Vikas Tripathi

Impact of Brand Cues on Young Consumers’ Preference for Mobile Phones: A Conjoint Analysis and Simulation Modelling:

There are multiple attributes and product features which influence youth and impact their purchase decisions. The companies are assiduously trying to tap young consumers but are unable to sustain their high growth and market share. The attributes or brand cues influencing youth can be broadly classified as extrinsic cues and intrinsic cues. Extrinsic cues are peripheral or external to the product such as price, brand image, store image, whereas intrinsic cues are independent, inherent and constitute the product’s physical characteristics such as mobile camera, size, colour etc. In the present study, extrinsic cues are brand name and price while camera, RAM, Android type and battery power are intrinsic cues. To recognize the role of brand cues, a sample of 417 respondents through judgement sampling is drawn. The impact of brand name, price and technology on brand equity is empirically examined by conjoint and simulation analysis to generate information regarding consumers’ preferences towards mobile phone. The salience of study put forth the measures of enhancing mobile brand equity among young consumers. The originality of present study articulates brand equity diverge across different age groups and the young consumers obsession to spend more on consumer durable products like mobile with their desirable intrinsic and extrinsic cues.

Discriminating market segments using preferential green shift: a conjoint approach

Purpose This paper aims to explore surprising facets of consumer delight behavior. The study is the empirical juncture of three studies based on consumer survey on the Indian television market. Study 1 traces the existence of greenies in India among brownies prevailing around the globe by using the surprise-delight model. Study 2 is a pre-intervention research design confirming greenies preferences to television attributes such as screen technology, annual energy cost saving, screen resolution, screen size and free gifts. Study 3 signifies a price intervention design by allowing customers to include their preference by replacing the annual energy cost saving with price. Design/methodology/approach This paper is a harvest of studies based on discriminant analysis for identifying green and brown customers and a two-level conjoint analysis for identifying attributes contributing to green behavior. Findings The empirical generalization of a study comes out with unique findings of the greenies and brownies and their preference and attitude toward green attribution and substitution. A “preferential green shift” appeared as a vital output owing to knowledge–attitude–practice from these consecutive studies. This gap exists because of the price factor. The authors suggest the measures for improvement in product offering by targeting and positioning green products from the findings and the preferential green shift. Research limitations/implications Future research may focus on other segments of products such as automobiles, i.e. cars. Despite the availability of the non-probabilistic sampling technique, the probabilistic sampling technique can be used. Finally, a larger sample size could have given a better generalization of results. Originality/value The gap in knowledge–attitude–practice was evident. This gap was caused by the presence of “price” concern. The study revealed that heavy consumer durable buyers are aware of the benefit of green, but the reality of price cannot be ignored and finally make a purchasing decision on the basis of price criteria. Hence price is recommended as another criterion to be considered in the technology acceptance models.

Exploring key dimensions of e-service quality: a case of Indian banking industry

Customers become more aware of a companys performance when the service provider adopts technology. In such situations, customers demand more reliable services and greater security in financial transactions. Thus, banks need to improve the quality of e-services provided by them. The present paper seeks to identify e-service quality dimensions relevant to the banking industry. It attempts to critically analyse the relationship amongst them so that policy makers can focus on relevant parameters to improve the e-service quality in banking. Interpretive structural modelling (ISM) approach has been applied in this study for modelling the e-service quality dimension. The major findings of this study are to prioritise the strategic dimension in reducing the risks associated with e-service quality. The hierarchical presentation of dimensions and their classification into driver and dependent categories is a unique attempt that has been made in context of e-service quality in the Indian banking industry.