Hari Govind Mishra, Piyush Kumar Sinha and Surabhi Koul
The purpose of this paper is to examine the relationship between customer loyalty and customer dependence in the context of modern format and traditional format stores. In the…
Abstract
Purpose
The purpose of this paper is to examine the relationship between customer loyalty and customer dependence in the context of modern format and traditional format stores. In the process, the role of switching cost and trust in this relationship has been explored.
Design/methodology/approach
Building on the literature, the authors have postulated a conceptual model and formulated relevant hypotheses. Quantitative methodology is applied with previously established. The data were collected through convenient sampling. Methods like Factor analysis, cross-tab and regression analysis have been used.
Findings
The findings indicate a significant relationship between customer loyalty and customer dependence. Switching cost and trust have been found to have a moderating effect over the relationship in both modern and traditional environments.
Research limitations/implications
The limitation is the restriction to the Jammu context. The studies have brought about the difference in attitudinal and behavioural loyalty. Future research can be carried out on the role of dependence in explaining and strengthening this relationship.
Originality/value
The present study provides an insight into for the customer loyalty and customer dependence in the context of modern and traditional retail formats.
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Piyush Kumar Sinha, Suraksha Gupta and Saurabh Rawal
The purpose of this paper is to develop a framework to understand how bottom of the pyramid (BoP) retailers adopt brands who sell to a very different set of customers and are…
Abstract
Purpose
The purpose of this paper is to develop a framework to understand how bottom of the pyramid (BoP) retailers adopt brands who sell to a very different set of customers and are served through long indirect channels.
Design/methodology/approach
In this study, 60 retailers belonging to different villages of Central and North Gujarat were interviewed. The interviews were audio recorded, transcribed and analyzed. A grounded theory-based analysis was carried out.
Findings
The analysis brought out six criteria used by the retailers in selecting brands with demand for the brand as the most dominant factor. Other criteria included brand adoption by other retailers, profitability, influence of wholesaler/distributor and packaging.
Originality/value
Previous studies with regard to brand adoption by retailers have focused on large retailers who are approached directly by the brands. There is a lack of studies on how BoP retailers adopt brands. Most studies have approached the subject from a distribution perspective of reaching these markets.
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Sujo Thomas, Abhishek, Sanket Vatavwala and Piyush Kumar Sinha
BigBasket.com, an online supermarket established in December 2011 in Bangalore, India, had become one of the major players in the Indian online grocery market by the end of March…
Abstract
BigBasket.com, an online supermarket established in December 2011 in Bangalore, India, had become one of the major players in the Indian online grocery market by the end of March 2016.1 Run by Innovative Retail Concepts Private Limited, BigBasket.com was operating in more than 23 cities across the country in 2016. The online grocery market in India was in a stage of growth and transformation, fuelled by India's large urban population who sought a lifestyle of convenience and ease. It had also attracted many entrepreneurs who competed fiercely with each other in a market characterised by thin margins. Intense competition ensured that only a few companies were able to survive and sustain themselves. One of these companies was Big Basket, which succeeded in spite of the competition, attracting Series Da funding worth USD 150b million from the United Arab Emirates-based Abraaj Group in March 2016.2
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Sujo Thomas, Nidhi Titus, Sushmita Suggala and Piyush Kumar Sinha
Parsana Health Centre Private Limited, a part of the INR 4,500 crore1 fitness industry, was a fitness centre established at Ahmedabad (Gujarat) in India in December 2002, as an…
Abstract
Parsana Health Centre Private Limited, a part of the INR 4,500 crore1 fitness industry, was a fitness centre established at Ahmedabad (Gujarat) in India in December 2002, as an integral part of the organized players of the fitness industry. It had been relentlessly working towards creating and nurturing a healthy lifestyle for the people of Ahmedabad over the previous two eventful decades. Under the able guidance of skilled trainers and dieticians, the fitness enthusiast could enjoy state of the art gym facilities, in the upcoming mega city of Ahmedabad. Parsana Health Centre Private Limited enjoyed the first mover advantage in Ahmedabad and tapped the fitness club2 market through its 13 franchises opened in select vantage locations of the city. It was started by the Parsana brothers: Vijay and Dinesh. They strived hard to inculcate the fitness regime in people and attempted to interweave the benefits of fitness with their occupations. However, the road undertaken threw challenges at them – sometimes from people who failed to underline the importance of fitness in their daily schedule, and sometimes from other fitness brands which emerged as strong competitors. The emergence of many individual and branded fitness chains started making inroads into the busy streets of Ahmedabad and they too worked hard to pull out fitness enthusiasts to these social fitness centres by providing personal health counseling, rejuvenation, yoga, etc. Sustaining competitive advantage became a tough task.
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Piyush Kumar Sinha and Arindam Banerjee
The objective of this study is to identify, at a macro level, the drivers of store choice in various product categories, in the context of the evolving retail industry in India…
Abstract
The objective of this study is to identify, at a macro level, the drivers of store choice in various product categories, in the context of the evolving retail industry in India. The paper attempts to correlate the distinct store features as perceived by respondents with the true motivations of various consumers in patronising various stores. In the process it provides insight as to whether the average Indian consumer values the new store dimensions offered by retailers as a part of the new formats emerging in the market place. The framework evolved for evaluating effectiveness of newer store formats is necessary since it has a major impact on the overall profitability of the retailing business. Suggests that customers in a developing market such as India do not require the service paraphernalia offered by many of the new store formats emerging in the market and notes that this may cast a serious doubt over the retail revolution, which has taken shape in the Indian markets lately. Some hypotheses about the evolution of the retailing business in India, which requires further investigation, are suggested.
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Piyush Gupta, Amit Sachan and Rajiv Kumar
Based on social science theories of customer's action such as theory of planned behaviour, theory of reasoned action, and technology acceptance model, this paper adopts…
Abstract
Purpose
Based on social science theories of customer's action such as theory of planned behaviour, theory of reasoned action, and technology acceptance model, this paper adopts belief–attitude–intention model to study impact of perceived process-belief of different stages of e-service delivery system process (e-SDSP), i.e., searching process belief (SPB), agreement process belief (APB), fulfilment process belief (FPB) and after-sales service process belief (ASPB) on customer attitude and intention towards service providers. The study also focuses on the mediating effect of customer attitude on the relationship between process-beliefs of different stages of e-SDSP and their behavioural intention.
Design/methodology/approach
A quantitative method has been employed using data collected from 414 Indian e-retail customers. Structural equation modelling with bootstrap estimation is used to find the mediating effect of attitude.
Findings
The findings suggest that SPB and ASPB directly impact the customer attitude while APB and FPB directly impact the customer behavioural intention. The study also finds that customer attitude towards e-retailers fully mediates the effect of SPB and ASPB on the behavioural intention but there are no mediating effects for APB and FPB.
Research limitations/implications
The sample used may not be generalizable for India, given its huge diversity and population. As the sample considers only Indian e-retail customers, this study may lack generalizability across countries.
Originality/value
In our knowledge, this study is the first step to conceptualize the process-oriented customer's perceived belief of different stages of e-SDSP and how these beliefs impact the customers' attitude and intention towards the e-retailers. The findings offer insight to managers on how they can create and cultivate customer happiness and positive behavioural intention by enhanced customer journey throughout the e-SDSP.
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Shiladitya Dey and Piyush Kumar Singh
The study aims to analyze the impact of market participation on small paddy farmers' income and consumption expenditure. The study also estimates various determinants affecting…
Abstract
Purpose
The study aims to analyze the impact of market participation on small paddy farmers' income and consumption expenditure. The study also estimates various determinants affecting the market participation of smallholders. Further, the study computes the efficiency of different paddy marketing channels and identifies the determinants that impact the marketing channel selection of paddy growers in Eastern India.
Design/methodology/approach
The study used the propensity score matching (PSM) approach to measure the impact of market participation on farm income and per capita consumption. Further, the study employed Acharya and Aggarwal's composite index approach to estimate the marketing efficiency of various paddy marketing channels. Further, a multinomial logit model was used to determine the marketing channel selection constraints.
Findings
The outcomes indicate that market participation positively impacts farm income and consumption expenditure. Education, membership in farmers' organizations, price information and distance to the marketplace significantly affect farmers' market participation. The results show that the producer–retailer marketing channel is the most efficient compared to others. However, most paddy farmers sell paddy to farmgate collectors due to a lack of market information, vehicle ownership, storage system, and inability to take the risk of venturing out of the farmgate into markets.
Research limitations/implications
The study uses primary data and captures only farmers' perspectives to measure the impact of market participation, marketing channel efficiency and determinants for market channel selection. The other stakeholder's perceptions can be included in future studies.
Originality/value
Rarely does any study identifies the efficiency of different marketing channels for paddy farmers in India and includes cognitive factors like risk perception and trust in buyers as constraints for market channel selection.
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Rajiv Kumar, Ritu Kumar, Amit Sachan and Piyush Gupta
E-government quality (e-GovQual) and e-government user value (e-GUV) are multidimensional concepts. While previous studies have identified apparent factors influencing…
Abstract
Purpose
E-government quality (e-GovQual) and e-government user value (e-GUV) are multidimensional concepts. While previous studies have identified apparent factors influencing e-government satisfaction (e-GovSat) and e-government adoption intention (e-GovAI), such as e-GovQual and e-GUV, but they have neglected to explain the influence of the dimensions of these two concepts. The purpose of this research is to study e-government service value chain (e-GSVC) one-GovQual dimensions, e-GUV dimensions, e-GovSat and e-GovAI.
Design/methodology/approach
The study employs a quantitative method to test the hypotheses and validate the proposed model. Data are collected from 378 e-government users across different parts of India comprising of different demographic characteristics. The model is analyzed using structural equation modeling.
Findings
The findings highlight the impact of the dimensions of e-GovQual (efficiency, trust, reliability and citizen support) on the dimensions of e-GUV (functional, economic, social and emotional value) as e-GUV dimensions affect e-GovSat, which in turn influences e-GovAI. The results validate the e-GSVC and also stress the partial mediating role of the dimensions of e-GUV on the relationship between the dimensions of e-GovQual and e-GovSat.
Research limitations/implications
The sample size of 378 may not be a proper representation of a country like India, which has huge diversity within its vast population.
Practical implications
The study offers practitioners a clear picture and a useful guide to better understand the drivers of value, satisfaction and adoption in the case of e-government users.
Originality/value
This study is probably the first attempt toward demonstrating the process influencing e-GovSat via e-GUV dimensions originating from excellent e-GovQual dimensions to ultimately trigger e-GovAI.
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Sanjaya Singh Gaur, Russel P.J. Kingshott and Piyush Sharma
The purpose of this paper is to study the impact of relationship comfort and relationship proneness on the ability of service firms to build and maintain customer relationships in…
Abstract
Purpose
The purpose of this paper is to study the impact of relationship comfort and relationship proneness on the ability of service firms to build and maintain customer relationships in emerging markets (EMs).
Design/methodology/approach
A field-survey was conducted with retail-banking customers in India (n=300) using a structured self-administered questionnaire with well-established scales.
Findings
Relationship comfort positively affects key relationship marketing (RM) constructs (e.g. customer satisfaction, trust, commitment and loyalty) and relationship proneness positively moderates (strengthens) the impact of relationship comfort on customer commitment and loyalty.
Research limitations/implications
The findings may not be generalizable to all customer types using bank services as well as other types of services and in other EMs.
Practical implications
Service firms in EMs can build and maintain robust customer relationships by using relationship comfort and relationship proneness to strengthen key RM constructs, such as customer satisfaction, trust, commitment and loyalty.
Originality/value
The paper highlights the importance of maintaining RM as a tool to build valuable customer relationships but also reveals the importance of relationship comfort and relationship proneness in building trust-based customer relationships in the EMs.
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Anirban Nandy and Piyush Kumar Singh
Data envelopment analysis (DEA) has wide applications in the agricultural sector to evaluate the efficiency with crisp input and output data. However, in agricultural production…
Abstract
Purpose
Data envelopment analysis (DEA) has wide applications in the agricultural sector to evaluate the efficiency with crisp input and output data. However, in agricultural production, impreciseness and uncertainty in data are common. As a result, the data obtained from farmers vary. This impreciseness in crisp data can be represented in fuzzy sets. This paper aims to employ a combination of fuzzy data envelopment analysis (FDEA) approach to yield crisp DEA efficiency values by converting the fuzzy DEA model into a linear programming problem and machine learning algorithms for better evaluation and prediction of the variables affecting the farm efficiency.
Design/methodology/approach
DEA applications are focused on the use of a common two-step approach to find crucial factors that affect efficiency. It is important to identify impactful variables for minimizing production adversities. In this study, first, FDEA was applied for efficiency estimation and ranking of the paddy growers. Second, the support vector machine (SVM) and random forest (RF) were used for identifying the key leading factors in efficiency prediction.
Findings
The proposed research was conducted with 450 paddy growers. In comparison to the general DEA approach, the FDEA model evaluates fuzzy DEA efficiency giving the user the flexibility to measure the performance at different possibility levels.
Originality/value
The use of machine learning applications introduces advanced strategies and important factors influencing agricultural production, which may help future research in farms' performance.