Old Habits Die Hard

Walker, Ian; Thomas, Gregory Owen; Verplanken, Bas

doi:10.1177/0013916514549619

Cited by 173 publications

(44 citation statements)

References 37 publications

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“…These two latter elements are obviously more context-dependent than the former. This echoes some recent findings on travel habit formation and decay where it shown that "weakened habits alone cannot predict or explain who changed their behaviour after the relocation" [53] (p. 1100).…”

Section: Habit Strength and The Extent Of Effort Requiredsupporting

confidence: 86%

“…As acknowledged in [57], habituation thus constitutes the mechanism through which "active" agents adjust their cognitive perceptions, matters of appreciation and normative judgements in coherent structures. The strength of these coherent structures may explain a puzzling result from the study performed by [53] where it is shown that an extant transport habit does not suddenly disappear (but rather gradually decay) even in the case of a change of mode. This takes us back to a central feature of the VEE perspective which distinguishes the genotype (i.e., the underlying structure) from its phenotypic manifestation (i.e., the habitual action per se).…”

Section: Car-use Habits and The Importance Of Associated Practicesmentioning

confidence: 99%

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Recasting the Understanding of Habits for Behaviour-Oriented Policies in Transportation

Maréchal

2018

Sustainability

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Abstract:The role of habits in influencing transportation behaviour is acknowledged in many studies. However, most of these analyses draw on a narrow perspective of habits. In this paper, we adopt a reversed perspective regarding the interplay between habits and rationality. The insightfulness of this perspective is illustrated with the findings of two empirical studies on urban transportation. This paper shows that the underlying structure (i.e., the "genotype") behind the phenotypic manifestation of a habit is essential to grasp for getting a better understanding of the role played by habits in explaining car use. The framework of habitual practices is then put forward in discussing the results. Its rationale is to provide a characterisation of the interconnected elements that make and shape the transportation practices, together with important aspects regarding how they are formed and sustained over time. Adequately picturing both constituent elements as well as dynamic aspects is crucial for explaining the strength of habitual practices and thus car dependence. In doing so, the framework of habitual practices could thus well be of help for policy-makers in reflecting on the design of efficient and innovative interventions for the transition towards more sustainable transportation behaviours.

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Section: Habit Strength and The Extent Of Effort Requiredsupporting

confidence: 86%

Section: Car-use Habits and The Importance Of Associated Practicesmentioning

confidence: 99%

Recasting the Understanding of Habits for Behaviour-Oriented Policies in Transportation

Maréchal

2018

Sustainability

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“…The present study also included ratings of habit which has only rarely been measured in the context of travel behaviour market segmentation research (see Krizek and El-Geneidy 2007, for one exception). Considering that travel mode choice often involves a strong habitual component (Domarchi et al 2008;Donald et al 2014;Klöckner and Matthies 2004;Verplanken et al 1997;Walker et al 2014), including habit as an additional factor has the potential to improve taxonomies of different traveller types. In their recent work, Thomas and Walker (2015) illustrated that satisfaction and habit may vary significantly between mode users and thus may also be suitable to discriminate between traveller types.…”

Section: The Present Studymentioning

confidence: 99%

Do supra-modal traveller types exist? A travel behaviour market segmentation using Goal framing theory

Bösehans

Walker

2018

Transportation

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Travel behaviour market segmentations have become a popular method of identifying different types of car users, bicyclists or public transport users. However, while previous studies have looked at different types of users within single modes, such as the car, little research has explored the existence of traveller types transcending modes. The study presented here is an extension of an earlier segmentation study that distinguished travellers based on their individual preferences, yet did so independent of their current mode choice. The data came from a travel survey at a middle-sized UK university and were analysed using a combination of hierarchical and iterative partitioning methods. Crucially, however, the current study uses a different theoretical framework to previous segmentation research-goal framing theory-which may more adequately explain the findings than models used in the past such as the theory of planned behaviour. The findings supported earlier work, suggesting the presence of seemingly stable traveller types that cut across modes and can be distinguished based on gain, hedonic and normative goals. This has important implications for policies aimed at encouraging mode change which may have been too preoccupied with changing people's attitudes rather than paying attention to people's underlying travel preferences.

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“…For example, several studies have found that people are more likely to establish new behavior patterns after moving to a new environment (Bamberg 2006;Dolnicar and Grun 2009;Walker et al 2014). In an attempt to decrease food waste in the well-defined environment of hotel buffets, Kallbekken and Saelen (2013) have identified some simple changes to decrease waste caused by guests loading too much food on their plate.…”

Section: The Influence Of Habits and Environmental Stimulimentioning

confidence: 99%

Consumers and their behavior: state of the art in behavioral science supporting use phase modeling in LCA and ecodesign

Sorrentino

Woelbert

Sala

2016

Int J Life Cycle Assess

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Purpose Life cycle thinking and assessment require a holistic approach to the evaluation of product supply chains. An assessment from raw material extraction to end of life of any products is based on modeling a wide number of aspects and options, e.g., at technological, geographical, and temporal levels. Since the use phase is one of the most contributing life cycle stages for some products (e.g., appliance, housing, cars), a robust modeling of this stage is fundamental. Several attempts to better modeling use-phase have been performed; however, so far no systematic study is available on how to integrate behavioral science (BS) insights into LCA. This is even more important when the impact of the product under consideration is strongly determined by the use phase relatively to other life cycle stages. The aim of this paper is to explore how behavioral science has been used to date and how BS can contribute towards more robust modeling of use phase in LCA and as basis for a behavior-driven ecodesign. Methods We identified the key areas in which LCA and ecodesign may benefit from integrating insights from behavioral science and developing a conceptual model. Both robust modeling and the design of behavior change interventions rest on a sound understanding of behavior in the specific context of interest though empirical investigation. Hence, we reviewed literature on behavioral science and introduce key drivers of human behavior that are relevant in the context of use phase modeling and ecodesign. We provide examples where these were applied to facilitate the integration of BS elements by practitioners. Results and discussion Consumer's behavior is increasingly recognized as one of the drivers of overall environmental impact of a product, and some examples of use of BS for LCA are available in literature. We suggest that behavioral science can be useful in the context of life cycle assessment in two ways: measuring behavior and assessing potential and means for changing behavior. Specifically, insights and methods from behavioral sciences could be applied for assessing variability of consumer behavior, understanding leverages for behavioral changes, and possible rebound effects. Conclusions This insight may help to model the use phase more accurately, to identify realistic scenarios, and to support behavior-driven eco-innovation.

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Old Habits Die Hard

Cited by 173 publications

References 37 publications

Recasting the Understanding of Habits for Behaviour-Oriented Policies in Transportation

Recasting the Understanding of Habits for Behaviour-Oriented Policies in Transportation

Do supra-modal traveller types exist? A travel behaviour market segmentation using Goal framing theory

Consumers and their behavior: state of the art in behavioral science supporting use phase modeling in LCA and ecodesign

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