Conceptualisation of sustainable consumer behaviour: converging the theory of planned behaviour and consumption cycle

Sheoran, Monika; Kumar, Divesh

doi:10.1108/qrom-05-2020-1940

Cited by 22 publications

(18 citation statements)

References 129 publications

(127 reference statements)

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“…It is rather inefficient in terms of computing. Sheoran and Kumar [28] investigated how the theory of planned behavior (TPB) has been used to comprehend the multifaceted character of sustainability consumer behavior using descriptive and analytical methodologies and to perform consumption behavior prediction, information extraction, and user influence analysis. It takes a lot of time and effort.…”

Section: Literature Surveymentioning

confidence: 99%

Consumption Behavior Prediction Based on Multiobjective Evolutionary Algorithm

Jaharudin

Song

2022

Journal of Sensors

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Consumption behavior prediction reveals customer attributes, personal preferences, and intrinsic laws. Organizations would benefit from knowing further about customer needs and business desires by monitoring client behavior to provide more precise recommendations and boost acquisition rates. The economics of the customer, buyer groupings, and product quality are only a few of the numerous variables that influence customer behavior. The key issue that has to be resolved at this time is how to filter out useful information from these vast amounts of data to forecast customer behavior. For customer consumption behavior prediction and analysis with an advanced quantitative research process, we proposed the multiobjective evolutionary algorithm, which significantly boosts the accuracy of consumption behavior predictions. The dataset is initially gathered based on consumer preferences and behaviors as the essential information for the entire prediction model. Min-max normalization is used as a component of the preprocessing of the data to get the elimination of redundant and superfluous data. The Word2vec model is utilized for feature extraction, and boosted ant colony optimization (BACO) is employed to choose the best features. Utilizing the suggested multiobjective evolutionary algorithm (MOEA), the predictions are made. The suggested system’s performance is assessed, and the metrics are contrasted with more established methods. The findings demonstrate that the suggested MOEA technique performs well than the traditional ML, XGB, AI, and HNB algorithm methods in terms of accuracy (95 percent), quality of prediction (97 percent), precision (99 percent), recall (93 percent), F 1 -score (98 percent), and prediction time (50 seconds). Hence, the outcomes show that the regression model is sustainable. The suggested consumption behavior prediction system has demonstrated its efficiency in boosting profitability.

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Section: Literature Surveymentioning

confidence: 99%

Consumption Behavior Prediction Based on Multiobjective Evolutionary Algorithm

Jaharudin

Song

2022

Journal of Sensors

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“…In terms of theoretical implications, this study contributes to enhanced scholarly knowledge at the intersection between the consumer dynamics literature (Baumert et al, 2020;Forbes, 2017;Kirk & Rifkin, 2020;Sneath et al, 2009;Zwanka & Buff, 2021) and the green/sustainable consumer behavior literature (e.g., Alzubaidi et al, 2020;Dangelico et al, 2021;Diamantopoulos et al, 2003;Luchs & Mooradian, 2012;Sheoran & Kumar, 2021;Stagl & O'Hara, 2002), by assessing the influence of an unexpected and disruptive event -the Covid-19 pandemic -on sustainable consumer behavior, and comparing the behavior of different socio-demographic groups. Limited research has been conducted on this topic so far (e.g., Borsellino et al, 2020;Jian et al, 2020;Qi et al, 2020;Severo et al, 2020).…”

Section: Theoretical Implicationsmentioning

confidence: 99%

Is Covid‐19 changing sustainable consumer behavior? A survey of Italian consumers

Dangelico

Schiaroli

Fraccascia

2022

Sustainable Development

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Since the beginning of 2020, the world has been hit by the SARS‐CoV‐2 virus that causes Covid‐19. To hamper its spread, policymakers of many countries have put in place strong countermeasures, including lockdowns, that have led to significant changes in people's lifestyles and daily routines. This article aims at assessing the changes caused by Covid‐19 in sustainable consumer behavior under multiple perspectives, contributing to advance knowledge at the intersection between consumer dynamics and sustainable consumer behavior literature. A survey was conducted on 1.535 Italian consumers between December 2020 and February 2021. Respondents were asked to assess the extent to which their consumption behavior—purchase frequency, willingness to pay a premium price, sense of moral duty to purchase, social influence to purchase—related to several categories of sustainable products changed due to the pandemic, as well as the extent to which the pandemic impacted on many other aspects, including their environmental awareness, concern, and habits. Results show that Covid‐19 generated relevant changes. Consumers have increased their purchase frequency and willingness to pay for sustainable products, show growing attention to environmental issues, and behave more sustainably. Further, the extent of change is strongly affected by socio‐demographic variables, such as gender, age, income, and education. For instance, women reported a higher shift towards sustainable consumption and behavior than men. Understanding these changes is important to guide marketers and policymakers to respond promptly and effectively to them and to leverage on them to foster a transition towards a more sustainable society.

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“…A study by Vilkaite-Vaitone and Jeseviciute-Ufartiene (2021) investigated the predictors of textile recycling using the TPB; however, this study's focus was on Lithuanian households rather than fashion waste, more specifically. Within this study, the authors employ the TPB as it is one of the most robust theories in explaining human behaviour (Ogiemwonyi, 2022) and can be generalised to various behavioural contexts (Reysen et al , 2018), especially, in regards to sustainable and pro-environmental behaviours (Joshi et al , 2021; Ogiemwonyi, 2022; Sheoran and Kumar, 2022).…”

Section: Literature Review and Hypothesis Developmentmentioning

confidence: 99%

Predictors of consumers' behaviour to recycle end-of-life garments in Australia

Rotimi

Johnson²,

Daronkola³

et al. 2023

JFMM

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PurposeThe purpose of this study is to apply and extend the predictors within the theory of planned behaviour (TPB) to understand consumers' behaviour toward recycling end-of-life garments among Australian consumers. The predictors explored within this study include attitude, perceived behavioural control, subjective norms, self-identity, general recycling behaviour eco-literacy, self-efficacy, intentions to recycle and behaviour to recycle end-of-life garments.Design/methodology/approachData were collected from a sample of consumers across all eight recognised states/territories in Australia through survey questionnaires. A total of 481 usable responses were analysed using structural equation modelling.FindingsResults show positive relationships between the factors explored with all hypotheses supported. The findings of this study have theoretical and managerial implications. They (1) provide an insight into the significant factors that influence consumers' recycling behaviour amongst Australian fashion consumers; (2) bridge the gap in the explanatory nature of TPB by extending this theory; (3) call to develop marketing campaigns to educate consumers on the impact of fashion waste; (4) suggest the need for provision of household textile collection bins at a national level and (5) highlight the need for policy reform on garment recycling enabled by the Australian government.Originality/valueThis study is part of the limited studies that focus on the recycling of consumer fashion waste within the Australian context. Little research has also applied the TPB to end-of-life fashion products with a focus on recycling. In addition, no study to the authors' knowledge has, in combination, explored self-efficacy, self-identity, general recycling behaviour and eco-literacy as predictors of intentions to recycle end-of-life garments.

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Conceptualisation of sustainable consumer behaviour: converging the theory of planned behaviour and consumption cycle

Cited by 22 publications

References 129 publications

Consumption Behavior Prediction Based on Multiobjective Evolutionary Algorithm

Consumption Behavior Prediction Based on Multiobjective Evolutionary Algorithm

Is Covid‐19 changing sustainable consumer behavior? A survey of Italian consumers

Predictors of consumers' behaviour to recycle end-of-life garments in Australia

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