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Online flight booking websites compare airfares, convenience and other consumer relevant attributes. Environmental concerns are typically not addressed, even though aviation is the most emission-intensive mode of transportation. This article demonstrates the potential for digital nudges to facilitate more environmentally friendly decision-making on online flight booking websites.

The authors used the digital nudging design process to implement two nudging interventions in an experimental setting on a fictitious flight booking website. The two nudging interventions are (1) an informational nudge, presented as an emission label, and (2) an understanding mapping nudge, presented as an emission converter.

This article finds that both digital nudges are useful interventions in online choice environments; however, emission labels more effectively encourage sustainable booking behavior.

The contributions of this article are twofold. In contribution to research, this article builds on existing research in sustainability contexts and successfully evaluates the effectiveness of anchoring and understanding mapping heuristics to influence sustainable decision-making in virtual environments. Furthermore, in contribution to practice, this article contributes knowledge to nudge design and provides hands on examples for designers or website operators on how to put nudge designs to practice in virtual choice environments. Additionally, this article contributes relevant considerations in a high-impact research field with growing importance given the global climate crisis.

This study aims to identify the origins, mechanisms and outcomes of applying behavioral insight in public policy research.

The authors conducted a systematic literature review to answer three research questions. The authors identified 387 primary studies, dated from January 2000 to April 2021 and coded them through a thematic analysis. Related studies were obtained through searching in Emerald, ScienceDirect, Sage, Springer, Wiley and Routledge.

The results identified eight themes for origins, 16 themes for mechanisms/techniques and 13 outcome-related themes. Through the thematic analysis, the major mechanisms of behavioral approach were found to be social marketing, information provision, social norms, incentives, affect, regulation design, framing, salience, defaults, simplification, networking, environment design, scheduled announcements, commitments, attitude-preference-behavior manifestation and combining behavioral and nonbehavioral mechanisms.

The findings of this review help policymakers to design or redesign policy elements.

This review provides the first systematic exploration of the existing literature on behavioral public policy.

The global food waste and food scarcity paradox is steadfastly increasing. This study aims to examine the effects of digital nudging as forms of positive and negative reinforcement to change food waste behavior and found that nudging positive reinforcement modifies this habit.

A field experiment was conducted on 628 diners randomly split into experiment (n = 412) and control group (n = 216) in two separate dining locations over four weeks. Out of these, 412 diners were randomly subjected to tent cards with positive (n = 228) and negative (n = 184) reinforcement nudging and completed a questionnaire to ascertain if nudging affects their consumption behavior. Consumption waste per unit revenue was calculated from all 628 diners individually to analyze the financial impact between control and experiment groups.

SEM analysis reveals that positive reinforcement mediates between external motivators (social media and restaurant service) and reduction of food waste behavior. Further analysis also reveals that nudging has a higher three times effect on reducing food waste as compared with no nudging (control).

Positive messaging encourages behavior change more effectively as compared to negative ones. Gentle reminders of how everyone can personally be a “warrior” or “hero” in the fight against global food waste increases the likelihood of altruistic motivation in tackling these issues.

This study demonstrates how positive reinforcement in the form of nudges acts as key mediator to support reduction of consumer food waste on site, ultimately helping to reduce financial costs compared to those without nudges.

A central question of public administration is how political principals secure the cooperation of administrators within organisational frames and contexts; increasingly, rational influences are being considered alongside bounded rationality and non-rational influences. This paper aims to explore the intent of New Zealand’s Public Service Act 2020 in managing administrative behaviour.

The methodology is primarily ethnographic, combining emic and etic perspectives. A mixed-methods approach comprises participant observer field notes and meeting documentation, substantiated by official documents; documents were analysed thematically and triangulated with other data sources.

The Public Service Act introduces new bounds on administrative behaviour. The stated rationale for these changes reveals an attempt to set limits on the principal–agent relationship between politicians and administrators and causes predictable deviations from rational behaviour by cultivating public service motivation and a unified public service identity.

As the legislation in question was only passed in 2020, it is too early to definitively assess the ultimate impact of legislation on administrative behaviour. This case study demonstrates that behavioural approaches to public administration are being applied intentionally by governments. The choice architecture created in the case study blends rational, bounded, and non-rational influences. Together, this produces a bricolage of semi-relevant theories from other disciplines, especially psychology, to explain administrative behaviour. Further refinement is needed to develop a cohesive and comprehensive theory of administrative behaviour that can account for contemporary practice.

Administrators act as agents of political principals, within ethical and rules-based limitations and influenced by public service motivation and social identity. Shifting from implicit to explicit choice architecture does not negate possible tensions between bounds and can signal them more explicitly. Shared symbols are sometimes intended to influence identity and therefore adherence to behavioural norms.

This paper explores the manipulation of choice architecture as a viable strategy for altering behaviour for the better and, to the best of the authors’ knowledge, is the first known instance of choice architecture being “legislated in” rather than merely “showing through”. This study illustrates the blending of rational, boundedly rational and non-rational factors into a choice architecture for public administrators that help mediate the biases and challenges of principal–agent relationships (which form a cascade in New Zealand’s public administration system).

Strategies to promote more sustainable consumer choices have been gaining interest among tourism and hospitality scholars. In particular, behavioral economic theories of decision-making have gained popularity in the past decade, led by behavioral interventions (BIs) such as the nudge movement. This paper aims to present a critical reflection on this recent trend, with a specific focus on whether these BI approaches are an adequate tool to contribute to long-term behavioral changes, one crucial aim of the promotion of sustainable consumption.

Based on a critical review of recent significant academic works in the field, this paper reflects on how nudge principles are applied in the hospitality and tourism sectors, as well as the usual justifications given for their use. This paper then discusses the potential limitations, both theoretical and practical, of using these short-term focused approaches to decisions that intend to have long-term outcomes and aims.

BIs in hospitality and tourism have the potential to create long-term sustainable changes through a more comprehensive view of behavioral factors influencing decisions; however, such approaches would need to be strongly embedded in theoretical arguments that question “how” and “why” behavior change could be sustainable in the long term. This paper proposes a conceptual framework to address these concerns for future research.

This critical reflection proposes a comprehensive framework that will help guide stronger theoretically motivated identification, design and empirical testing of BIs and nudges. Industry can eventually benefit from theoretically stronger interventions that provide a balance between the short-term and long-term influence of BIs to attain customer loyalty and eventually greater value for business stakeholders.

This reflection paper critically reviews the basis of BIs and recommends a framework to strengthen their theoretical arguments. This reflection focuses on the theoretical critique of BIs and nudges to ensure long-term behavior changes are sustainable. The paper also proposes a comprehensive framework that incorporates well-founded theoretical models to enhance BIs and nudge literature.

Machine learning (ML), and deep learning in particular, is gaining traction across a myriad of real-life applications. Portfolio management is no exception. This paper provides a systematic literature review of deep learning applications for portfolio management. The findings are likely to be valuable for industry practitioners and researchers alike, experimenting with novel portfolio management approaches and furthering investment management practice.

This review follows the guidance and methodology of Linnenluecke et al. (2020), Massaro et al. (2016) and Fisch and Block (2018) to first identify relevant literature based on an appropriately developed search phrase, filter the resultant set of publications and present descriptive and analytical findings of the research itself and its metadata.

The authors find a strong dominance of reinforcement learning algorithms applied to the field, given their through-time portfolio management capabilities. Other well-known deep learning models, such as convolutional neural network (CNN) and recurrent neural network (RNN) and its derivatives, have shown to be well-suited for time-series forecasting. Most recently, the number of papers published in the field has been increasing, potentially driven by computational advances, hardware accessibility and data availability. The review shows several promising applications and identifies future research opportunities, including better balance on the risk-reward spectrum, novel ways to reduce data dimensionality and pre-process the inputs, stronger focus on direct weights generation, novel deep learning architectures and consistent data choices.

Several systematic reviews have been conducted with a broader focus of ML applications in finance. However, to the best of the authors’ knowledge, this is the first review to focus on deep learning architectures and their applications in the investment portfolio management problem. The review also presents a novel universal taxonomy of models used.

This study investigated the impacts of the interaction experiential customization (IEC) mode on consumers' information processing fluency and green customization intention (GCI) as well as the moderating effect of consumers' self-construal.

This study conducted an online field experiment, questionnaire study and between-subjects laboratory experiment to test the hypotheses.

It was found that IEC had a significant positive effect on consumers' GCI. Moreover, consumer retrieval processing fluency played a partial mediating role in the relationship between IEC and GCI. In addition, consumers' self-construal moderated the “IEC? Three dimensions of processing fluency” relationships.

The results emphasized the importance of IEC in influencing consumers' consumption intention in a green customization setting and have some practical implications, that is, companies have the opportunity to use appropriate digital choice architecture designs, which can enhance consumer processing fluency when promoting eco-friendly products in the customized consumption process, especially for independent consumers.

This study focused on the customization design on consumers' GCI and explained the mechanism of impact of IEC on improving consumers' processing fluency and GCI in a product customization setting based on the fluency theory. In addition, this study investigated the moderating effect of consumers' self-construal (independent vs interdependent) on their significant different information processing modes for low-carbon choices.

Behavioral economics poses a challenge for the welfare evaluation of choices, particularly those that involve risk. It demands that we recognize that the descriptive account of behavior toward those choices might not be the ones we were all taught, and still teach, and that subjective risk perceptions might not accord with expert assessments of probabilities. In addition to these challenges, we are faced with the need to jettison naive notions of revealed preferences, according to which every choice by a subject expresses her objective function, as behavioral evidence forces us to confront pervasive inconsistencies and noise in a typical individual’s choice data. A principled account of errant choice must be built into models used for identification and estimation. These challenges demand close attention to the methodological claims often used to justify policy interventions. They also require, we argue, closer attention by economists to relevant contributions from cognitive science. We propose that a quantitative application of the “intentional stance” of Dennett provides a coherent, attractive and general approach to behavioral welfare economics.

The attempt to establish a common European framework for core platforms' duties and responsibilities toward other actors in the digital environment is at the core of the recent scholarly debate surrounding the Digital Markets Act (DMA) proposal. In particular, the everlasting juxtaposition between the “data power” – as emerging from recent cases (Section 2) – that dominant tech companies enjoy and the concept of consumer sovereignty (Section 3) lies at the core of the proposal's attempt to identify digital core platforms as market gatekeepers. Accordingly, this chapter critically investigates the divide between power imbalance and consumer sovereignty in light of the architecture designed by the DMA, with a specific focus on its effectiveness in identifying gatekeepers' power drivers (Section 4). After highlighting the main critical aspects of the pertinent rules, opportunities for fruitful developments are then identified through the reframing of some of the notions considered in the proposal, and namely the role of “lock-in” effects and “data accumulation” (Section 5). Lastly, this chapter suggests that the DMA advancements – while desirable – are bound to be fragmentary in the absence of a wider appraisal of the nature of data power imbalance dynamics in the modern digital markets (Section 6).