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Article

Kalpak K. Kulkarni, Arti D. Kalro and Dinesh Sharma

This study aims to investigate the influence of Big Five Personality traits (i.e. openness to experience, conscientiousness, extraversion, agreeableness and neuroticism…

Abstract

Purpose

This study aims to investigate the influence of Big Five Personality traits (i.e. openness to experience, conscientiousness, extraversion, agreeableness and neuroticism) on young consumers’ intentions to share branded viral video advertisements. Further, this study also demonstrates that the advertising appeal (informational versus emotional) used in the viral advertisement moderates the effects of specific personality traits on the sharing of viral ads.

Design/methodology/approach

A conceptual framework is proposed based on the Five-Factor Model of Personality (McCrae and John, 1992) and advertising effectiveness literature. Using experiments, responses from young consumers were collected and hypotheses were tested using hierarchical regression and ANOVA.

Findings

Results reveal that the two personality traits, extraversion and openness to experiences, are positively associated with consumers’ viral ad sharing intentions, whereas conscientiousness, agreeableness and neuroticism are not. Moreover, individuals scoring high on openness and extraversion prefer sharing branded viral ads containing informational appeal vis-ã-vis those containing emotional appeals.

Originality/value

Studies decoding the factors behind the success of viral advertisements have more often focussed on the ad content rather than on personality dimensions of the ad sharers. This study bridges this gap by investigating the influence of Big Five Personality traits on young consumers’ intention to forward viral ads, in interaction with ad appeal. Young consumers represent key audience segments consuming and sharing viral content online, and hence, it is important to have a deeper understanding of this market segment.

Details

Journal of Consumer Marketing, vol. 36 no. 6
Type: Research Article
ISSN: 0736-3761

Keywords

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Article

Preeti Virdi, Arti D. Kalro and Dinesh Sharma

Decision aids (DAs) in online retail stores ease consumers' information processing. However, online consumers do not use all decision aids in purchase decision-making…

Abstract

Purpose

Decision aids (DAs) in online retail stores ease consumers' information processing. However, online consumers do not use all decision aids in purchase decision-making. While the literature has documented the effects of individual decision aids or two decision aids at a time, no study has compared the efficacy of multiple decision aids simultaneously. Also, very few studies have looked at the use of decision aids for consumers with maximizing and satisficing tendencies. Hence, this study aims to understand the preferences of maximizers and satisficers towards online decision aids during the choice-making process.

Design/methodology/approach

This is an observational study with 60 individuals who were asked to purchase either a search-based or an experience-based product online. Participants' browsing actions and verbalizations during online shopping, were recorded and analysed using NVivo, and later the use of decision aids was mapped along their choice process.

Findings

Consumer's preference of decision aids varies across the two stages of the choice process (that is, consideration set formation and evaluation & choice). In their choice formation, maximizers use different decision aids in both stages, that is, filter tool and in-website search tool for search products, and collaborative filtering-based recommender systems and eWOM for experience products. Satisficers used more decision aids as compared to maximizers across the two stages for both product types.

Originality/value

This study is an exploratory attempt to understand how consumers use multiple decision aids present on e-commerce websites.

Details

International Journal of Retail & Distribution Management, vol. 48 no. 6
Type: Research Article
ISSN: 0959-0552

Keywords

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Article

Preeti Virdi, Arti D. Kalro and Dinesh Sharma

Collaborative filtering based recommender systems (CF–RS) are widely used to recommend products based on consumers' preference similarity. Recommendations by CF–RS merely…

Abstract

Purpose

Collaborative filtering based recommender systems (CF–RS) are widely used to recommend products based on consumers' preference similarity. Recommendations by CF–RS merely provide suggestions as “people who bought this also bought this” while, consumers are unaware about the source of these recommendations. By amalgamating CF–RS with consumers' social network information, e-commerce sites can offer recommendation from social networks of consumers. These social network embedded systems are known as social recommender systems (SRS). The extant literature has researched on the algorithms and implementation of these systems; however, SRS have not been understood from consumers' psychological perspective. This study aims to qualitatively explore consumers' motives to accept SRS in e-commerce websites.

Design/methodology/approach

This qualitative study is based on in-depth interviews of frequent online shoppers. SRS are currently not very widespread in the Indian e-commerce space; hence, a vignette was shown to respondents before they responded to the questions. Inductive qualitative content analysis method was used to analyse these interviews.

Findings

Three main themes (social-gratification, self-gratification and information-gratification) emerged from the analysis. Out of these, social-gratification acts as an enabler, while self-gratification along with some elements of information-gratification act as inhibitors towards acceptance of social recommendations. Based on these gratifications, we present a conceptual model on consumer's acceptance of social recommendations.

Originality/value

This study is an initial attempt to qualitatively understand consumers' attitudes and acceptance of social recommendations on e-commerce websites, which in itself is a fairly new phenomenon.

Details

Online Information Review, vol. 44 no. 3
Type: Research Article
ISSN: 1468-4527

Keywords

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Article

S.P. Sharma, Dinesh Kumar and Komal

The purpose of this paper is to present a hybridized technique for analyzing the stochastic behavior of an industrial system. The feeding system of a paper mill situated…

Abstract

Purpose

The purpose of this paper is to present a hybridized technique for analyzing the stochastic behavior of an industrial system. The feeding system of a paper mill situated in North India producing 200 tons of paper per day has been considered for analysis and efforts have been made to incorporate vague, ambiguous, imprecise and conflicting information quantified by fuzzy numbers.

Design/methodology/approach

In this paper, three important tools namely, fuzzy analysis, neural network and genetic algorithms (GAs), are used to built a hybridized and more realistic technique herein named as, neural network and GAs‐based Lambda‐Tau (NGABLT). The technique will facilitate the maintenance personnel in making a better decision. This technique has been demonstrated by computing some of the reliability indices of the considered system.

Findings

The results indicate that NGABLT technique reduces the gap between crisp and existing Lambda‐Tau results, i.e. it may be a more useful tool to assess the current system condition and suggests to improve the system reliability and availability.

Originality/value

The authors have suggested a hybridized technique for analyzing the stochastic behavior of the feeding system in a paper mill by computing fuzzy reliability indices.

Details

International Journal of Quality & Reliability Management, vol. 27 no. 8
Type: Research Article
ISSN: 0265-671X

Keywords

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Article

Dinesh Sharma, B.S. Sahay and Amit Sachan

Previous research in the area of distributor performance proposed different scales, mostly in western, developed country context. These studies also lacked the…

Abstract

Previous research in the area of distributor performance proposed different scales, mostly in western, developed country context. These studies also lacked the consideration of dynamic interaction between variables, which determine the distributor’s performance. This paper proposes a composite Distributor Performance Index (DPI) to evaluate distributors’ performance based on at the “Enables” and “Results”, taking a system dynamics approach. The model results have been discussed and validated, in business marketing channel. The context of this study is India, an emerging market.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 16 no. 3
Type: Research Article
ISSN: 1355-5855

Keywords

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Article

Amit Sachan, B.S. Sahay and Dinesh Sharma

The objective of the present study is to model the total supply chain cost (TSCC) of an Indian grain chain in order to understand and predict the future outcome of each…

Abstract

Purpose

The objective of the present study is to model the total supply chain cost (TSCC) of an Indian grain chain in order to understand and predict the future outcome of each supply chain model in different situations and to devise policies accordingly to reduce TSCC.

Design/methodology/approach

The system dynamics (SD) approach is used to model the TSCC model of an Indian grain chain, which takes care of the dynamic interaction of the cost variables.

Findings

The major findings of the paper are the reduced cost ratios in the different scenarios. A total of nine scenarios are evaluated, which are the cooperative model, contract farming and a collaborative supply chain based on optimistic, pessimistic and most likely views.

Practical implications

The practical implications are the action plans suggested to reduce TSCC in each of the future scenarios of the supply chain model that are developed in the paper.

Originality/value

The TSCC model is beneficial not only for organizations entering into the food business, but also for economic policy makers.

Details

International Journal of Productivity and Performance Management, vol. 54 no. 3
Type: Research Article
ISSN: 1741-0401

Keywords

Content available

Abstract

Details

Multidiscipline Modeling in Materials and Structures, vol. 14 no. 1
Type: Research Article
ISSN: 1573-6105

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Book part

Dinesh Sharma and Sumanjit Dass

Customer experience (CE) has been of research interest especially with researchers in a Business-to-Consumer (B2C) context. Extensive research has identified the potential…

Abstract

Customer experience (CE) has been of research interest especially with researchers in a Business-to-Consumer (B2C) context. Extensive research has identified the potential of similar studies in Business-to Business (B2B) contexts, yet we have little understanding of what influences a customer's experience in a B2B environment.

This chapter aims to capture the adequacy of efforts to capture the intricacies of CE in a B2B context using input–output measures both in the traditional and modern-day environment. The chapter would provide marketing managers with a clear understanding of how CE is affected in the B2B context. Essentially, it describes the importance of creating a positive CE through the direct interaction of various stakeholders with the company and its brand. This chapter advances the current state of knowledge by analysing the impact of CE on all dimensions of customer journey, creating a differential advantage over time.

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Article

Siddhartha Sarkar, Dinesh Sharma and Arti D. Kalro

The purpose of this paper is to present different naming, packaging, and pricing strategies adopted by private label (PL) retailers in India. This study also aims to…

Abstract

Purpose

The purpose of this paper is to present different naming, packaging, and pricing strategies adopted by private label (PL) retailers in India. This study also aims to identify preferred private label brand (PLB) categories, factors influencing their selection, and the importance of cues in evaluation of PLBs. The overall purpose is to identify important areas for future research of PLBs in the wake of organized retail growth in an emerging economy (India is the context here).

Design/methodology/approach

This study is based on in-store observations of major Indian retail chains, longitudinal analyses of customers’ shopping bills, qualitative analyses of consumer interviews, and focus group discussions.

Findings

The results indicate that retailers primarily adopt “Sub-branding” (using the store name along with a separate brand name) and “House of Brands” (using a separate brand name only) strategies to sell PLBs in the Indian market. Groceries, food and beverages, and apparel are the preferred categories in PLB. Price, quality, and convenience are the major factors influencing PLB. Taste, ingredients, packaging, price, brand name, and store name are the main factors that are used to evaluate PLBs.

Research limitations/implications

Due to the qualitative analyses and interpretation, there are limitations to this study which need to be empirically validated.

Practical implications

This research has implications for organized retailers in understanding the various strategies used for PLBs in India.

Originality/value

This study is a novel study for documenting the PLB strategies adopted by organized retailers in India. It also uses a longitudinal exploratory approach to further understanding the consumption of PLBs in India.

Details

International Journal of Retail & Distribution Management, vol. 44 no. 2
Type: Research Article
ISSN: 0959-0552

Keywords

Content available
Book part

Abstract

Details

Crafting Customer Experience Strategy
Type: Book
ISBN: 978-1-83909-711-9

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