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The purpose of this paper is to review the literature on customer experience to develop a better understanding of the concept and propose a research agenda.

The paper is based on a thorough review of 69 full-text articles, 12 books and one published dissertation related to customer experience.

The review describes the relevance of experiential perspective, service experience and customer experience to attract, delight and retain customers. Customer experience is regarded as a holistic interactive process, facilitated through cognitive and emotional clues, moderated by customer and contextual characteristics, resulting into unique and pleasurable/un-pleasurable memories. The study provides a deeper understanding of the concept and research issues for customer experience.

It provides important insights into the emergence, development, management and measurement of customer experience-related issues for future research.

Customer experience needs to be considered and managed as a holistic strategic process for creating customer value, differentiation, customer satisfaction, loyalty and competitive advantage.

The study contributes to the understanding of customer experience and research agenda based on a thorough review of literature spanning 25 years.

This study aims at developing a reliable and valid measure of retail customer experience.

Scientific scale development process has been followed. Survey methodology was used to collect data. The results are tested for reliability and validity using Confirmatory Factor Analysis.

The study conceptualizes retail customer experience as a reliable and valid multidimensional construct, explained in four dimensions: leisure, joy, distinctive and mood.

It was confined to only “brick and mortar” personal lifestyle retail stores. Mediating and moderating effects of contextual variables and the influence of antecedents have not been studied. It provides insights into the “delivered” retail customer experience as perceived by the shoppers for future research.

The scale can be used to measure the experiential responses of retail customers and provide directions for retailing strategies.

The study presents psychometrically valid scale to measure retail customer experience scale.

The purpose of this review is to examine the influence of music on consumption experience and explore the relationships between musical variables and consumer responses in the context of retailing.

The paper is based on the review of studies conducted over last 30 years, empirical and conceptual, dealing with a large number of music‐related variables and their impact on various dimensions of consumption experience.

The studies report that music influences consumption experience at cognitive, emotional, and behavioural levels, specifically with regard to attitudes and perceptions, time and money spend, and moods and feelings, in retail experience. The influence of music is moderated by customer and store profiles, purchase timings, and other ambience factors.

The study provides important insights into critical issues related to influence of music, for future research.

The research brings out important issues for designing musical environment in the retail stores to influence shopping experience and consumer responses.

Based on a critical review of important studies, the present paper proposes a framework to understand the effect of music on consumption experience in retail stores.

This paper aims to propose DisDSS: a Web-based smart disaster management (DM) system for decision-making that will assist disaster professionals in determining the nature of disaster-related social media (SM) messages. The research classifies the tweets into need-based, availability-based, situational-based, general and irrelevant categories and visualizes them on a web interface, location-wise.

It is worth mentioning that a fusion-based deep learning (DL) model is introduced to objectively determine the nature of an SM message. The proposed model uses the convolution neural network and bidirectional long short-term memory network layers.

The developed system leads to a better performance in accuracy, precision, recall, F-score, area under receiver operating characteristic curve and area under precision-recall curve, compared to other state-of-the-art methods in the literature. The contribution of this paper is three fold. First, it presents a new covid data set of SM messages with the label of nature of the message. Second, it offers a fusion-based DL model to classify SM data. Third, it presents a Web-based interface to visualize the structured information.

The architecture of DisDSS is analyzed based on the practical case study, i.e. COVID-19. The proposed DL-based model is embedded into a Web-based interface for decision support. To the best of the authors’ knowledge, this is India’s first SM-based DM system.