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.
PurposeThe 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/approachThe 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.FindingsThe 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 implicationsThe 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/valueThe TSCC model is beneficial not only for organizations entering into the food business, but also for economic policy makers.
The authors develop a scale to measure individual perspectives on Corporate Social Responsibility (CSR) constructs based on microfoundation theory. To develop the microfoundation based CSR scale, the research methodology involved two stages (qualitative research followed by quantitative research). In qualitative research, Focused Group Discussion (FGD) was conducted to extract items for survey questionnaire development. Subsequently, quantitative analysis was carried out. The data were subjected to exploratory and confirmatory factor analysis (CFA). The study sample comprised of 407 management students of Indian business schools who enrolled in CSR and sustainability courses. The developed scale comprised of four variables namely Customer Product Preference (CPP), Customer Firm Preference (CFP), Investor Preference (IP) and Employability Preference (EP). The results were arrived at by undertaking Exploratory Factor Analysis (EFA) and CFA. The scale developed and extended the theoretic conversation on CSR from the organizational level discussion to an individual level discussion based on microfoundation theory. This is one of the first studies to develop a scale on individual perspectives on CSR constructs based on micro-foundation theory.
Research on brand naming has recently taken center stage in marketing literature. This study formulates a comprehensive classification of brand names that incorporates frameworks from existing literature and current naming methods used by practitioners. A content analysis of the top 500 global brand names based on manifest content, across 11 product categories, was conducted to understand the current brandnaming trends. The results confirm extensive use of the promoter's name and place of origin (39.7 per cent of all brand names coded), compounding (34.1 per cent), abbreviations (18.2 per cent) and blending (7.9 per cent). Category-wise analysis indicates that certain categories, such as durables, follow the aggregate pattern of 61.5 per cent semantic word names, 53.0 per cent invented word names and 23.6 per cent non-word names. FMCG brands, on the other hand, show differing patterns because of disproportionately low abbreviations in the distribution. Further, χ 2 tests using equal expected frequencies of the three dimensions; semantic, invented and non-word names, showed that there appears to be significant differences in frequency between these dimensions. Practitioners may consider using these newly defined categories, such as semantically related acronyms, in creating distinctive brand names. This study also analyzes the use of sound symbolic names for brands.
PurposeCollaborative 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/approachThis 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.FindingsThree 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/valueThis 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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.