Effects of social value orientation (SVO) and decision mode on controlled information acquisition—A Mouselab perspective

Insights into the processes underlying observed decisions are crucial for a comprehensive understanding of behavior. We investigate how individual social value orientation (SVO) relates to controlled information acquisition and how this relationship may be governed by intuitive versus reflective decision modes. We measure controlled information acquisition with the process tracing tool Mouselab and demonstrate its potential for advancing research on social decision-making. In two experiments, participants worked on two consecutive SVO tasks, in which they allocated points between themselves and others. Information regarding the available distributions of points had to be actively acquired by moving the mouse cursor over corresponding boxes on the screen. We observed a stable relationship between SVO and controlled information acquisition in both experiments: less selfish participants acquired more information and made more other-oriented acquisitions, and this relationship showed up in both an intuitive and a reflective decision mode. However, participants in a reflective decision mode acquired more information, their acquisitions were more strongly other-oriented, and their decisions were more prosocial compared to participants in an intuitive mode. Taken together, our results advance research on SVO by showing that non-selfish individuals invest considerable time and effort to gauge the consequences of their decisions for others, which might underlie the pervasive effects of SVO on many socially relevant behaviors. Moreover, we demonstrate how intuitive versus reflective decision modes can alter controlled information acquisition. Finally, our results illustrate that Mouselab is a simple-to-use and versatile tool for tracing cognitive processes underlying social psychological phenomena.

Assessing how we decide: Psychometric development of a decision modes scale

We present the development of the Domain-general Decision Mode Scale (DDMS), a 24-item scale to measure decision modes. Decision modes are the qualitatively different approaches through which individuals report making decisions. Researchers have consistently acknowledged that existing two-systems models of decision-making processes that distinguish between an intuitive and a rational mode do not account for the range of rule-based processes that decision makers employ in evaluating and making choices. Our studies identified six different decision modes, driven respectively by calculation, affect, habit, social norms, identity, and morality. Making a decision using the calculation mode involves a deliberate process of assessing costs and benefits. Using the affective mode involves an emotion- or gut-driven process. Using the social norms mode involves consideration of what others are doing or what others condone as appropriate. Using the habitual mode involves following a previously determined rule or habit. Using the identity mode involves identifying what is consistent with one’s sense of self or own values. Finally, using the moral decision mode involves consideration of what does the most good. We conceptually group the final four decision modes under the umbrella of rule-based decision-making: making a decision based on previously-learned and/or socially-derived conventions. The DDMS exhibits good reliability, as well as convergent and discriminant validity. By providing a scale that assesses the degree to which decision makers report using these decision modes, we integrate past research on decision modes and create a framework for additional research into the effects of different decision processes.

A knowledge representation of decision communications in scheme for automotive troubleshooting service

Scheme processes about complicated engineering systems are certainly complex on account of the interdependencies among submodules in the same tier and between tiers of a segmented hierarchy. In the design process with decision mode, this effects in communications among groups of design decisions. It is important to extract and represent the knowledge relevant to the decision communications for developing design process with decision mode. There are two critical issues addressed regarding the modeling of communications: decision types and these are made in various tiers. To stress the above two issues, there are several fundamental communication models defined among decisions in this study. Meanwhile, a presented ontology to identify the knowledge connected with these communication models. Critical benefits of the ontology involve that a hierarchical communications between decisions can be extracted, and a decision task-flows with accessible, adaptable, and implementable features for developing more complex systems can be generated. The applicability of the ontology is shown by scheme for an automotive braking troubleshooting service example.

Effects of Dual Credit Policy and Consumer Preferences on Production Decisions in Automobile Supply Chain

New energy vehicles have a significant advantage in energy saving and environmental pollution reduction in the transportation industry; however, they are still at a disadvantage in the market competition. The Chinese government has introduced lots of policy measures to promote the mass adoption of new energy vehicles (NEVs), specifically the dual credit policy. Moreover, consumer’s preferences are vital factors in their purchase decision making. This study focuses on the production decisions of automobile manufacturers under the decentralized and centralized supply chain, considering the factors of both consumer preferences and dual credit policy. First, under the centralized decision mode, higher demand drives the manufacturer to expand production; however, retailers’ profits are harmed. With the increase in consumers’ environmental preference and cognition of endurance ability, market pricing and demand increase under the decentralized decision mode. The cross effects of preferences bring more profits for manufacturers and retailers. Second, the difference in prices and profits widens, under the two decision modes, as increases in consumer preferences’ value. When consumers have higher environmental preferences, manufacturers and retailers should increase the new energy vehicle pricing. Otherwise, they should decrease pricing to increase the market penetration ratio. In addition, the impacts of one preference on the profit difference are related to the other preference.

Hunger improves reinforcement-driven but not planned action

Human decisions can be reflexive or planned, being governed respectively by model-free and model-based learning systems. These two systems might differ in their responsiveness to our needs. Hunger drives us to specifically seek food rewards, but here we ask whether it might have more general effects on these two decision systems. On one hand, the model-based system is often considered flexible and context-sensitive, and might therefore be modulated by metabolic needs. On the other hand, the model-free system’s primitive reinforcement mechanisms may have closer ties to biological drives. Here, we tested participants on a well-established two-stage sequential decision-making task that dissociates the contribution of model-based and model-free control. Hunger enhanced overall performance by increasing model-free control, without affecting model-based control. These results demonstrate a generalised effect of hunger on decision-making that enhances reliance on primitive reinforcement learning, which in some situations translates into adaptive benefits.Significance statementThe prevalence of obesity and eating disorder is steadily increasing. To counteract problems related to eating, people need to make rational decisions. However, appetite may switch us to a different decision mode, making it harder to achieve long-term goals. Here we show that planned and reinforcement-driven actions are differentially sensitive to hunger. Hunger specifically affected reinforcement-driven actions, and did not affect the planning of actions. Our data shows that people behave differently when they are hungry. We also provide a computational model of how the behavioural changes might arise.

Coordination Strategy for a New Retail Supply Chain Based on Combination Contract

The supply chain in the new retail context demands higher requirements on the price, service, and logistics level. It is very important to seek the coordination among the optimal price, service level, and logistics level. In this paper, we propose the coordination of pricing, the service level, and delivery time of a new retail supply chain composed of one product supplier, one platform service provider, and one logistics provider. Firstly, the profit function mode of product pricing, platform service level, and logistics distribution level that influence the consumers’ demand is constructed in two modes, namely, the centralized and decentralized decision mode. Then, we calculate and compare the optimal product price, the optimal platform service level, the optimal delivery time, and the profit of each member of the supply chain from both decision modes. We discovered that cooperation improves the service level, logistics level, and the income of each member of the new retail supply chain. Therefore, we propose a novel mode called the coordination mode as a strategy for the supply chain based on the combination contract. We performed a numerical analysis to demonstrate the feasibility and effectiveness of the coordination contract.

Development of a Small Intelligent Weather Station for Agricultural Applications

It is known that climate change causes a decrease in the profit gained from agricultural production. This work designs and establishes weather boxes equipped with functions of rainfall prediction, frosting forecast, and lightning detection. With the wireless connection and the build-in decision mode, weather boxes can deliver early-warning by sending texting messages to the users and actuating the corresponding action to response the extreme climate. To implement rainfall and frosting prognostication, two different datasets are analyzed by the technology of data mining. One of the datasets is acquired from the Central Weather Bureau, and the other is from the proposed weather box monitoring the agricultural environment. From the experimental results, the prediction model constructed from the data which is collected by the proposed weather box exhibits a higher accuracy in rainfall forecasting than those based on the Central Weather Bureau.

Operation Strategies Based on Horizontal Competition and Service Capability Sharing under Demand Disturbance

The article considers the influence of demand disturbance on price, service capability, and operation mode selection of firms. Firstly, we discuss the equilibrium pricing and service capability strategy of the firm under three operation modes: price and service competition, price competition and service capability sharing, and price and service centralized making-decision. When there is demand disruption, firms determine their pricing and service capacity strategies under the three main operating models above. Finally, the comparative analysis shows that the influence of service capability in centralized decision price and service capability mode is greater than that on service capability in price competition and service capability sharing mode. The smoothness of service capability in price competition and service capability sharing mode is better than that in the centralized decision mode. And when the market price competition coefficient is moderate or the negative demand disturbance occurs, the price competition and service capability sharing mode has little influence on the profit compared with the other two modes (the profit loss is the smallest).