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Consumers’ awareness of green products has increased in the last few years, but studies show that the demand for green products has been stagnant. The purpose of this study is to explore the roles of consumers’ perceived readiness to be green and subsequently, how readiness to be green affects consumers’ purchase intention towards green products in an emerging market, Indonesia. A total of 916 survey responses were collected in three universities, two major shopping malls and several housing areas in Yogyakarta, Indonesia. The findings reveal that consumers’ attitude (ATT), subjective norm, perceived behavioural control (PBC), pro‐environmental self‐identity (PEI), ethical obligation and consumers’ readiness to be green are the determinants of intention to purchase green products. Consumers’ readiness to be green mediates the effects of ATT, PBC, PEI and perceived sense of responsibility on purchase intention. The study provides further insights into the discrepancy between professed positive attitudes towards the environment and the slow uptake of green behaviour in an emerging market.

The COVID-19 pandemic has caused one of the most severe disruptions in the global economy in modern history (Gössling et al., 2020). When challenged by this dramatic disruption and instability in our lives, an understanding of consumer vulnerability and the consumption-related repercussions of this pandemic merits further exploration (Kirk & Rifkin, 2020). Overall, past research has not sufficiently addressed vulnerability issues relating to technology consumption in the wake of a disaster. The discourse of technology consumption has often been framed from either utopian (focusing on the opportunities that technology presents) or dystopian perspectives (focusing on the negative consequences of technology consumption) (Zolfagharian & Yazdanparast, 2017). However, in reality, technology consumption may not always be represented by this binary opposition; that is, human-technology relations are more complex than this deterministic view (Katz & Rice, 2002). Prior research points to a paradoxical fascination and anxiety about technologies (Foehr & Germelmann, 2020). The term 'paradox' is defined as 'a situation, act, or behavior that seems to have contradictory or inconsistent qualities' (Jarvenpaa & Lang, 2005, p. 7), which suggests that 'polar opposite conditions can simultaneously exist' (Mick & Fournier, 1998, p. 124). We adopt the lens of paradox in our theoretical investigation following Mick and Fournier's (1998, p. 124) argument that paradox is 'a highly relevant and resonant concept for advancing knowledge of contemporary consumer behaviour'.We found three conceptual articles relevant to the central premise of our work. The first article by Sheth (2020) discusses how the pandemic has disrupted consumers' lives and how they have learned to cope and improvise new habits in the contexts of social spaces, co-working spaces, technology and natural disasters. While Kirk and

Purpose With the soaring volumes of brand-related social media conversations, digital marketers have extensive opportunities to track and analyse consumers’ feelings and opinions about brands, products or services embedded within consumer-generated content (CGC). These “Big Data” opportunities render manual approaches to sentiment analysis impractical and raise the need to develop automated tools to analyse consumer sentiment expressed in text format. This paper aims to evaluate and compare the performance of two prominent approaches to automated sentiment analysis applied to CGC on social media and explores the benefits of combining them. Design/methodology/approach A sample of 850 consumer comments from 83 Facebook brand pages are used to test and compare lexicon-based and machine learning approaches to sentiment analysis, as well as their combination, using the LIWC2015 lexicon and RTextTools machine learning package. Findings Results show the two approaches are similar in accuracy, both achieving higher accuracy when classifying positive sentiment than negative sentiment. However, they differ substantially in their classification ensembles. The combined approach demonstrates significantly improved performance in classifying positive sentiment. Research limitations/implications Further research is required to improve the accuracy of negative sentiment classification. The combined approach needs to be applied to other kinds of CGCs on social media such as tweets. Practical implications The findings inform decision-making around which sentiment analysis approaches (or a combination thereof) is best to analyse CGC on social media. Originality/value This study combines two sentiment analysis approaches and demonstrates significantly improved performance.

The purpose of this study is to explore the concept of consumers’ green perceptions (CGPs) which encompasses consumers’ current perceptions of green products, green consumers, green consumption practices, and green marketing communications. We hypothesise that CGPs may influence their consumption behaviour and how ready they are to be green. Focus groups were used to explore the concept of CGPs. Stage Two involved two surveys in Australia and New Zealand to test and corroborate the themes that were identified in the exploratory study. We identified five dimensions underpinning CGPs. These include “product perception”, “hard to be green”, “green stigma”, “perceived sense of responsibility” and “readiness to be green”. This paper presents the findings from both studies, provides empirical insights into Australian and New Zealand consumers’ green perceptions and demonstrates the explanatory power of CGPs in predicting green consumption behaviour, in particular their likelihood to purchase green household products.