Attitude segmentation of Indian online buyers

Mathew, Priya Mary

doi:10.1108/jeim-08-2014-0078

Cited by 19 publications

(11 citation statements)

References 13 publications

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“…Customer segmentation is often based on demographics and reported usage activities. Digital consumer segmentation has been based on Internet usage, perceived risks, website attributes, intent to do online purchase in future, preference for website attributes (Mathew, 2016), recalled reach and frequency of exposure to the touch points (Ieva and Ziliani, 2018) and patterns of medium preference for loyalty programmes accompanied by socio-demographics (Ieva and Ziliani, 2017). Within the mobile consumer group, researchers are looking for new segmentation approaches which would more directly reflect actual customer activities on smartphones.…”

Section: Discussionmentioning

confidence: 99%

Clustering consumers' shopping journeys: eye tracking fashion m-retail

Tupikovskaja-Omovie

Tyler

2020

JFMM

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PurposeDespite the rapid adoption of smartphones among digital fashion consumers, their attitude to retailers' mobile apps and websites is one of increasing dissatisfaction. This suggests that understanding how mobile consumers use smartphones for fashion shopping is important in developing digital shopping platforms that fulfil consumer' expectations.Design/methodology/approachFor this research, mobile eye-tracking technology was employed in order to develop unique shopping journeys for 30 consumers, using fashion retailers' websites on smartphones, documenting their differences and similarities in browsing and purchasing behaviour.FindingsBased on scan path visualisations and observed shopping experiences, three prominent mobile shopping journeys and shopper types were identified: “directed by retailer's website”, “efficient self-selected journey” and “challenging shopper”. These prominent behaviour patterns were used to characterise mixed cluster behaviours; three distinct mixed clusters were identified, namely, “extended self-selected journey”, “challenging shoppers directed by retailer's website” and “focused challenging shopper”.Research limitations/implicationsThis research argues that mobile consumers can be segmented based on their activities and behaviours on the mobile website. Knowing the prominent shopping behaviour types any other complex behaviour patterns can be identified, analysed and described.Practical implicationsThe findings of this research can be used in developing personalised shopping experiences on smartphones by feeding these shopper types into retailers' digital marketing strategy and artificial intelligence (AI) systems.Originality/valueThis paper contributes to consumer behaviour literature by proposing a novel mobile consumer segmentation approach based on detailed shopping journey analysis using mobile eye-tracking technology.

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Section: Discussionmentioning

confidence: 99%

Clustering consumers' shopping journeys: eye tracking fashion m-retail

Tupikovskaja-Omovie

Tyler

2020

JFMM

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“…It would be a mistake to approach consumers in these cities as a homogeneous group. In addition, as the cities grow larger, companies will need to segment further within each one, to identify small areas of opportunity (Izogo and Jayawardhena, 2018;Mathew, 2016). In a report by BCG (Singhi et al, 2015), it is stated that in terms of consumption expenditures, emerging cities (those with populations of less than 1m) will be the fastest growing.…”

Section: Backdrop Of the Study And Conceptual Frameworkmentioning

confidence: 99%

Determinants of Tier 2 Indian consumer’s online shopping attitude: a SEM approach

Kaur

Thakur

2019

APJML

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Purpose The purpose of this paper is to validate the conceptual model that presents the determinants of Tier 2 consumer’s online shopping attitude and the interrelationships among the constructs across the three Tier 2 cities in India. Design/methodology/approach The paper uses survey-based data from three Tier 2 cities of North India – Kota, Agra and Jalandhar and uses a combination of statistical techniques to assess psychometric properties of the scales and conduct the measurement and structural invariance. Findings The findings of the paper reveals that technology readiness, consumer innovativeness, fondness for branded products and perceived brand unavailability act as determinants of online shopping attitude and there is a positive relationship between online shopping attitude and online purchase intention among Tier 2 consumers in India while perceived offline hedonic value do not have any significant impact. Research limitations/implications Future researchers can use this model with additional confidence given its cross-segment robustness. Practical implications Online marketers can use the antecedents identified in this study to develop and encourage positive online shopping attitude in small town India. Originality/value This research paper is the first one that investigated online shopping attitudes of Indian Tier 2 consumers. Importantly, it validated the determinants of online shopping attitude among Tier 2 consumers. National and international e-tailers aiming to develop and expand their operations to India now have the critical empirical verification concerned with the determinants of online shopping attitude and behaviour in India which would be meaningful to develop a sound marketing strategy.

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“…Hence, the need arises for SCRM activities (Sigala, 2018;Zerbino et al, 2018). Whenever an organization adopts a new system or technology, the attitudes of the organization's top officials play vital roles (Askool and Nakata, 2011;Mathew, 2016). When the question of adopting SCRM in an organization is raised, top managers should consider if this system is trustworthy, how it can easily share information between the organization and the customers and how the employees would react to and be made familiar with the new system (SCRM) (Elena, 2016;Xu, 2017;Kantorová and Bachmann, 2018;Singh et al, 2019a).…”

Section: Factors Affecting Social Customer Relationship Managementthe Theoretical Foundationmentioning

confidence: 99%

Social customer relationship management factors and business benefits

Chatterjee

Chaudhuri

Vrontis

et al. 2020

IJOA

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Purpose This study aims to identify the business benefit of and factors affecting the use of social customer relationship management (SCRM) in Indian organizations. Design/methodology/approach Building on theoretical foundations, a conceptual model of factors affecting SCRM in Indian organizations is developed and empirically tested through a survey and corresponding analysis using SPSS and AMOS software. Findings The study presents empirical evidence that technological competence, environmental characteristics and organizational environment positively impact the actual use of SCRM on Indian organizations. Additionally, leadership support of organizations impacts positively the actual use of SCRM in organizations, while the trust factor insignificantly impacts the latter. The actual use of SCRM in organizations was found to have a positive impact on their business benefits. Research limitations/implications The theoretical model is built on the constructs of the technology, environment and organizational framework. It has added new factors, such as leadership support and trust, and thereby identified the business benefits of organizations using SCRM mediating through the organizations’ actual use of SCRM. The proposed model is simple, implementable and has a high explanative power of 81 per cent. Practical implications The study provides practitioners with evidence and practicable knowledge regarding the means and impact/benefits of SCRM use in Indian organizations. Originality/value The study is one of few empirical studies on the topic and contributes valuable knowledge to extant works through additional factors, theoretical conceptualization and empirical scientific findings of both scholarly and executive worth.

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Attitude segmentation of Indian online buyers

Cited by 19 publications

References 13 publications

Clustering consumers' shopping journeys: eye tracking fashion m-retail

Clustering consumers' shopping journeys: eye tracking fashion m-retail

Determinants of Tier 2 Indian consumer’s online shopping attitude: a SEM approach

Social customer relationship management factors and business benefits

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