An Interactive Input–Process–Output Model of Social Influence in Decision-Making Groups

2014 ◽  
Vol 45 (6) ◽  
pp. 704-730 ◽  
Author(s):  
Charles Pavitt
Keyword(s):  
Decision Making ◽  
Social Influence ◽  
Input Process ◽  
Process Output

An Input–Process–Output Model of Pilot Core Competencies

2017 ◽  
Vol 7 (2) ◽  
pp. 78-85 ◽  
Author(s):  
Heikki Mansikka ◽  
Don Harris ◽  
Kai Virtanen
Keyword(s):  
Path Analysis ◽  
Team Performance ◽  
Core Competencies ◽  
Core Competency ◽  
Principal Component ◽  
Analysis Model ◽  
Input Process ◽  
The Core ◽  
Performance Framework ◽  
Process Output

Abstract. The aim of this study was to investigate the relationship between the flight-related core competencies for professional airline pilots and to structuralize them as components in a team performance framework. To achieve this, the core competency scores from a total of 2,560 OPC (Operator Proficiency Check) missions were analyzed. A principal component analysis (PCA) of pilots’ performance scores across the different competencies was conducted. Four principal components were extracted and a path analysis model was constructed on the basis of these factors. The path analysis utilizing the core competencies extracted adopted an input–process–output’ (IPO) model of team performance related directly to the activities on the flight deck. The results of the PCA and the path analysis strongly supported the proposed IPO model.

scholarly journals Humans rely more on algorithms than social influence as a task becomes more difficult

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric Bogert ◽  
Aaron Schecter ◽  
Richard T. Watson
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Social Influence ◽  
Correct Answer ◽  
Online Reviews ◽  
Personal Networks ◽  
Human Judgment ◽  
Individual Decision ◽  
Individual Decision Making

AbstractAlgorithms have begun to encroach on tasks traditionally reserved for human judgment and are increasingly capable of performing well in novel, difficult tasks. At the same time, social influence, through social media, online reviews, or personal networks, is one of the most potent forces affecting individual decision-making. In three preregistered online experiments, we found that people rely more on algorithmic advice relative to social influence as tasks become more difficult. All three experiments focused on an intellective task with a correct answer and found that subjects relied more on algorithmic advice as difficulty increased. This effect persisted even after controlling for the quality of the advice, the numeracy and accuracy of the subjects, and whether subjects were exposed to only one source of advice, or both sources. Subjects also tended to more strongly disregard inaccurate advice labeled as algorithmic compared to equally inaccurate advice labeled as coming from a crowd of peers.

Exploring the Effects of Individual Differences in Function Structure Modeling Behaviors

2021 ◽  
Author(s):  
Apurva Patel ◽  
Joshua D. Summers
Keyword(s):  
Individual Differences ◽  
Goal Orientation ◽  
Structure Modeling ◽  
Risk Propensity ◽  
Input Process ◽  
Function Structure ◽  
Modeling Process ◽  
Survey Instruments ◽  
Process Output ◽  
Protocol Study

Abstract This paper presents an exploratory study conducted to understand the role of individual differences between designers in the function modeling process and with respect to final models. An input-process-output framework of function modeling is proposed to systematically approach this theory building and discovery research study. Four measures of individual differences are identified of interest. These include the systemizing quotient, goal orientation, risk propensity, and concept design thinking style. Each metric is composed of multiple items that can be assessed through survey instruments. A previously developed protocol study is used to capture function modeling behaviors and a final function structure model. Data collected from the survey instruments and protocol study is processed to generate input, process, and output measures. A regression-based analysis is used to identify correlations in three groups: input-process, input-output, and process-output. Potential correlations of interest are identified within each group. Implications of these correlations are discussed from a function structure modeling perspective and hypotheses for future research are identified based on the patterns observed in this study. Three testable hypotheses are proposed for future investigation: (1) Goal orientation has no effect on activity distribution in the function modeling process, (2) Thinking style has no effect on the function modeling process, and (3) Risk propensity has no effect on element distribution in the function modeling process. Finally, an anticipated experiment is outlined to investigate one of the potential relationships discovered in this study.

scholarly journals Liegt die Zukunft der Teamforschung in ihrer Vergangenheit? Auf dem Weg zu einem ganzheitlich-dynamischen Teamverständnis

2018 ◽  
Vol 40 (3) ◽  
pp. 301-321
Author(s):  
Michael W. Busch
Keyword(s):  
Team Performance ◽  
International Research ◽  
Team Size ◽  
Input Process ◽  
Causal Explanations ◽  
Performance Variables ◽  
Team Research ◽  
Holistic Understanding ◽  
Emergent States ◽  
Process Output

Abstract The international research on teams, which is inspired by the input-process-output model, is mostly empirical. Researchers in this field look for causal explanations between independent (e.g., team size and team composition) and dependent (e.g., team performance) variables. Recently, some critics have pointed to the deficits in this model. Especially, the temporal, contextual, and dynamic aspects of teams need to be investigated further (multilevel approach). Emergent states, such as team cognitions, team emotions, and team hierarchies, comprise a promising field of study that leads to a more comprehensive and holistic understanding of teams. These emergent states offer an opportunity to reconcile former concepts (Lewin’s gestalt, Koestler’s holarchy, and Cattell’s syntality) with topical team research. Therefore, the future of research on teams may partly lie in its past.

Development of a Social Distancing Monitoring System in Korea: Results of a Modified Delphi Process (Preprint)

2021 ◽  
Author(s):  
Heeyoung Lee ◽  
Suin Seo ◽  
Jin-Ok Han ◽  
Sool Shin
Keyword(s):  
Monitoring System ◽  
Surveillance System ◽  
Response Rate ◽  
Delphi Process ◽  
Surveillance Systems ◽  
Input Process ◽  
Social Distancing ◽  
Modified Delphi ◽  
Process Output ◽  
Different Levels

BACKGROUND Since the COVID-19 pandemic is an ongoing situation in most countries worldwide, a “social distancing” policy as a non-pharmaceutical intervention has been implemented for several months in many countries including Korea. Social distancing policies work in different ways and at different levels. In addition, various forms of surveillance systems have been implemented in different countries. However, there is an almost complete lack of specific surveillance system in Korea to effectively monitor social distancing policy. OBJECTIVE This study aims to develop a monitoring system for social distancing measures in Korea to evaluate and improve the implemented policy. METHODS A draft monitoring system was developed after reviewing Korea's social distancing measures (central and local government briefings) and checking available data for applications. The modified Delphi process was used to evaluate the draft of the monitoring system. In total, 27 experts participated in the evaluation. The round 1 evaluation includes (1) commenting on the composition of the monitoring fields (open response), (2) monitoring indicators for each monitoring field (10-point Likert scale), and (3) commenting on the source of data used to develop the monitoring system (open response). In the round 2 evaluation, 55 indicators, excepting open responses, were re-evaluated. RESULTS The response rate for the Delphi survey was 100% in both the first and second rounds. Of the 55 indicators, 14 were excluded according to experts’ open response comments, as these indicators did not satisfy the quantitative criteria. Finally, 41 indicators were included with 12 available data sources. The monitoring system domain was divided into input, process/output, and result. CONCLUSIONS This study is significant in that it is the first in Korea to develop a comprehensive monitoring system for social distancing policy, and is applicable to estimates utilizing data that are immediately available for each indicator. Furthermore, the developed monitoring system could be a reference for other countries that require the development of such systems to monitor social distancing measures.

Information Traffic and Information Effectiveness

2016 ◽  
Vol 13 (2) ◽  
pp. 21-36 ◽  
Author(s):  
Bixia Xu ◽  
Zhulin Huang
Keyword(s):  
Information Search ◽  
Accounting Information ◽  
Input Process ◽  
Investor Attention ◽  
Economic Downturns ◽  
Different Types ◽  
Process Output ◽  
Concept Of Information ◽  
Types Of Information ◽  
The Impact

ABSTRACT Search engines are among the most important information technology (IT) applications and platforms on which to conduct information search. This study contributes by investigating whether and how the search engine-enabled information search is related to accounting information effectiveness. We develop the concept of information traffic to conceptualize investor IT-enabled information search activities and to explore whether the searches captured by this concept provide any insights for understanding and enhancing accounting information effectiveness. Building upon the input-process-output model (Maines and McDaniel 2000) and with a sample of 59 accounting information items, we report that information items with higher information traffic have greater ability to explain and predict firm market value (i.e., higher information effectiveness). The impact of information traffic on information effectiveness is higher for economic upturns than for economic downturns and differs among different types of information. We propose a conceptual measure that integrates both information traffic and information effectiveness to capture information relative importance and to suggest empirically an order in importance of the ten types of information we investigate. Our dynamic analysis of information traffic reveals a significant increase of investor IT-enabled information search in the post-financial-crisis period. It also shows higher search increases for accounting items that received previously scant investor attention.

Marshmallows and Braking Systems

2021 ◽  
pp. 105-122
Author(s):  
Craig J. Bryan
Keyword(s):  
Decision Making ◽  
Mental Illness ◽  
Suicide Attempt ◽  
Social Influence ◽  
Emotional Distress ◽  
Basic Concept ◽  
Decision Making Process ◽  
The Past ◽  
Internal States ◽  
Decision Making Processes

This chapter argues that suicide can be more usefully understood as a consequence of decision-making processes that are vulnerable to environmental and social influence rather than a consequence of internal states or traits such as mental illness. Mental illness and emotional distress more generally are better understood as one particular context within which the decision to make a suicide attempt or not often presents itself, but this does not mean that mental illness is the only context within which this choice is considered. This also does not mean that mental illness causes suicide. The basic concept involved in the marshmallow experiment—decision-making under different conditions—has received increased attention in the past decade among suicide researchers. Studies reveal that the decision-making process of someone who almost died as a result of a suicide attempt was no different from the decision-making process of someone who had never attempted suicide, was not currently suicidal, and did not have a mental illness. This finding lines up with the idea that there can be multiple pathways to suicide.

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