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Increasingly, retailers are adopting technologies such as augmented reality (AR) as tools to enhance the customer experience. However, little is known about consumers' differing attitudes towards AR. The aim of this study is to explore how consumers differ in terms of the value they receive from using AR, as well as the trade-offs they experience when using the technology for shopping. Moreover, the study explores the individual characteristics that lead to these differences by segmenting consumers according to their perceptions of and attitudes towards AR as a shopping tool.

To identify the segments, latent class analysis was conducted on the data collected from an online survey of 503 US consumers.

The analysis yielded four distinct segments of consumers who vary in their attitude towards AR as a shopping tool – AR Averse, AR Hesitant, AR Open and AR Enthusiastic. Covariate analysis indicated that the factors which drive membership of these segments include perceived ease of use, perceived usefulness and psychographic characteristics such as innovativeness, time pressure and shopping enjoyment.

The heterogeneity of consumer attitudes towards AR is driven by consumers' perceptions of decision confidence (how they see AR enhancing their ability to make choices), information overload (the potential for AR to over-stimulate shoppers) and experiential value (the derived value from engaging with AR). Hence, retailers should leverage these dimensions when communicating the value of AR in assisting consumers when shopping.

This study highlights that heterogeneity exists in consumer attitudes towards AR, and suggests that the attitude towards AR is not a fixed value, but can change through education.

For consumers, cross-channel behaviour is increasingly prevalent. Such behaviour involves consumers actively engaging in (and deriving benefit) from one channel during a product search but switching to another channel when making a purchase. Drawing on multi-attribute utility theory, this study proposes a cross-channel behaviour typology consisting of three key aspects: channel choice behaviour, functional and economic outcomes and consumer-specific psychographic and demographic variables.

Segmentation analysis conducted via latent class analysis (LCA) was performed on a sample of 400 US consumers collected via an online survey.

Cross-channel behaviour is not always intentional. We identify a specific segment of consumers that most often engage in unplanned, rather than intentional, cross-channel switching. We find that of all shoppers that engage in cross-channel behaviour, a fifth (20%) are forced to switch channels at the point of purchase.

Cross-channel behaviour can be mitigated by retailers via a deep understanding of the driving factors of different configurations of showrooming and webrooming.

In contrast with existing conceptualisations, this study suggests that cross-channel behaviour often stems from consumers being “forced” by factors outside of their control, but within the retailers' control. This research presents a nuanced approach to decompose consumer cross-channel behaviour from the consumer perspective as planned, forced or opportunistic.

This paper investigates the degree to which self-selection explains the apparent higher purchase value of research shoppers.

An online survey was administered to 594 retail shoppers. The purchase value of research shoppers and single-channel shoppers was compared before and after propensity score matching to account for self-selection effects.

Prior to matching, research shoppers spend significantly more than single-channel shoppers. This difference persists after accounting for self-selection but is reduced by 25%. The impact of self-selection differs across product categories and channels, with the online channel most likely to lead to higher purchase value.

The findings build on existing literature on the value of omni-channel retail strategies and provide insights for retailers to determine the likely impact of encouraging research shopping among their customers.

The research provides important insights into the role that self-selection plays in the value of multi-channel shoppers, and the likely value to retailers of omni-channel strategies.

Although saving for retirement is critical, many people are reluctant to contribute money now in anticipation of a future event, namely their retirement. This study aims to investigate the interaction effect between message frame and message appeal on individual preparedness for retirement, specifically in terms of an individual’s willingness to contribute to retirement savings.

Across three studies, the authors show that message frames with a gain-orientation are more persuasive when self-oriented rather than oriented towards socially distant others. In Study 1, the authors use a 2 (gain-loss message frame) × 3 (self, close-other, distant-other message appeal) experimental design with ad copy manipulating the scenarios. In Study 2, the authors replicate and extend Study 1 to validate the findings. In Study 3, the authors overlay life-stage to determine how consumers differ in terms of their willingness to contribute to retirement.

Across the studies the authors find that message frame and message appeal influence consumer preparedness for retirement. The authors investigate these effects in terms of willingness to contribute to retirement savings (Studies 1–3) as well as satisfaction with retirement savings, anticipated retirement enjoyment, positive emotions and negative emotions (Studies 1 and 2).

While a substantive amount of research has been devoted to retirement planning, gaps remain as to the efficacy of communication message strategies on influencing retirement preparedness. This research seeks to contribute towards this literature stream by uncovering the ways in which individuals can be encouraged to contribute towards retirement planning.

Behavioural change practice has focussed attention on understanding behaviour; failing to apply dynamic approaches that capture the underlying determinants of behavioural change. Following recommendations to direct analytical focus towards understanding both the causal factors of behaviour and behavioural change to enhance intervention practice, this paper aims to apply a hidden Markov model (HMM) approach to understand why people transition from one state to another (e.g. reporting changes from wasting food to not wasting food or vice versa).

Data were drawn from a 2017 food waste programme that aimed to reduce waste of fruit and vegetables by increasing self-efficacy through a two-week pilot, featuring recipes and in-store cooking demonstrations. A repeated measure longitudinal research design was used. In total, 314 households completed a phone survey prior to the two-week pilot and 244 completed the survey in the weeks following the intervention (77% retention in the evaluation study).

Two behavioural states were identified, namely, fruit and vegetable (FV) wasters and non-FV wasters. Age was identified as a causal factor for FV food wasting prior to the campaign (45-54 years were most likely to waste FV). Following the intervention, a total of 43.8% transitioned away from FV wasters to non-wasters, and attitudes and self-efficacy were indicated as potential causal factors of this change in FV waste behaviour.

Through this application, it is demonstrated how HMM can identify behavioural states, rates of behaviour change and importantly how HMM can identify both causal determinants of behaviour and behavioural change. Implications, limitations and future research directions are outlined.