamics of optically interconnected lasers to address the competitive multi-armed bandit (CMAB) problem, is a highly compelling approach due to its scalability and experimental feasibility. We investigated essential network structures for collective decision-making through quantitative stability analysis. Moreover, we demonstrated the asymmetric preferences of players in the CMAB problem, extending its functionality to more practical applications. Our study highlights the capability and significance of machine learning built upon chaotic lasers and photonic devices.

Re-Examining the South African Reserve Bank’s Policy Reaction Function Using the NARDL Model

The 3–6 percent inflation target is a policy rule used by the South African Reserve Bank (SARB) to fulfil its statutory obligation of ensuring a low and stable inflation environment and its policy reaction function assesses how the Reserve Bank responds to deviations of inflation from its target. We rely on nonlinear autoregressive distributive lag (NARDL) models to estimate the asymmetric preferences which the Reserve Bank has to inflation deviations during rising and falling episodes of inflation. Using quarterly data spanning from 2002:q1 to 2021:q4, we estimate the policy reaction functions using 7 disaggregated measures of inflation to capture the heterogeneity in the formation of price expectations. We further segregate our data into two sub-periods, corresponding to the pre-crisis and post-crisis era, as a robustness exercise. Overall, our findings indicate that in the post-crisis era the SARB (i) has become more responsive to inflation, output fluctuations and exchange rates and (ii) has responded more aggressively to rising inflation than falling inflation.

The Conservatism Principle and Asymmetric Preferences over Reporting Errors

ABSTRACT Accounting conservatism has been described as deriving from preferences for reporting errors to be in the direction of understatement rather than overstatement. We pair reporters with users (who rely on reporters’ information) in a multiperiod experiment. We posit that, under misaligned incentives that motivate aggressive reporting, users view aggressive reports as reflecting exploitative intent and expect that a norm prohibiting aggressive reporting applies. We predict that users use noisy reporting errors to gauge reporters’ norm compliance. We find that, ceteris paribus, users prefer not to be paired with reporters producing overstatement errors likely to reflect aggressive reporting relative to reporters producing understatement errors likely to reflect conservative reporting; alternatively, we find no such asymmetric preferences when the agents’ motives are aligned. The asymmetric preferences cannot be explained by agency theory predictions of payoff maximization or loss aversion. These moral preferences provide an initial condition from which conservatism can endogenously emerge. Data Availability: Data are available from the authors upon request. JEL Classifications: B52; D81; D82; M41.

Examining B2B channel decision-making within differential quality-level zone: a supply chain design using a non-cooperative strategic game theoretic approach (“Stackelberg Supply Chain for B2B”)

Purpose The consumers want to purchase the target products in the right place, whereas the manufacturers want to allocate their possible products to optimal distribution channels. The manufacturer must know how to handle itself in this business. The study aims to examine the B2B channel decision-making with different product qualities in a non-cooperative supply chain. Design/methodology/approach The authors develop a B2B Manufacturer-Stackelberg game as an analytical framework, combining asymmetric preference of purchase channels choice by the consumers, a continuous quality setting of the manufacturer and differential channel structure to study the manufacturer’s product strategy and channel optimisation. By horizontal comparisons across four channel structures, product variety can be classified into the differential quality-level zone through exogenous quality intervention, and the preference of manufacturers in each quality-level zone within the structures can be ranked. Findings Theoretically and practically, the hybrid-channel structure should be completely neglected when the direct channel dominates the retail channel. In contrast, dual-channel structures dominate single channels irrespective of the channel power, and channel preferences between high-quality and low-quality zones are stable, whereas the preference in medium-quality zone is unstable. In addition, the supply chain system cannot achieve global Pareto improvement without any additional coordination mechanism between the manufacturer and the retailer. Originality/value The extended results by numerical examples suggest that the bigger the area of the medium-quality zone, the more significant the product variety of the manufacturer.

An interactive ACO enriched with an eclectic multi-criteria ordinal classifier to address many-objective optimisation problems

Despite the vast research on many-objective optimisation problems, the presence of many objective functions is still a challenge worthy of further study. A way to treat this kind of problem is to incorporate the preferences of the decision maker (DM) into the optimisation process. In this paper, we introduce an interactive ant colony optimisation combined with an ordinal classification method in which classes are described by characteristic profiles. Through several interactions, the DM is supposed to identify some representative solutions of the classes ‘satisfactory’ and ‘dissatisfactory,’ which are used to initialise an ordinal classifier that increases the selective pressure by discriminating in favour of the ‘satisfactory’ class. This method can work with any either asymmetric or symmetric binary preference relation, a feature that confers a very wide generality. As another advantage, the interaction with the DM has minimal cognitive demands, which is an advisable feature for any approach based on interaction. Although the preference model is quite general, the proposal was tested using an eclectic model which combines compensatory preferences, veto conditions, and interval numbers to handle imprecise values; those preferences are aggregated in an asymmetric preference relation. Our approach performs particularly well in 10-objective problems according to the standards in the state-of-the-art literature. Numerical results and tests for statistical significance on the DTLZ and WFG test suites support this claim.

Learning the Parameters of ELECTRE-Based Primal-Dual Sorting Methods that Use Either Characteristic or Limiting Profiles

Two multicriteria-sorting methods that generalize the relational paradigm have been recently presented in the literature. One uses objects representative of classes, the other uses objects in the limiting boundaries of classes; both can use either a reflexive or an asymmetric preference relation. However, defining the parameters of relation-based methods is not straightforward. The present work operationalizes those methods with a methodology that takes examples provided by the decision-maker and, using an accuracy measure that specifically fits the characteristics of the methods, exploits an evolutionary algorithm to determine the parameters that best reproduce such examples. The assessment of the proposal showed that (i) it can achieve considerably high levels of out-of-sample effectiveness with only a few decision examples; (ii) the inference process is more effective learning the parameters of the method based on representative objects; (iii) it tends to be more effective with a reflexive relation; (iv) the effectiveness decreases while increasing the number of classes, which is not always the case when increasing the number of criteria. Theoretical properties of the proposed methodology will be investigated in future works.

A new hierarchical multiple criteria ordered clustering approach as a complementary tool for sorting and ranking problems

Multiple criteria ordered clustering is a problem that involves grouping the objects of decisions (actions) into a priori unknown ordered classes considering the preferences of a decision maker (DM). By exploring the relationship between multiple criteria sorting and multiple criteria ordered clustering, we take advantage of some ordinal classification approaches to propose a new approach. The set of totally ordered clusters fulfills a property of monotonicity with respect to dominance and an asymmetric preference relation; this is useful for suggesting a more consistent and robust rank of actions regarding the existence of possible “irrelevant alternatives”. The algorithm designed to operationalize our approach makes use of either a fuzzy outranking relation or a fuzzy preference relation. Imperfect knowledge (namely uncertainty and imprecision) of criteria performance levels and model parameter values can be modelled using interval numbers. Our approach and algorithm are illustrated through a simple interval extension of the well-known PROMETHEE method, which is applied to group countries according to human development criteria. The OECD country governments are also grouped according to their public sector performance but instead using a fuzzy outranking relation in an interval framework. In both examples, the results are very promising.

Channel encroachment strategy through pure online or combined offline retailing

Abstract With the rise of e-commerce, an increasing number of retailers concentrate on the online channel to sell their products (strategy O), while some retailers select online and offline combined retailing. That is, the retailers introduce an offline experience store in addition to their online channels (strategy B). However, there is little literature on which strategies are better when a retailer’s intrusion is considered. This paper constructs a competitive system in which the incumbent is a well-established pure online retailer and the new entrant will decide which strategy to select, strategy O or strategy B. The hotelling model is applied to represent the competitive market of both retailers through consumers’ asymmetrical preference for products, and Nash games under two strategies are built. Through comparing equilibrium solutions, we show that when consumers prefer the incumbent’s product, online and offline retailing is an effective strategy for the new entrant to compete with the incumbent. Meanwhile, the incumbent’s advantage does not always benefit him. Consumers’ asymmetrical preference for products may intensify the competition between them and hurt their profits, but the new entrant can benefit from providing offline retailing under most cases.

Special Issue: “Symmetry in Cognition and Emotion”

The ten contributions of the current Special Issue on “Symmetry in Cognition and Emotion” represent different and original contributions to this topic. The new evidence spans from addressing whether the attentional blink can be elicited by internal events to the role of the fronto-parietal network. The review contributions address the effect of emotion on pseudoneglect and the role of the temporal parietal junction in processing self-related information, respectively. Four contributions provide new evidence on processing different aspects of faces, such as age, gaze, emotional expression, and their effect on response inhibition. Finally, two contributions provide novel evidence on the asymmetric preferences in decisions and on the relation between preferences for visual symmetry, respectively. Taken together, these contributions provide a new insight into the different forms of “Symmetry in Cognition and Emotion”, and we hope they can help to stimulate new research.

An asymmetric PROMETHEE II for cryptocurrency portfolio allocation based on return prediction

Portfolio allocation, portfolio selection, and portfolio optimization are recognized as three crucial problems in the financial field. Using different criteria in addition to return and risk in the portfolio allocation problem based on the multi-criteria decision-making (MCDM) methods makes it more practical in the real world. The emergence of new and volatile assets such as cryptocurrencies has recently increased the need to use portfolio allocation models. In order to reduce inequalities and alleviate poverty as one of the sustainable development goals, cryptocurrency portfolio construction leads to sustainable income and wealth. This paper proposes a cryptocurrency portfolio allocation model based on the asymmetric Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE II) method using eight criteria and nine cryptocurrencies. To reduce the uncertainty of the problem, the return prediction obtained from the Auto-Regressive Integrated Moving Average (ARIMA), the Long Short-Term Memory (LSTM), and the Random Forest Regression (RFR) models as return-related criteria and has been used from the SlideVaR, along with the Value at Risk (VaR) and the Conditional Value at Risk (C-VaR) as risk-related criteria to consider investor insight from the market situation. It is also proposed that an asymmetric preference function be proposed to consider gain and loss asymmetry as a behavioral phenomenon in the model. The out-of-sample performance of the proposed model in the last three months of 2021 confirms the superiority of the proposed model in terms of average return (= 0.017) and standard deviation (= 0.036) among other proposed models.

Generalized disappointment aversion and the cross-section of stock returns

ABSTRACT Based on Epstein and Zin’s recursive utility function, this paper integrates generalized disappointment aversion preferences to derive an intertemporal equilibrium asset pricing model (ICAPM). We show that in addition to discount-rate news, cash-flow news, and news about future risk, four factors related to disappointment are priced. These four factors are a downstate factor, discount-rate downside news, cash-flow downside news, and downside news about future risk. We find that our seven-factor model can explain the cross-section of expected returns across portfolios sorted by size, book-to-market, investment, operating profitability, and momentum. Both the seven-beta ICAPM and the restricted seven-beta ICAPM suggest that disappointment-averse investors are more sensitive to cash-flow news and cash-flow downside news than other news terms and therefore demand higher premiums. Our results show that the seven-beta ICAPM has better performance for most portfolios and provides empirical support for investors’ asymmetric preferences.

Uncertainty of Preferences in the Assessment of Supply Chain Management Systems Using the PROMETHEE Method

The use of Supply Chain Management (SCM) systems allows for the improvement of an organization’s operations. Companies use many Enterprise Resource Planning (ERP) systems that also include SCM functionalities. As a result, the selection of the right system to be used in the enterprise is a complex problem. The use of multi-criteria decision aid (MCDA) methods provides the possibility of system ordering in a ranking, based on an asymmetric preference relation, symmetric indifference and incomparability relations. The aim of the article is to evaluate ERP systems in terms of their support for SCM. The scientific contribution of the article is the study of the impact of various degrees of uncertainty of the decision-maker’s preferences on the evaluation results and the analysis of the impact of various approaches to the preferences of alternatives on the final ranking. An approach based on MCDA Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) was used for the study. The decision model uses 12 criteria, three different preference functions and two variants of the PROMETHEE method (I and II). In this way, a total of six rankings were built, and each of them includes seven systems, supporting the management of the supply chain. As a result of the study, it was found that the highest functionality in logistics is characterized by the Oracle E-Business Suite system, which is more functional than SAP ERP and JD Edwards EnterpriseOne. The remaining analysed systems offer much less functionality. The applied approach, which was possible with the use of various preference functions, allowed three different levels of uncertainty in the preferences of decision-makers to be taken into account in the study. Moreover, the application of two different variants of the PROMETHEE method made it possible for the obtained solution to take into account the uncertainty of positions taken by individual ERP systems in the final rankings.

Proper Scoring Rules for Evaluating Density Forecasts with Asymmetric Loss Functions

This article proposes a novel asymmetric continuous probabilistic score (ACPS) for evaluating and comparing density forecasts. It generalizes the proposed score and defines a weighted version, which emphasizes regions of interest, such as the tails or the center of a variable’s range. The (weighted) ACPS extends the symmetric (weighted) CRPS by allowing for asymmetries in the preferences underlying the scoring rule. A test is used to statistically compare the predictive ability of different forecasts. The ACPS is of general use in any situation where the decision-maker has asymmetric preferences in the evaluation of the forecasts. In an artificial experiment, the implications of varying the level of asymmetry in the ACPS are illustrated. Then, the proposed score and test are applied to assess and compare density forecasts of macroeconomic relevant datasets (U.S. employment growth) and of commodity prices (oil and electricity prices) with particular focus on the recent COVID-19 crisis period.