Judgments in the Sharing Economy: The Effect of User-Generated Trust and Reputation Information on Decision-Making Accuracy and Bias.
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ABSTRACT:
SUBMITTER: Zloteanu M
PROVIDER: S-EPMC8637778 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The Sharing Economy (SE) is a growing ecosystem focusing on peer-to-peer enterprise. In the SE the information available to assist individuals (users) in making decisions focuses predominantly on community-generated trust and reputation information. However, how such information impacts user judgement is still being understood. To explore such effects, we constructed an artificial SE accommodation platform where we varied the elements related to hosts' digital identity, measuring users' perceptions and decisions to interact. Across three studies, we find that trust and reputation information increases not only the users' perceived trustworthiness, credibility, and sociability of hosts, but also the propensity to rent a private room in their home. This effect is seen when providing users both with complete profiles and profiles with partial user-selected information. Closer investigations reveal that three elements relating to the host's digital identity are sufficient to produce such positive perceptions and increased rental decisions, regardless of which three elements are presented. Our findings have relevant implications for human judgment and privacy in the SE, and question its current culture of ever increasing information-sharing.
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Project description:Accurately judging emotion regulation (ER) may help facilitate and maintain social relationships. We investigated the accuracy and bias of ER judgments and their social correlates in a two-part study with 136 married couples (ages 23-85 years). Couples completed trait measures of their own and their partner's suppression, reappraisal, and situation selection. On a separate day, they discussed a conflict, then rated their own and their partner's suppression during the discussion. Couples accurately judged their partner's trait level use of all ER strategies, but they were most accurate for suppression. In contrast, they did not accurately judge state suppression; they showed a similarity bias, such that their own use of state suppression predicted judgments of their partner's suppression. Greater relationship satisfaction predicted positive biases at the trait level (e.g., overestimating reappraisal, underestimating suppression), but not the state level. Relationship length did not predict ER accuracy or bias. Findings suggest ER is more detectable at the trait level than state level and for strategies with more behavioral cues. Greater relationship satisfaction may signal positive perceptions of partners' ER patterns.Supplementary informationThe online version contains supplementary material available at 10.1007/s42761-022-00144-3.
| S-EPMC9743848 | biostudies-literature
Project description:This work aims to provide a reliable and intelligent prediction model for future trends in sharing economy. Moreover, it presents valuable insights for decision-making and policy development by relevant governmental bodies. Furthermore, the study introduces a predictive system that incorporates an enhanced Harris Hawk Optimization (HHO) algorithm and a K-Nearest Neighbor (KNN) forecasting framework. The method utilizes an improved simulated annealing mechanism and a Gaussian bare bone structure to improve the original HHO, termed SGHHO. To achieve optimal prediction performance and identify essential features, a refined simulated annealing mechanism is employed to mitigate the susceptibility of the original HHO algorithm to local optima. The algorithm employs a mechanism that boosts its global search ability by generating fresh solution sets at a specific likelihood. This mechanism dynamically adjusts the equilibrium between the exploration and exploitation phases, incorporating the Gaussian bare bone strategy. The best classification model (SGHHO-KNN) is developed to mine the key features with the improvement of both strategies. To assess the exceptional efficacy of the SGHHO algorithm, this investigation conducted a series of comparative trials employing the function set of IEEE CEC 2014. The outcomes of these experiments unequivocally demonstrate that the SGHHO algorithm outperforms the original HHO algorithm on 96.7% of the functions, substantiating its remarkable superiority. The algorithm can achieve the optimal value of the function on 67% of the tested functions and significantly outperforms other competing algorithms. In addition, the key features selected by the SGHHO-KNN model in the prediction experiment, including " Form of sharing economy in your region " and " Attitudes to the sharing economy ", are important for predicting the future trends of the sharing economy in this study. The results of the prediction demonstrate that the proposed model achieves an accuracy rate of 99.70% and a specificity rate of 99.38%. Consequently, the SGHHO-KNN model holds great potential as a reliable tool for forecasting the forthcoming trajectory of the sharing economy.
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Project description:An experiment is designed to shed light on how deception works. The experiment involves a twenty period sender/receiver game in which period 5 has more weight than other periods. In each period, the informed sender communicates about the realized state, the receiver then reports a belief about the state before being informed whether the sender lied. Throughout the interaction, a receiver is matched with the same sender who is either malevolent with an objective opposed to the receiver or benevolent always telling the truth. The main findings are: (1) in several variants (differing in the weight of the key period and the share of benevolent senders), the deceptive tactic in which malevolent senders tell the truth up to the key period and then lie at the key period is used roughly 25% of the time, (2) the deceptive tactic brings higher expected payoff than other observed strategies, and (3) a majority of receivers do not show cautiousness at the key period when no lie was made before. These observations do not match the predictions of the Sequential Equilibrium and can be organized using the analogy-based sequential equilibrium (ABSE) in which three quarters of subjects reason coarsely.
| S-EPMC8550209 | biostudies-literature
Project description:Background:The predominant focus of academic research on the sharing economy has been on Airbnb and Uber; to this extent, the diversity of business models ascribed to the sharing economy has not yet been sufficiently explored. Greater conceptual and empirical research is needed to increase understanding of business models in the sharing economy, particularly attributes that deliver on its purported sustainability potential. Objective:We aimed to elaborate an improved sharing economy business modelling tool intended to support the design and implementation of sharing economy business models (SEBMs) with improved sustainability performance. Methods:We used a structured approach to business modelling, morphological analysis, to articulate relevant business model attributes. Our analysis was informed by a narrative literature review of business and platform models in the sharing economy. We also iteratively tested, refined, and evaluated our analysis through three structured opportunities for feedback. Results:The output of the morphological analysis was a sharing economy business modelling tool for sustainability, with stipulated preconditions and descriptions of all business model attributes. Conclusion:The sharing economy is not sustainable by default, so we must be strategic and deliberate in how we design and implement SEBMs. The sharing economy business modelling tool should be of interest not only to researchers and practitioners, but also to advocacy organisations and policymakers who are concerned about the sustainability performance of sharing platforms.
| S-EPMC7323621 | biostudies-literature
Project description:Fluctuations in mental and bodily states have both been shown to be associated with negative affective experience. Here we examined how momentary fluctuations in attentional and cardiac states combine to regulate the perception of positive social value. Faces varying in trustworthiness were presented during a go/no-go letter target discrimination task synchronized with systolic or diastolic cardiac phase. Go trials lead to an attentional boosting of perceived trust on high trust and ambiguous neutral faces, suggesting attention both boosted existing and generated positive social value. Cardiac phase during face presentation interacted with attentional boosting of trust, enhancing high trust faces specifically during relaxed diastolic cardiac states. Confidence judgments revealed that attentional trust boosting, and its cardiac modulation, did not reflect altered perceptual or response fluency. These results provide evidence for how moment-to moment fluctuations in top-down mental and bottom-up bodily inputs combine to enhance a priori and generate de novo positive social value.
| S-EPMC7060330 | biostudies-literature
Project description:OBJECTIVE:To measure public trust in a health information sharing in a broadly defined health system (system trust), inclusive of health care, public health, and research; to identify individual characteristics that predict system trust; and to consider these findings in the context of national health initiatives (e.g., learning health systems and precision medicine) that will expand the scope of data sharing. DATA SOURCES:Survey data (n = 1,011) were collected in February 2014. STUDY DESIGN:We constructed a composite index of four dimensions of system trust-competency, fidelity, integrity, and trustworthiness. The index was used in linear regression evaluating demographic and psychosocial predictors of system trust. DATA COLLECTION:Data were collected by GfK Custom using a nationally representative sample and analyzed in Stata 13.0. PRINCIPAL FINDINGS:Our findings suggest the public's trust may not meet the needs of health systems as they enter an era of expanded data sharing. We found that a majority of the U.S. public does not trust the organizations that have health information and share it (i.e., the health system) in one or more dimensions. Together, demographic and psychosocial factors accounted for ~18 percent of the observed variability in system trust. Future research should consider additional predictors of system trust such as knowledge, attitudes, and beliefs to inform policies and practices for health data sharing.
| S-EPMC5867170 | biostudies-other
Project description:Thriving is a psychological state in which individuals experience a sense of vitality and a sense of learning. Thriving come from relational connections with others, and is deeply rooted in social systems. Theoretical literature suggests that thriving occurs in the presence of decision-making discretion, broad information sharing, and a climate of trust. However, no study has investigated these environmental factors empirically. Using a multiple-studies approach, we (a) established valid and reliable scale for each of these environmental factors using experimental vignettes, (b) confirmed the association of decision-making discretion, broad information sharing and climate of trust with thriving, and (c) identified the role of self-determination theory in determining these relationships. Our analysis was based on data collected from 512 Indian management students across five studies. The results indicate significant difference in thriving for high vs. low level for decision-making discretion, broad information sharing and climate of trust. The relationship of these environmental factors with thriving is mainly due to the fulfillment of the need for competence. Competence partially mediates the relationship of decision-making discretion with thriving, and fully mediates the relationship of broad information sharing and climate of trust with thriving. Autonomy, although positively related with the environmental factors, does not lead to thriving. Practical implications, limitations and research avenues are discussed.
| S-EPMC8959831 | biostudies-literature
Project description:Bacteriophage ("bacteria eaters") or phage is the collective term for viruses that infect bacteria. While most phages are pathogens that kill their bacterial hosts, the filamentous phages of the sub-class Inoviridae live in cooperative relationships with their bacterial hosts, akin to the principal behaviours found in the modern-day sharing economy: peer-to-peer support, to offset any burden. Filamentous phages impose very little burden on bacteria and offset this by providing service to help build better biofilms, or provision of toxins and other factors that increase virulence, or modified behaviours that provide novel motile activity to their bacterial hosts. Past, present and future biotechnology applications have been built on this phage-host cooperativity, including DNA sequencing technology, tools for genetic engineering and molecular analysis of gene expression and protein production, and phage-display technologies for screening protein-ligand and protein-protein interactions. With the explosion of genome and metagenome sequencing surveys around the world, we are coming to realize that our knowledge of filamentous phage diversity remains at a tip-of-the-iceberg stage, promising that new biology and biotechnology are soon to come.
| S-EPMC6549030 | biostudies-literature
Project description:The world can be a confusing place, which leads to a significant challenge: how do we figure out what is true? To accomplish this, children possess two relevant skills: reasoning about the likelihood of their own accuracy (metacognitive confidence) and reasoning about the likelihood of others' accuracy (mindreading). Guided by Signal Detection Theory and Simulation Theory, we examine whether these two self- and other-oriented skills are one in the same, relying on a single cognitive process. Specifically, Signal Detection Theory proposes that confidence in a decision is purely derived from the imprecision of that decision, predicting a tight correlation between decision accuracy and confidence. Simulation Theory further proposes that children attribute their own cognitive experience to others when reasoning socially. Together, these theories predict that children's self and other reasoning should be highly correlated and dependent on decision accuracy. In four studies (N = 374), children aged 4-7 completed a confidence reasoning task and selective social learning task each designed to eliminate confounding language and response biases, enabling us to isolate the unique correlation between self and other reasoning. However, in three of the four studies, we did not find that individual differences on the two tasks correlated, nor that decision accuracy explained performance. These findings suggest self and other reasoning are either independent in childhood, or the result of a single process that operates differently for self and others.Supplementary informationThe online version contains supplementary material available at 10.1007/s11409-021-09263-x.
| S-EPMC8550463 | biostudies-literature