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Understanding the stages and pathways of travel behavior change induced by technology-based intervention among university students
•A mobility behaviour change system, called Blaze, achieving a mobility shift among students from Manila, Philippines.•Stage model of self-regulated behavioral change (SSBC) is used as a theoretical framework.•Identification of the causal pathway between technology interventions and behaviour change...
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Published in: | Transportation research. Part F, Traffic psychology and behaviour Traffic psychology and behaviour, 2018-11, Vol.59, p.98-114 |
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creator | Sunio, Varsolo Schmöcker, Jan-Dirk Kim, Junghwa |
description | •A mobility behaviour change system, called Blaze, achieving a mobility shift among students from Manila, Philippines.•Stage model of self-regulated behavioral change (SSBC) is used as a theoretical framework.•Identification of the causal pathway between technology interventions and behaviour change.•Illustration that impact paths differ depending on stage membership.•Extension of SSBC by distinguishing post-action as to whether the behaviour is on initiation or under maintenance.
We describe how a mobility behavior change support system, called Blaze, is able to achieve a shift in changing the travel behavior of university students. We identify a causal pathway linking the effect of the technology intervention to its behavioral outcome through the mediation of a number of variables. The stage model of self-regulated behavioral change (SSBC) is used as a theoretical framework to understand how the outcome may be influenced by determinants (conceptual theory), and how the determinants may be activated by different intervention types (action theory). Using longitudinal data from a social experiment conducted over a month at a university in the Philippines, we test three hypotheses regarding the mechanism of change induced by Blaze. Our main findings suggest, in agreement with SSBC, that travel behavior change is achieved by a transition through a temporal sequence of four stages: predecision, pre-action, action and post-action. In an extension from SSBC, we further distinguish post-action depending on whether the behavior is on initiation or under maintenance. We observe that the former (initiation) is characterized by instability (either relapse or progress), while the latter (maintenance) by stability. Moreover, we validate most of the determinants of intentions as postulated by the stage model. Finally, we find that that Blaze can significantly change only the proximate implementation intention and not the more distal ones (e.g. goal and behavioral intentions). We discuss the implications of our results on the potential role of technology interventions in mobility management. |
doi_str_mv | 10.1016/j.trf.2018.08.017 |
format | article |
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We describe how a mobility behavior change support system, called Blaze, is able to achieve a shift in changing the travel behavior of university students. We identify a causal pathway linking the effect of the technology intervention to its behavioral outcome through the mediation of a number of variables. The stage model of self-regulated behavioral change (SSBC) is used as a theoretical framework to understand how the outcome may be influenced by determinants (conceptual theory), and how the determinants may be activated by different intervention types (action theory). Using longitudinal data from a social experiment conducted over a month at a university in the Philippines, we test three hypotheses regarding the mechanism of change induced by Blaze. Our main findings suggest, in agreement with SSBC, that travel behavior change is achieved by a transition through a temporal sequence of four stages: predecision, pre-action, action and post-action. In an extension from SSBC, we further distinguish post-action depending on whether the behavior is on initiation or under maintenance. We observe that the former (initiation) is characterized by instability (either relapse or progress), while the latter (maintenance) by stability. Moreover, we validate most of the determinants of intentions as postulated by the stage model. Finally, we find that that Blaze can significantly change only the proximate implementation intention and not the more distal ones (e.g. goal and behavioral intentions). We discuss the implications of our results on the potential role of technology interventions in mobility management.</description><identifier>ISSN: 1369-8478</identifier><identifier>EISSN: 1873-5517</identifier><identifier>DOI: 10.1016/j.trf.2018.08.017</identifier><language>eng</language><publisher>Oxford: Elsevier Ltd</publisher><subject>Behavioral sciences ; Determinants ; Mechanism of change ; Mobility ; Mobility behavior change support system ; Mobility management ; Stability ; Stage model ; Students ; Support systems ; Technology adoption ; Technology-based intervention ; Travel ; Travel demand management ; University students</subject><ispartof>Transportation research. Part F, Traffic psychology and behaviour, 2018-11, Vol.59, p.98-114</ispartof><rights>2018 Elsevier Ltd</rights><rights>Copyright Elsevier Science Ltd. Nov 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-4127395848d82845acfa8dcc5bb901aa56a395897ef4f15551c5a0c0dd28105a3</citedby><cites>FETCH-LOGICAL-c353t-4127395848d82845acfa8dcc5bb901aa56a395897ef4f15551c5a0c0dd28105a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Sunio, Varsolo</creatorcontrib><creatorcontrib>Schmöcker, Jan-Dirk</creatorcontrib><creatorcontrib>Kim, Junghwa</creatorcontrib><title>Understanding the stages and pathways of travel behavior change induced by technology-based intervention among university students</title><title>Transportation research. Part F, Traffic psychology and behaviour</title><description>•A mobility behaviour change system, called Blaze, achieving a mobility shift among students from Manila, Philippines.•Stage model of self-regulated behavioral change (SSBC) is used as a theoretical framework.•Identification of the causal pathway between technology interventions and behaviour change.•Illustration that impact paths differ depending on stage membership.•Extension of SSBC by distinguishing post-action as to whether the behaviour is on initiation or under maintenance.
We describe how a mobility behavior change support system, called Blaze, is able to achieve a shift in changing the travel behavior of university students. We identify a causal pathway linking the effect of the technology intervention to its behavioral outcome through the mediation of a number of variables. The stage model of self-regulated behavioral change (SSBC) is used as a theoretical framework to understand how the outcome may be influenced by determinants (conceptual theory), and how the determinants may be activated by different intervention types (action theory). Using longitudinal data from a social experiment conducted over a month at a university in the Philippines, we test three hypotheses regarding the mechanism of change induced by Blaze. Our main findings suggest, in agreement with SSBC, that travel behavior change is achieved by a transition through a temporal sequence of four stages: predecision, pre-action, action and post-action. In an extension from SSBC, we further distinguish post-action depending on whether the behavior is on initiation or under maintenance. We observe that the former (initiation) is characterized by instability (either relapse or progress), while the latter (maintenance) by stability. Moreover, we validate most of the determinants of intentions as postulated by the stage model. Finally, we find that that Blaze can significantly change only the proximate implementation intention and not the more distal ones (e.g. goal and behavioral intentions). We discuss the implications of our results on the potential role of technology interventions in mobility management.</description><subject>Behavioral sciences</subject><subject>Determinants</subject><subject>Mechanism of change</subject><subject>Mobility</subject><subject>Mobility behavior change support system</subject><subject>Mobility management</subject><subject>Stability</subject><subject>Stage model</subject><subject>Students</subject><subject>Support systems</subject><subject>Technology adoption</subject><subject>Technology-based intervention</subject><subject>Travel</subject><subject>Travel demand management</subject><subject>University students</subject><issn>1369-8478</issn><issn>1873-5517</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kMFu2zAMho1iBZp1fYDeBOzsVLKtWMZOQ7C1BQr0spwFWqJjBYmUSbIHX_fkZZCdBxCgRPLXT31F8Sj4WnCxeTqscxzWFRdqzSlEe1OshGrrUkrRfqJzvelK1bTqrvic0oFz3lSiXRV_d95iTBm8dX7P8oiMLntMjCrsDHn8A0tiYWA5woxH1uMIswuRmRH8HpnzdjJoWb-wjGb04Rj2S9lDoprzGeOMPrvgGZwCGUzezeTn8kI-k6Ve-lLcDnBM-PAv3xe7nz9-bV_Kt_fn1-33t9LUss5lI6q27qRqlFWVaiSYAZQ1RvZ9xwWA3MCl3bU4NIOQ9G8jgRtubaUEl1DfF1-v755j-D1hyvoQpujJUlcXPLzqak5T4jplYkgp4qDP0Z0gLlpwfUGtD5pQ6wtqzSlES5pvVw3S-rPDqJNx6AmLi2iytsH9R_0BrQeJ4g</recordid><startdate>20181101</startdate><enddate>20181101</enddate><creator>Sunio, Varsolo</creator><creator>Schmöcker, Jan-Dirk</creator><creator>Kim, Junghwa</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>20181101</creationdate><title>Understanding the stages and pathways of travel behavior change induced by technology-based intervention among university students</title><author>Sunio, Varsolo ; Schmöcker, Jan-Dirk ; Kim, Junghwa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-4127395848d82845acfa8dcc5bb901aa56a395897ef4f15551c5a0c0dd28105a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Behavioral sciences</topic><topic>Determinants</topic><topic>Mechanism of change</topic><topic>Mobility</topic><topic>Mobility behavior change support system</topic><topic>Mobility management</topic><topic>Stability</topic><topic>Stage model</topic><topic>Students</topic><topic>Support systems</topic><topic>Technology adoption</topic><topic>Technology-based intervention</topic><topic>Travel</topic><topic>Travel demand management</topic><topic>University students</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sunio, Varsolo</creatorcontrib><creatorcontrib>Schmöcker, Jan-Dirk</creatorcontrib><creatorcontrib>Kim, Junghwa</creatorcontrib><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Transportation research. Part F, Traffic psychology and behaviour</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sunio, Varsolo</au><au>Schmöcker, Jan-Dirk</au><au>Kim, Junghwa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Understanding the stages and pathways of travel behavior change induced by technology-based intervention among university students</atitle><jtitle>Transportation research. Part F, Traffic psychology and behaviour</jtitle><date>2018-11-01</date><risdate>2018</risdate><volume>59</volume><spage>98</spage><epage>114</epage><pages>98-114</pages><issn>1369-8478</issn><eissn>1873-5517</eissn><abstract>•A mobility behaviour change system, called Blaze, achieving a mobility shift among students from Manila, Philippines.•Stage model of self-regulated behavioral change (SSBC) is used as a theoretical framework.•Identification of the causal pathway between technology interventions and behaviour change.•Illustration that impact paths differ depending on stage membership.•Extension of SSBC by distinguishing post-action as to whether the behaviour is on initiation or under maintenance.
We describe how a mobility behavior change support system, called Blaze, is able to achieve a shift in changing the travel behavior of university students. We identify a causal pathway linking the effect of the technology intervention to its behavioral outcome through the mediation of a number of variables. The stage model of self-regulated behavioral change (SSBC) is used as a theoretical framework to understand how the outcome may be influenced by determinants (conceptual theory), and how the determinants may be activated by different intervention types (action theory). Using longitudinal data from a social experiment conducted over a month at a university in the Philippines, we test three hypotheses regarding the mechanism of change induced by Blaze. Our main findings suggest, in agreement with SSBC, that travel behavior change is achieved by a transition through a temporal sequence of four stages: predecision, pre-action, action and post-action. In an extension from SSBC, we further distinguish post-action depending on whether the behavior is on initiation or under maintenance. We observe that the former (initiation) is characterized by instability (either relapse or progress), while the latter (maintenance) by stability. Moreover, we validate most of the determinants of intentions as postulated by the stage model. Finally, we find that that Blaze can significantly change only the proximate implementation intention and not the more distal ones (e.g. goal and behavioral intentions). We discuss the implications of our results on the potential role of technology interventions in mobility management.</abstract><cop>Oxford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.trf.2018.08.017</doi><tpages>17</tpages></addata></record> |
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subjects | Behavioral sciences Determinants Mechanism of change Mobility Mobility behavior change support system Mobility management Stability Stage model Students Support systems Technology adoption Technology-based intervention Travel Travel demand management University students |
title | Understanding the stages and pathways of travel behavior change induced by technology-based intervention among university students |
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