http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/38 2026-05-22T06:06:13Z http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1879 Title: How customer incivility affects service-sector employees: A systematic literature review and a bibliometric analysis Authors: Chaudhuri, Ranjan.; Apoorva, A.; Vrontis, Demetris.; Siachou, Evangelia.; Trichi, Eleni. Abstract: Practitioners dedicate considerable effort to prescribe, control, and manage actions and reactions of dysfunctional customers when they interact with service sector employees. As customer incivility causes both direct damages to employees and supplemental adverse effects, arising from a sequence of malpractices, academic research in this domain is found to be a necessity. Our study presents a systematic review of the relatively scarce literature on customer incivility, that is organized around the interrogative 6 W framework, aiming to reveal academic trends, to unpack significant contributors and recent dynamics, and to recommend future directions. Together with a bibliometric analysis, we identified the characteristics of the impactful research (e.g., journals, scholar, articles, and countries) since 1997, organized the existing literature along certain themes (i.e., theories used; customer incivility conception; antecedents to customer incivility) and examined the effects of customer incivility on the performance of service sector employees. The research serves as a multidisciplinary guide for practitioners and researchers to link current research areas to future trends. 2023-09-01T00:00:00Z http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1995 Title: Uncovering the role of consumer trust and bandwagon effect influencing purchase intention: an empirical investigation in social commerce platforms. Authors: Anantharaman, Rajesh; Prashar, Sanjeev; Vijay, T Sai Abstract: Owing to the increased use of social media and networking, social commerce is gaining popularity among industry experts and academia. As a result, there are ongoing concerns about creating high-quality buyer-seller relationships in social commerce. To aid this conversation, the present research investigates the influence of several factors – mainly, social presence and trusting beliefs – on sellers’ trustworthiness. It also considers the impact of the bandwagon effect on purchase intention in the field of social commerce, as well as the role of gender differences in the relationship between trust and purchase intention. To validate the measures, the paper applied structural equation modeling to a data set of 204 online consumers in India. The study found that social bonding and bandwagon effect have a strong influence on trust and purchase intention, respectively. The results may encourage social commerce managers to develop better strategies for interacting and communicating with site users. 2023-08-01T00:00:00Z http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1994 Title: Retail atmospherics effect on store performance and personalised shopper behaviour: a cognitive computing approach Authors: Behera, Rajat Kumar; Bala, Pradip Kumar; Vijay, T Sai; Rana, Nripendra P. Abstract: Purpose The best possible way for brick-and-mortar retailers to maximise engagement with personalised shoppers is capitalising on intelligent insights. The retailer operates differently with diversified items and services, but influencing retail atmospheric on personalised shoppers, the perception remains the same across industries. Retail atmospherics stimuli such as design, smell and others create behavioural modifications. The purpose of this study is to explore the atmospheric effects on brick-and-mortar store performance and personalised shopper's behaviour using cognitive computing based in-store analytics in the context of emerging market. Design/methodology/approach The data are collected from 35 shoppers of a brick-and-mortar retailer through questionnaire survey and analysed using quantitative method. Findings The result of the analysis reveals month-on-month growth in footfall count (46%), conversation rate (21%), units per transaction (27%), average order value (23%), dwell time (11%), purchase intention (29%), emotional experience (40%) and a month-on-month decline in remorse (20%). The retailers need to focus on three control gates of shopper behaviour: entry, browsing and exit. Attention should be paid to the cognitive computing solution to judge the influence of retail atmospherics on store performance and behaviour of personalised shoppers. Retail atmospherics create the right experience for individual shoppers and forceful use of it has an adverse impact. Originality/value The paper focuses on strategic decisions of retailers, the tactical value of personalised shoppers and empirically identifies the retail atmospherics effect on brick-and-mortar store performance and personalised shopper behaviour. 2023-08-11T00:00:00Z http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1771 Title: SENE: A novel manifold learning approach for distracted driving analysis with spatio-temporal and driver praxeological features Authors: Bag, Subhajit.; Golder, Rahul.; Sarkar, Sobhan.; Maity, Saptashwa. Abstract: Although there are many studies conducted on distracted driving, the growing number of accidents on roads demands further serious attention. The majority of the distracted driving-related data in real life are unlabeled and higher dimensional, leading to complex analyses. There is a lack of existence of proper indices for understanding the perilousness due to distracted driving, which makes it very difficult to understand which road or neighborhood has a higher risk of accidents. Despite earlier studies have focused on either spatiotemporal or praxeological factors separately, they have not considered both factors together. Moreover, crisp rule extraction and interpretation are lacking in the literature. Therefore, to deal with such issues, we have proposed a new methodology which: (i) develops Schrodinger Eigenmap Neighborhood Embedding (SENE) manifold learning for dimensionality reduction, followed by K-means clustering, (ii) develops road perilousness index (RPI) and neighborhood PI (NPI) to explain dangerousness of roads or neighborhoods, (iii) uses both spatiotemporal and driver praxeological factors, and (iv) develops Tolerance Rough Set Approach (TRSA) for crisp rules generation and interpretation. Road accident data from the Nevada Department of Transportation is used as a case study. Besides, a total of four benchmark datasets from the University of California Irvine repository are also used for comparative study to prove the superiority of our proposed methodology over some state-of-the-art. Experimental results reveal that the proposed methodology outperforms others by providing the highest clustering accuracy with four clusters. Finally, a set of 16 crisp rules are extracted and interpreted from clusters using TRSA. 2023-08-01T00:00:00Z