Yet Another Bookmarks Service



[https://www.sciencedirect.com/science/article/pii/S0167268120300871] - - public:weinreich
behavior_change, design, strategy, theory - 4 | id:802639 -

We present a theoretical model to clarify the underlying mechanisms that drive individual decision making and responses to behavioral interventions, such as nudges. The model provides a theoretical framework that comprehensively structures the individual decision-making process applicable to a wide range of choice situations. We also identify the mechanisms behind the effectiveness of behavioral interventions—in particular, nudges—based on this structured decision-making process. Hence, the model can be used to predict under which circumstances, and in which choice situations, a nudge is likely to be effective.

[https://pure.mpg.de/rest/items/item_2492539_5/component/file_2495784/content] - - public:weinreich
behavior_change, design, policy - 3 | id:802638 -

Much of the discussion of behaviourally informed approaches has focused on ‘nudges’; that is, non-fiscal and non-regulatory interventions that steer (nudge) people in a specific direction while preserving choice. Less attention has been paid to boosts, an alternative evidence-based class of non-fiscal and non-regulatory intervention. The goal of boosts is to make it easier for people to exercise their own agency in making choices. For instance, when people are at risk of making poor health, medical or financial choices, the policy-maker – rather than steering behaviour through nudging – can take action to foster or boost individuals’ own decision-making competences.

[http://eprints.lse.ac.uk/108189/2/banerjee_chap_1.pdf] - - public:weinreich
behavior_change, design, policy - 3 | id:802637 -

This chapter goes beyond classic nudges in introducing public policy practitioners and researchers worldwide to a wide range of behavioural change interventions like boosts, thinks, and nudge pluses. These policy tools, much like their classic nudge counterpart, are libertarian, internality targeting and behaviourally informed policies that lie at the origin of the behavioural policy cube as originally conceived by Oliver. This chapter undertakes a review of these instruments, in systematically and holistically comparing them. Nudge pluses are truly hybrid nudge-think strategies, in that they combine the best features of the reflexive nudges and the more deliberative boosts (or, think) strategies. Going forward, the chapter prescribes the consideration of a wider policy toolkit in directing interventions to tackle societal problems and hopes to break the false synonymity of behavioural based policies with nudge-type interventions only

[https://pure.mpg.de/rest/items/item_2513866_5/component/file_2514744/content] - - public:weinreich
behavior_change, design, strategy - 3 | id:802636 -

To date, much of the discussion of behaviorally informed approaches has emphasized “nudges,” that is, interventions designed to steer people in a particular direction while preserving their freedom of choice. Yet behavioral science also provides support for a distinct kind of nonfiscal and noncoercive intervention, namely, “boosts.” The objective of boosts is to foster people’s competence to make their own choices—that is, to exercise their own agency. Building on this distinction, we further elaborate on how boosts are conceptually distinct from nudges: The two kinds of interventions differ with respect to (a) their immediate intervention targets, (b) their roots in different research programs, (c) the causal pathways through which they affect behavior, (d) their assumptions about human cognitive architecture, (e) the reversibility of their effects, (f) their programmatic ambitions, and (g) their normative implications.

[https://bootcamp.uxdesign.cc/com-b-experience-mapping-a-design-thinking-love-story-f09e3403495] - - public:weinreich
behavior_change, design, how_to, research, strategy - 5 | id:802634 -

In their maturity, the fields of experience strategy and behavior change design are moving past the casual flirtations of two complementary knowledge domains into a full fledged partnership: when we marry the design of behavioral interventions and the design of experiences, there’s a special power in combining the myriad frameworks from both domains. This becomes especially effective when the goal is not just to identify pain points in an existing experience journey or illustrate an ideal future one — but to make actionable recommendations that will help clients make the leap from actual to ideal.

[https://alistapart.com/article/engaged-excerpt/] - - public:weinreich
behavior_change, design, technology - 3 | id:744525 -

It’s not just about really liking a product (although you definitely want users to really like your product). With the right design elements, your users might embark on a meaningful bond with your technology, where they feel engaged in an ongoing, two-way relationship with an entity that understands something important about them, yet is recognizably non–human. This is a true emotional attachment that supplies at least some of the benefits of a human-to-human relationship. This type of connection can help your users engage more deeply and for a longer period of time with your product. And that should ultimately help them get closer to their behavior change goals.

[https://peoplescience.maritz.com/Articles/2020/Its-My-Life] - - public:weinreich
behavior_change, design, ethics - 3 | id:744524 -

The following is from Dr. Bucher’s forthcoming book, Engaged: Designing for Behavior Change. I chose this section because it touches upon a PeopleScience theme: being successful and effective behavioral practitioners while also, and primarily, being good.

[https://www.uxmatters.com/mt/archives/2020/09/engaged-designing-for-behavior-change-1.php] - - public:weinreich
behavior_change, design - 2 | id:744523 -

This is an excerpt from Amy Bucher’s book Engaged: Designing for Behavior Change. In this chapter, you’ll learn how to structure [users’ meaningful choices on their behavior-change journey] so that it’s easier for people to select good options that ultimately support their goals.

[https://www.nngroup.com/articles/summary-quant-sample-sizes/?utm_source=Alertbox&utm_campaign=6b433997b0-EMAIL_CAMPAIGN_2020_11_12_08_52_COPY_01&utm_medium=email&utm_term=0_7f29a2b335-6b433997b0-24361717] - - public:weinreich
design, quantitative, research - 3 | id:744486 -

40 participants is an appropriate number for most quantitative studies, but there are cases where you can recruit fewer users.

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