Does the Temporal Stability of Behavioral Intentions Moderate Intention-Behavior and Past Behavior-Future Behavior Relations?

When interacting with others, it is often important for you to know what they have done in similar situations in the past: to know their reputation. One reason is that their past behavior may be a guide to their future behavior. A second reason is that their past behavior may have qualified them for reward and cooperation, or for punishment and revenge. The fact that you respond positively or negatively to the reputation of others then generates incentives for them to maintain good reputations. This article surveys the game theory literature which analyses the mechanisms and incentives involved in reputation. It also discusses how experiments have shed light on strategic behavior involved in maintaining reputations, and the adequacy of unreliable and third party information (gossip) for maintaining incentives for cooperation.

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Small Garden, Big Impact: Emotional and Behavioral Responses of Visitors to a Rooftop Atrium in a Major Hospital

HERD Health Environments Research & Design Journal ◽

10.1177/1937586721992799 ◽

2021 ◽

pp. 193758672199279

Author(s):

Kelly Martin ◽

Luana Nanu ◽

Wi-Suk Kwon ◽

David Martin

Keyword(s):

United States ◽

Empirical Research ◽

Behavioral Intentions ◽

Southeastern United States ◽

Behavioral Responses ◽

Future Behavior ◽

Healing Garden ◽

Healing Gardens

Purpose: To measure hospital visitors’ satisfaction with a rooftop atrium and its resultant impact on the visitors’ behavioral intentions toward the healing garden, the hospital, and overall satisfaction with the hospital. Background: There is a significant lack of empirical research that links the emotional and behavioral responses toward healing gardens and the hospitals providing them. Methods: A purposeful sample of 96 visitors to the healing garden in the rooftop atrium of a surgery building in a major hospital in the Southeastern United States completed a survey based on Roger Ulrich’s Theory of Supportive Gardens and the Stimulus, Organism, Response (S-O-R) paradigm. Results: Findings of this study suggest visitors’ experience with the healing garden can lead to overall satisfaction with the hospital and behavioral intentions toward the hospital. Visitors’ satisfaction with the healing garden significantly predicted their satisfaction with the hospital, their intend to revisit the hospital, and their intend to recommend it. Conclusions: This study demonstrates that a small healing garden can be a powerful enough space to impact visitors’ overall satisfaction with the hospital and their intentions regarding their future behavior toward the hospital, such as revisiting or recommending the hospital.

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The mediating role of constructs representing reasoned-action and automatic processes on the past behavior-future behavior relationship

Social Science & Medicine ◽

10.1016/j.socscimed.2020.113085 ◽

2020 ◽

Vol 258 ◽

pp. 113085 ◽

Cited By ~ 4

Author(s):

Daniel J. Brown ◽

Martin S. Hagger ◽

Kyra Hamilton

Keyword(s):

Reasoned Action ◽

Automatic Processes ◽

Mediating Role ◽

The Past ◽

Past Behavior ◽

Future Behavior

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Destination Image Components and Word-of-Mouth Intentions in Urban Tourism: A Multigroup Approach

Journal of Hospitality & Tourism Research ◽

10.1177/1096348015584443 ◽

2015 ◽

Vol 42 (4) ◽

pp. 503-527 ◽

Cited By ~ 48

Author(s):

Dimitra Papadimitriou ◽

Kyriaki (Kiki) Kaplanidou ◽

Artemisia Apostolopoulou

Keyword(s):

Behavior Analysis ◽

Behavioral Intentions ◽

Word Of Mouth ◽

Urban Tourism ◽

Destination Image ◽

Future Behavior ◽

Structural Relationships ◽

Local Residents

The purpose of this study was to explore differences among three distinct groups, namely local residents, past tourists, and prospective tourists, in their perceptions of cognitive, affective, and overall image of a city destination and their future behavior. Analysis of data generally confirmed previously established structural relationships of cognitive and affective image, overall destination image, and word-of-mouth intentions. However, differences were identified among the three groups in terms of their destination image perceptions and their behavioral intentions to engage in word-of-mouth communications. Specifically, residents who engaged in word-of-mouth were primarily influenced by the cognitive and affective destination image components, while tourists relied on overall image perceptions.

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Influencing Future Behavior by Priming Past Behavior: A Test in the Context of Petrified Forest National Park

Leisure Sciences ◽

10.1080/014904099273273 ◽

1999 ◽

Vol 21 (1) ◽

pp. 31-42 ◽

Cited By ~ 13

Author(s):

David Trafimow, William T. Borrie

Keyword(s):

National Park ◽

Past Behavior ◽

Future Behavior ◽

Petrified Forest National Park ◽

Petrified Forest

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The Roles of Behavioral and Implementation Intentions in Changing Physical Activity in Young Children With Low Socioeconomic Status

Journal of Sport and Exercise Psychology ◽

10.1123/jsep.32.3.359 ◽

2010 ◽

Vol 32 (3) ◽

pp. 359-376 ◽

Cited By ~ 23

Author(s):

Christopher J. Armitage ◽

Christine A. Sprigg

Keyword(s):

Physical Activity ◽

Socioeconomic Status ◽

Low Socioeconomic Status ◽

Implementation Intentions ◽

Good Reason ◽

Implementation Intention ◽

Low Socioeconomic ◽

Past Behavior ◽

Future Behavior ◽

Children’S Physical Activity

There is a dearth of research examining physical activity in children aged 6–10 years with low socioeconomic status, despite the fact there is good reason to suspect this is a critical period when physical activity habits are created. Physical activity and theory of planned behavior variables were measured at three time points, and children (N = 77) randomized to the experimental condition were additionally asked to form an implementation intention. Intention was a potent mediator of the past behavior–future behavior relationship and the implementation intention intervention significantly increased physical activity compared with the control condition. The findings suggest that physical activity can be increased in children aged 6–10 years with low socioeconomic status and that implementation intentions might enhance the effectiveness of children’s physical activity programs.

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Predicting Premeditation: Future Behavior is Seen as More Intentional than Past Behavior

SSRN Electronic Journal ◽

10.2139/ssrn.1879558 ◽

2011 ◽

Author(s):

Zachary C. Burns ◽

Eugene M. Caruso ◽

Daniel M. Bartels

Keyword(s):

Past Behavior ◽

Future Behavior

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Segmentation of Time Series Data

Encyclopedia of Data Warehousing and Mining, Second Edition ◽

10.4018/978-1-60566-010-3.ch267 ◽

2011 ◽

pp. 1753-1758 ◽

Cited By ~ 3

Author(s):

Parvathi Chundi ◽

Daniel J. Rosenkrantz

Keyword(s):

Time Series ◽

Time Series Data ◽

Large Fraction ◽

Series Data ◽

Past Behavior ◽

Future Behavior ◽

Time Series Segmentation ◽

Original Time ◽

High Level ◽

Conclusion Section

Time series data is usually generated by measuring and monitoring applications, and accounts for a large fraction of the data available for analysis purposes. A time series is typically a sequence of values that represent the state of a variable over time. Each value of the variable might be a simple value, or might have a composite structure, such as a vector of values. Time series data can be collected about natural phenomena, such as the amount of rainfall in a geographical region, or about a human activity, such as the number of shares of GoogleTM stock sold each day. Time series data is typically used for predicting future behavior from historical performance. However, a time series often needs further processing to discover the structure and properties of the recorded variable, thereby facilitating the understanding of past behavior and prediction of future behavior. Segmentation of a given time series is often used to compactly represent the time series (Gionis & Mannila, 2005), to reduce noise, and to serve as a high-level representation of the data (Das, Lin, Mannila, Renganathan & Smyth, 1998; Keogh & Kasetty, 2003). Data mining of a segmentation of a time series, rather than the original time series itself, has been used to facilitate discovering structure in the data, and finding various kinds of information, such as abrupt changes in the model underlying the time series (Duncan & Bryant, 1996; Keogh & Kasetty, 2003), event detection (Guralnik & Srivastava, 1999), etc. The rest of this chapter is organized as follows. The section on Background gives an overview of the time series segmentation problem and solutions. This section is followed by a Main Focus section where details of the tasks involved in segmenting a given time series and a few sample applications are discussed. Then, the Future Trends section presents some of the current research trends in time series segmentation and the Conclusion section concludes the chapter. Several important terms and their definitions are also included at the end of the chapter.

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