Purpose The purpose of this paper is to investigate the adoption and implementation of supply chain management practices (SCMPs) on supply chain performance (SCP) and firm performance (FP) in the organized retail industry in a developing country like India. Design/methodology/approach An empirical study was conducted on a sample size of 125 responses collected from the supply chain heads of organized retail firms in India. A theoretical model was developed depicting the relationship between SCMPs, SCP and FP. The theoretical model was tested using mediating multiple regression analysis. Findings This research suggests that the SCMPs are positively related to SCP and FP. Customer relationship management and supplier relationship management are reported as the most important SCMPs, which had the maximum impact on the FP in the organized retailing context in India. Research limitations/implications The research employed perceptual performance measures. Future studies can use actual performance parameters like profit and sales growth to better quantify the benefits of SCM in this context. Originality/value This research is an attempt to empirically test the impact of SCMPs on FP in organized retailing context in an emerging market, India.

Purpose The purpose of this paper is to analyze the factors affecting mobile banking adoption among young Indian consumers. Design/methodology/approach The authors use a cross-sectional survey research design to empirically examine the factors affecting mobile banking adoption among young Indian consumers. The study sample consists of 269 respondents aged between 23 and 30 years from India. Findings The findings of the study suggest that perceived usefulness (PU), perceived ease of use (PEU), perceived credibility (PC) and structural assurance (SA) are strong determinants of user satisfaction (US) and behavioral intention (BI) to use the mobile banking service. US was found to partially mediate the relationship between PU, PEU, PC and SA and BI to use the service. Perceived risk was found to be statistically insignificant in terms of its relationship with BI to use the service. Research limitations/implications The results of this study provide good evidence for banks to further revamp their work practices in the area of mobile banking to enhance the overall penetration of mobile banking in India. Originality/value The study identifies factors influencing mobile banking adoption among young Indian consumers. Furthermore, this study suggests that US partially mediates the relationship between factor influencing mobile banking adoption and BI.

Purpose The purpose of this paper is to ascertain the performance of Indian hospitals in recent past and derive meaningful insights for policy makers and practicing managers in this area. Design/methodology/approach This paper analyses the technical efficiency of select Indian private hospitals using three related methodologies: data envelopment analysis (DEA), Malmquist Productivity Index (MPI) and Tobit regression. Two output variables (i.e. total income and profit after tax) and four input variables (i.e. cost of labour, net fixed assets, current assets and other operating expenses) were selected for the purpose of the study. Findings DEA analysis has shown that 14 out of 37 hospitals are found to be efficient under the Cooper and Rhodes model of DEA and 20 out of 37 hospitals are efficient under the Banker, Charles and Cooper model of DEA. The empirical results pertaining to MPI indicate an overall productivity progress in the private Indian hospital industry during the study period, which is largely due to technological advancement in the industry. Tobit regression demonstrates that chain affiliated, specialized and multi-city located hospitals exhibit a higher technical efficiency. Research limitations/implications This study has a limitation with reference to the unavailability of data on the input and output parameters of the model. The data related to the number of beds, number of doctors, number of nurses, etc., were not available for the period under consideration. Originality/value This study seems to be one of the few studies applying productivity and performance analysis using DEA, MPI and Tobit regression for the Indian private hospital industry.

Purpose – The purpose of this paper is to analyze the performance of Indian retailers in recent past and derive meaningful insight for practicing managers in this area. Design/methodology/approach – This paper analyses the economic efficiencies of select Indian retailers using three related methodologies: Data Envelopment Analysis (DEA), Malmquist Productivity Index (MPI) and Bootstrapped Tobit Regression. Findings – DEA analysis has shown that five retail firms out of selected 18 are found as efficient under the CCR model of DEA and seven out of 18 retail firms are efficient under the BCC model of DEA. MPI results indicate that 61 percent of the firms have progressed in terms of the MPI during the period under consideration. The Bootstrapped Tobit Regression shows that number of retail outlets and mergers and acquisitions can be considered as the driving forces influencing efficiency of retailers in India. Research limitations/implications – The paper has a limitation with reference to the availability of data for a few retail outlets, especially in the modeling through the Bootstrapped Tobit Regression. Originality/value – This study seems to be the first in applying productivity analysis using DEA, MPI and Bootstrapped Tobit Regression for the Indian retail sector.

Purpose This paper aims to understand the impact of modern technologies such as artificial intelligence on impulse buying behaviour of Indian shoppers specifically in fashion retail outlets. Design/methodology/approach The empirical study on the effect of artificial intelligence on impulse purchase decisions was conducted through an e-survey of the Indian shoppers. The data collected was analysed using factor analysis and multiple regression analysis. Findings The impact of modern technologies which are used by the retailers to enhance sale and consumer engagement was studied. The relationship between use of artificial intelligence parameters such as the purchase duration, recommended products, product information and human interaction and its impact on Impulse Purchase was studied and the results revealed that all these factors except product information had a significant impact on the impulse purchase decision of the buyer. Practical implications This study will be useful to the fashion retailers to gauge the effect of incorporating artificial intelligence and its impact on driving sales by attracting shoppers to their outlets. Originality/value This study specifically focusses on the impact of modern technologies on impulse purchase of Indian shoppers in fashion retail outlets. Other research works have focussed on impact of visual merchandising, store layouts, store environment and promotional activities on impulse purchases. This is one of the few studies which deals with the impact of artificial intelligence on impulse buying behaviour of Indian shoppers specifically in the fashion retail segment.