Actual Preferences Research Articles

Dynamic pricing of free-floating carsharing networks with sensitivity to travellers’ attitudes towards risk

Free-floating carsharing (FFCS) systems are characterised by volatile fleet distribution as well as customers’ heterogeneous price sensitivity and spatiotemporal flexibility. There is thus an opportunity for operators to employ dynamic pricing to manage various aspects of fleet allocation: which customer is provided which vehicle, at what time and price, and the agreed pick-up and drop-off location. While there are emerging examples of dynamic pricing in FFCS, there is as yet no general framework for the interaction of consumer and operator behaviours in this context, most particularly consumer response to the inherent risks and uncertainties in the journey characteristics noted above. In this study, we propose a choice-based framework for modelling the supply/demand interaction, drawing on behavioural models of decision-making in risky choice contexts and empirical stated-choice data of user preferences in a dynamically priced FFCS market. In addition to the ‘spot market’ mechanism of dynamic pricing, the proposed framework is capable of evaluating operator strategies of allowing (at an agreed price) customers to make guaranteed advance reservations. We demonstrate that this approach allows the system operator to set an optimal pricing strategy regardless of whether user risk preferences are risk-seeking or risk-averse. We also demonstrate the applicability of the proposed framework when the operator seeks to maximise revenue (as with a private operator) vs social welfare (as with a public operator). In the case study which employs empirical user preferences, we show that users’ risk preferences have a relatively small impact on revenue, however the impacts are much larger if there is a mismatch between users’ actual risk preferences and the system operator’s assumptions regarding users’ risk preferences.

Do interest groups bias MPs' perception of party voters' preferences?

This study analyses how information provided by different types of interest groups influences the ability of members of parliament (MPs) to accurately perceive the preferences of those citizens who voted them into office. To study how information provision by interest groups affects MPs’ perceptions, we combine unique data from a citizen survey and face-to-face meetings with 151 federal MPs in Switzerland, thus enabling a comparison of actual voter preferences with MPs’ estimations of these preferences. Ties to citizen groups, as self-reported by MPs in our survey, relate to more accurate perceptions by MPs, even when controlling for MPs’ partisan affiliation. Ties to business groups, as declared in the official registry, relate to less accurate perceptions. These findings suggest that interest groups can both tighten and weaken MPs’ link to their party voters, which might have repercussions on substantive representation and democratic accountability.

Large-Scale Ideal Point Estimation

AbstractRecent advances in the study of voting behavior and the study of legislatures have relied on ideal point estimation for measuring the preferences of political actors, and increasingly, these applications have involved very large data matrices. This has proved challenging for the widely available approaches. Limitations of existing methods include excessive computation time and excessive memory requirements on large datasets, the inability to efficiently deal with sparse data matrices, inefficient computation of standard errors, and ineffective methods for generating starting values. I develop an approach for estimating multidimensional ideal points in large-scale applications, which overcomes these limitations. I demonstrate my approach by applying it to a number of challenging problems. The methods I develop are implemented in an r package (ipe).

Shining a Light on Dark Patterns

AbstractDark patterns are user interfaces whose designers knowingly confuse users, make it difficult for users to express their actual preferences, or manipulate users into taking certain actions. They typically exploit cognitive biases and prompt online consumers to purchase goods and services that they do not want or to reveal personal information they would prefer not to disclose. This article provides the first public evidence of the power of dark patterns. It discusses the results of the authors’ two large-scale experiments in which representative samples of American consumers were exposed to dark patterns. In the first study, users exposed to mild dark patterns were more than twice as likely to sign up for a dubious service as those assigned to the control group, and users in the aggressive dark pattern condition were almost four times as likely to subscribe. Moreover, whereas aggressive dark patterns generated a powerful backlash among consumers, mild dark patterns did not. Less educated subjects were significantly more susceptible to mild dark patterns than their well-educated counterparts. The second study identified the dark patterns that seem most likely to nudge consumers into making decisions that they are likely to regret or misunderstand. Hidden information, trick question, and obstruction strategies were particularly likely to manipulate consumers successfully. Other strategies employing loaded language or generating bandwagon effects worked moderately well, while still others such as “must act now” messages did not make consumers more likely to purchase a costly service. Our second study also replicated a striking result in the first experiment, which is that where dark patterns were employed the cost of the service offered to consumers became immaterial. Decision architecture, not price, drove consumer purchasing decisions. The article concludes by examining legal frameworks for addressing dark patterns. Many dark patterns appear to violate federal and state laws restricting the use of unfair and deceptive practices in trade. Moreover, in those instances where consumers enter into contracts after being exposed to dark patterns, their consent could be deemed voidable under contract law principles. The article also proposes that dark pattern audits become part of the Federal Trade Commission (FTC)’s consent decree process. Dark patterns are presumably proliferating because firms’ proprietary A-B testing has revealed them to be profit maximizing. We show how similar A-B testing can be used to identify those dark patterns that are so manipulative that they ought to be deemed unlawful.

164 Standardised Anticipatory Care Planning in Care Homes Reduces Unscheduled Hospital Admissions

Abstract Background Anticipatory care planning (ACP) is a proactive person-centred approach for “thinking ahead”, exploring and recording a person’s goals and preferred actions when their health deteriorates. As a key part of Comprehensive Geriatric Assessment of frail patients, care home (CH) residents would benefit from ACP. Introduction West Lothian has 16 care homes with 853 residents. Between Oct—Dec 2017, 5.21% of CH residents were admitted to hospital each month. Some of these admissions could have been avoided had there been robust ACP in place. Methods In 2017 West Lothian Health and Social Care Partnership appointed a GP lead for Care Homes. Through standardising ACP for CH residents, the goal was to improve the pathway for managing medical emergencies and reduce unnecessary unscheduled care calls and admissions. In 2019 this role was taken over by a team of 2WTE Advanced Nurse Practitioners and 1WTE Staff Nurse. Outcome measures include hospital admission rates, number of ACPs in place and uptake of ACP training amongst CH staff. Interventions In collaboration with the Medicine of the Elderly Department at St John’s Hospital, a standardised ACP Summary document was developed for use in all CHs. A medical advice and emergency flowchart was created to reduce unnecessary hospital admissions. An continuous education programme was delivered across all CH staff to facilitate and implement this. Results Medical admission rates from CHs have decreased by 60% from 6 to 2.2 admissions per week. The largest reduction is in CHs with full ACP use. Conclusions Standardised ACP significantly reduces the number of medical admissions. Continuous education and training is crucial in maintaining its implementation, and ensuring its routine use throughout CHs in West Lothian.

A longitudinal study of e-commerce diversity in Europe

Owing to increased access to the Internet and the development of electronic commerce, e-commerce has become a common method of shopping in all countries. The purpose of this study is more precisely to research e-commerce diversity in Europe at the regional level and develop the conception of “E-commerce Supply Chain Management”. Statistical data derived from the European Statistical Office were applied to analyse the spatial diversity of e-retailing. Assessments of the regional diversity of e-retailing applied geographic information systems and exploratory spatial data analysis methods such us global and local spatial autocorrelation statistics. Clusters of regions with similar household preferences related to online shopping were identified. A spatial visualisation of the e-retailing diversity phenomenon may be utilised for the reconfiguration of supply chains and to adapt them to actual household preferences related to shopping methods.

Learning, exploitation and bias in games.

We focus on learning during development in a group of individuals that play a competitive game with each other. The game has two actions and there is negative frequency dependence. We define the distribution of actions by group members to be an equilibrium configuration if no individual can improve its payoff by unilaterally changing its action. We show that at this equilibrium, one action is preferred in the sense that those taking the preferred action have a higher payoff than those taking the other, more prosocial, action. We explore the consequences of a simple ‘unbiased’ reinforcement learning rule during development, showing that groups reach an approximate equilibrium distribution, so that some achieve a higher payoff than others. Because there is learning, an individual’s behaviour can influence the future behaviour of others. We show that, as a consequence, there is the potential for an individual to exploit others by influencing them to be the ones to take the non-preferred action. Using an evolutionary simulation, we show that population members can avoid being exploited by over-valuing rewards obtained from the preferred option during learning, an example of a bias that is ‘rational’.

Scalable and fair resource sharing among 5G D2D users and legacy 4G users: A game theoretic approach

We propose a game theoretic approach to the problem of resource allocation in fifth generation device to device communications underlying cellular networks, where modern fifth generation device to device users share channel resources of legacy fourth generation cellular users. Though such sharing improves scalability as more and more users can be served, the individual throughput obtained by a cellular user may get reduced when its channel resource is shared by a device to device user pair. Thus our aim is to increase the overall system throughput while ensuring effective user fairness for the legacy cellular users served. Our approach provides a tradeoff between the two objectives thereby ensuring no legacy cellular users are compromised heavily while encouraging modern device to device users. We have addressed this fairness problem by thresholding the reduction of the throughput of a cellular user with respect to its ideal throughput if not reused. We have proposed a game theoretic model in order to make strategic decision for selecting the preferred action configuration in order to meet this objective. We have also discussed about the convergence and the time bound of the proposed game model with a clear analysis of the scenarios encountered during the process of shared consumption of resources among cellular users and the device to device users. Together with this game model, convergence and time bound analyses and two validation processes, we aim to improve scalability, overall system throughput without compromising the fairness of the cellular users. We have also compared the user fairness achieved by our approach with two existing approaches to demonstrate the effectiveness of our game theoretic approach.

Two Sides of the Same Coin: EU Financial Regulation and Private Law

Today, legislators, courts, financial regulators and other actors at the EU and national level face major new challenges in safeguarding public and private interests in an increasingly digital and sustainability-minded environment surrounding financial markets. Innovative ways of addressing tensions between the common good and the individual preferences of market actors are needed to address these challenges. However, at present, the efforts to develop workable solutions are seriously hampered by the gap between the two areas of law that profoundly shape the financial markets—financial regulation and private law—in the current European policy discourse and legal scholarship. This article is an attempt to systematically rethink the role of private law in the regulatory and enforcement landscape for financial markets and its relationship with public regulation more generally. It argues that financial regulation and private law are not two parallel universes, but rather two sides of the same coin, each of which has a critical role to play in safeguarding public and private interests. Examining EU financial regulation through the ‘private law’ lens would enable us to unveil a complex interplay between the regulatory dimension, contractual settings and private law remedies that we need to better understand in order to be able to better regulate financial markets. Conversely, examining national private law through the European ‘regulatory’ lens would allow us to unpack the potential of traditional private law to contribute to the objectives of EU financial regulation, while at the same time realising justice between private parties.

Actor perspective and moral reasoning: Do levels of criminal thinking moderate this relationship among non‐criminals?

A large body of literature has explored moral decision-making; however, fewer have examined the explicit role of criminal thinking (CT). This study sought to determine whether moral judgment is influenced by CT in the general population and if this relationship further depends on the type of scenario (i.e., immoral vs. illegal) and/or the actor orientation (i.e., self vs. other). Using a sample of 239 U.S. adults and hypothetical case vignettes, results showed that those who endorsed higher levels of CT rated socially deviant behaviors, regardless of the type of scenario, as significantly more morally acceptable than participants who endorsed lower levels of CT. However, this difference was more pronounced for the immoral dilemma compared to the illegal dilemma. Specifically, proactive CT processes led to higher justification for the immoral dilemma. Neither general nor reactive CT were significantly associated with moral reasoning for the illegal dilemma. Among a mostly non-offending sample, this finding makes sense as it appears participants' levels of criminal thinking may have been high enough to rationalize an immoral dilemma but not so high as to allow for rationalization of an illegal dilemma. No significant differences were found concerning actor orientation. This research not only has important implications for better understanding traits associated with moral decision-making in everyday choices, but it may also have practical application in legal contexts. However, further research is needed in these contexts. Findings were also limited by a lack of racial diversity among participants.

To log or not to log? Actor preferences and networks in Swiss forest policy

Forests play a fundamental role in climate change mitigation. While there are calls to store carbon by increasing the forest stock, other actors oppose this, arguing that carbon stored in processed timber is more adequate. Applying an adapted version of the policy network analysis (PNA) framework, we uncover both the actors' policy preferences regarding the goal conflict between carbon storage in the forest versus in timber products as well as the actors' perceived importance and information sharing in the forest policy network in a Swiss region (canton Lucerne) via an online stakeholder survey. We find that an increase of carbon storage in the forest does not stand a chance in the Lucerne forest policy network, being rejected by nearly two-thirds of the actors. A majority views increased harvesting for wood products as a superior climate change mitigation measure than harvesting less for carbon storage. We also find that these proponents of wood are more central actors within the policy networks than those in favour of carbon storage in the forest. These findings are relevant for a context where the majority of the forest is privately owned and where interests in timber harvesting might dominate those on carbon storage. The analysis reflects the challenging situation within the timber market, where measures for increased wood harvesting might provide a more acceptable policy option than carbon sequestration for private forest owners.

Guidelines for Designing Green Products Considering Customers’ Cultural Preferences

The increasing customer awareness of environmental sustainability during the last decade has had an influence on many manufacturers to produce green products. However, issues arise regarding the actual preferences of customers for green products, which often differ depending on cultural influences. Cultural values can affect the decisions of designers to determine detailed design specifications that relate to customer preferences. Currently, few guidelines consider cultural values as an aspect of green product design. Thus, the aim of this study is to develop a guideline that incorporates the influence of cultural values on green product design. Malaysia was selected as the location of this study. The sources of data to establish a guideline were obtained from customer perspectives on green products. Structural equation modeling (SEM) was used to identify cultural influences and preferences on green product characteristics as the input strategies for the proposed guideline. Professional designers from different profiles were asked to identify the applicability of the guideline. Based on the results, the designers agreed that the influence of cultural values is an important aspect that should be considered in the development of green products. The implication of the guideline is discussed in this paper to accelerate decisions of designers in developing green products.

Negotiating preferred norms in requests and offers: Is the (dis)preferred answer so obviously (im)polite?

The article considers the relationship between (dis)preferred actions and (im)politeness. While both (im)politeness and preference organization share the characteristics of normativity and markedness the relationship between the two has not been discussed at length to date. Attempting to show that the linkage between politeness as social practice and preference organization pertains both to turn design and the position of an action, my analysis will focus on responsive actions to requests and offers. Drawing on Heritage's (1988) distinction between normative and moral accountability, I will study the way in which the relationship between preference, (im)politeness and accountability emerge from the sequential organization of talk, with special attention being paid to the position of a turn in the ongoing sequence as well as to its function with respect to the current activity. The dataset consists of thirty-eight everyday conversations, drawn from the Corpus of Spoken Greek at the Institute of Modern Greek Studies.

CNNA: A study of Convolutional Neural Networks with Attention

Point-of-Interest (POI) recommendation systems can give the user a list of locations that the user may be interested in, but the recent check-ins may contain some daily check-ins that users are not really interested in. To address the issues of mining users’ actual preferences from users’ recent check-ins, this paper proposes a Convolutional Neural Networks with Attention (CNNA), which consists of a latent representation method and a deep convolutional neural network. We have carried out several sets of experiments to test the validity of CNNA, and the experimental results show the effectiveness of CNNA.

International Statebuilding and the Domestic Politics of State Development

Managing the threat of violence remains a central concern in international security and development. International actors seek to terminate civil wars and prevent conflict recurrence by building peace and strengthening state institutions. In this article, I review the scholarship on international statebuilding, defined broadly as external efforts to create, strengthen, reform, and transform the authority structures of the state. Much of this literature models international statebuilding as provision, in which external actors provide a solution to the enforcement problem that plagues post-conflict bargains. However, in many cases the assumptions about domestic politics underpinning the provision model do not hold. When the central problem of domestic politics concerns bargaining over the distributional consequences of the peace rather than the parties' ability to credibly commit to the peace, international statebuilding is more fruitfully modeled as imposition, in which terms are imposed on recalcitrant domestic actors. The imposition model allows the preferences of external actors over the post-war order to diverge from the preferences of domestic actors. Divergence arises because statebuilding interventions have distributional consequences that threaten the interests of domestic elites. To unpack why this is the case, I turn to the literature on the domestic politics of statebuilding, which shows that ``weak statehood'' can help manage violence by facilitating the distribution of sovereignty rents. Insights from these literatures suggest exciting new avenues for future scholarship.

Unsupervised inference of statistically significant synchronization and opposition links from bipartite systems

Many of the real-world data sets can be portrayed as bipartite networks. Such data sets are particularly abundant where human behavior is being recorded. Because typically direct observations of the relationships between different agents are lacking, they need to be inferred by converting bipartite networks to their mono-partite counterparts. While most bipartite networks contain only one type of a link, e.g., an agent attended an event, data sets exist where the links can represent different actions, say when voting, an agent supported, opposed, or abstained a proposition. This paper proposes a new unsupervised statistical method based on hypergeometric-binomial mixture distribution to identify the most significant synchronization and opposition ties between agents when they are recorded to take different actions. The method takes into account the heterogeneity of individual nodes in terms of how active they are and in terms of their preferred actions. The resulting binary or signed graphs can then be used to investigate the structure of co-behaviors between agents. We demonstrate the link validation using empirical investor trading and parliament member voting data. We find structurally balanced signed networks.

Trading Places, Trading Platforms: The Geography of Trade Policy Realignment

AbstractWhat motivates politicians and political parties to shift their positioning on an issue? Focusing on the case of trade policy in countries with advanced economies and plurality electoral systems, I argue that the relative positioning of parties on an existing issue can change even when the preferences of the key actors (voters and politicians) are held constant, and even when party leaders continue to represent the same constituencies. In advanced plurality countries, college-educated voters support free trade, and high-density constituencies are predominantly represented by Left incumbents. As college-educated workers migrate to high-density constituencies in pursuit of higher wages, Left incumbents increasingly embrace free trade, while Right incumbents take more protectionist positions. I provide empirical support for several observable implications of my theory.

Quo Vadis, Europa? Five Paths, their Plausibility and Impact

The article discusses the plausibility of five different paths of institutional development of the European Union: deepening integration towards a federal state, a differentiated and flexible union, covert integration, a segmented political order and disintegration/dissolution Systematically varying either the preferences of the main actors or the macro conditions, i.e. decision-making rules, and external shocks, it discusses the plausibility of these paths and their overall effects on the European polity.

Research on Adaptive Relationship Between Trust and Privacy in Cloud Service

To prevent privacy leakage, cloud services need to take corresponding methods, so participants often face the dilemma of service utility and privacy protection. In this paper, we propose a dynamic adaptive access control model based on trust permission and privacy protection to solve the problem of privacy disclosure and utility in the cloud service. Firstly, we add the concept of obligation and purpose into access control and establish the privacy information tree and privacy policy tree. Secondly, we establish a new trust evaluation and give the corresponding weight algorithm. Thirdly, we quantify the privacy information with the normal space and correlation coefficient method. Further, we propose a tradeoff relationship model between trust permission and privacy protection, each participant can select the corresponding parameters according to the actual requirement and personal preference. Experimental analysis and comparison results verify the feasibility, effectiveness, and superiority of our method. Finally, we summarize the work of this paper and point out the future development direction.

Research on hot rolling scheduling problem based on Two-phase Pareto algorithm.

Under the background of excess capacity and energy saving in iron and steel enterprises, the hot rolling batch scheduling problem based on energy saving is a multi-objective and multi constraint optimization problem. In this paper, a hybrid multi-objective prize-collecting vehicle routing problem (Hybrid Price Collect Vehicle Routing Problem, HPCVRP) model is established to ensure minimum energy consumption, meet process rules, and maximize resource utilization. A two-phase Pareto search algorithm (2PPLS) is designed to solve this model. The improved MOEA/D with a penalty based boundary intersection distance (PBI) algorithm (MOEA/D-PBI) is introduced to decompose the HPCVRP in the first phase. In the second phase, the multi-objective ant colony system (MOACS) and Pareto local search (PLS) algorithm is used to generate approximate Pareto-optimal solutions. The final solution is then selected according to the actual demand and preference. In the simulation experiment, the 2PPLS is compared with five other algorithms, which shows the superiority of 2PPLS. Finally, the experiment was carried out on actual slab data from a steel plant in Shanghai. The results show that the model and algorithm can effectively reduce the energy consumption in the process of hot rolling batch scheduling.