Customer retention has become very important in the heightened competitive environment unleashed in India, post liberalization. Recently, some researchers have made attempts to evolve and link the service convenience construct to customer satisfaction and repeat purchase from a service organization. Service convenience — a multidimensional construct with five dimensions, involves aspects beyond locational nearness or convenient operating hours. The present study aims at validating the service convenience (ServCon) scale originally developed in the West, in the Indian organized food and grocery retail context, and develop linkage between service convenience on one side, and satisfaction/behavioural intentions on the other. Convenience samples, comprising of respondents from SEC A and SEC B with experience of shopping from organized retail food and grocery outlets, were drawn from various parts of Ahmedabad city. Through the scale validation process, five dimensions emerged, as in the original 17 items ServCon scale, though with 15 items (Seiders et al, 2007). Scale validity was evaluated using correlation and confirmatory factor analysis while neural networks were used for nomological model testing. Subsequently, using cluster analysis, an attempt was made to segment respondents based on their service convenience scores which resulted in four customer segments being identified: Aspirers Fatalists Balance-oriented Pre-purchase convenience seekers. Statistically insignificant differences were observed amongst these clusters based on demographics. In the Indian context, it is found that access, benefit, and decision convenience dimensions have more importance whereas dimensions like transaction and post-benefit convenience are less relevant. Hence, retail mall managers should focus on providing better access, benefit, and decision convenience rather than transaction and post-benefit convenience. In the same vein, shopping enjoyment appears to be having a major effect on service convenience as compared to customer involvement in product category implying that shoppers experiencing higher levels of shopping enjoyment should be accorded more importance by mall managers. On the other hand, it is found that higher the perceived service convenience level, the greater the impact on shopper�s behavioural intentions as compared to satisfaction. This implies that organized retail mall managers should focus on shoppers who perceive higher levels of service convenience from malls, as they are more likely to patronize such malls by way of either positive word of mouth or increasing their visit/purchase frequency.
As renewable energy (RE) penetration has a continuously increasing trend, the protection of RE integrated power systems is a critical issue. Recently, power networks developed for grid integration of solar energy (SE) have been designed with the help of multi-tapped lines to integrate small- and medium-sized SE plants and simultaneously supplying power to the loads. These tapped lines create protection challenges. This paper introduces an algorithm for the recognition of faults in the grid to which a solar photovoltaic (PV) system is integrated. A fault index (FI) was introduced to identify faults. This FI was calculated by multiplying the Wigner distribution (WD) index and Alienation (ALN) index. The WD-index was based on the energy density of the current signal evaluated using Wigner distribution function. The ALN-index was evaluated using sample-based alienation coefficients of the current signal. The performance of the algorithm was validated for various scenarios with different fault types at various locations, different fault incident angles, fault impedances, sampling frequencies, hybrid line consisting of overhead (OH) line and underground (UG) cable sections, different types of transformer windings and the presence of noise. Two phase faults with and without the involvement of ground were differentiated using the ground fault index based on the zero sequence current. This study was performed on the IEEE-13 nodes test network to which a solar PV plant with a capacity of 1 MW was integrated. The performance of the algorithm was also tested on the western part of utility grid in the Rajasthan State in India where solar PV energy integration is high. The performance of the algorithm was effectively established by comparing it with the discrete Wavelet transform (DWT), Wavelet packet transform (WPT) and Stockwell transform-based methods.
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