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The purpose of the study is to explore the relationship among organisation information technology support (OITS), knowledge sharing behaviour (KSB) and service innovation performance (SIP) in the context of the Indian Hospitality Industry (IHI). This study also attempts to examine the role of KSB as a mediator in the relationship between IT support and SIP and the firm age test as a moderating variable for service innovation performance.

Proposed relations are empirically examined, and the study was carried out on 115 employees from 71 randomly selected hotels situated in the major five travel destinations of Uttarakhand state of India. Initially, confirmatory factor analysis was performed to validate the construct, afterword structural equation modeling (SEM)-Path analysis was accomplished. The researcher examines the mediation and moderation relations of the variables through statistical tests executed with the help of AMOS 24 and SPSS 26.

The study result indicated that organisation IT support has a positive influence on knowledge sharing and SIP. The mediation result findings showed KSB is partially mediated between OITS and SIP. Sequentially, firm age moderation found the statistical results shown significant difference in young and old hotels.

This study only covers the aspect of the “knowledge sharing behaviour” dimension among the major organizations’ IT support capabilities and examined both variables that might be anticipated in SIP. Considering this limitation, new areas of research investigation are open to future researchers.

The study has both theoretical and managerial implications for academicians, practitioners and researchers. An attempt to conceptualise detailed insights on organisational IT support adaptation and KSB enhancement, which further leads to lifting SIP. Moreover, the study recommended for professionals to implement KM practices and mobilise the knowledge resources optimally to achieve better organizational outcomes.

The study attempts to delineate the proposed relationship and provides valuable insights for practitioners and academicians by including the knowledge sharing dimension to improve the SIP context of the IHI.

The study aims to examine the effect of knowledge management strategy (KMS) on knowledge-sharing behavior (KSB) and its subsequent effect on knowledge performance (KP). It also throws light on the mediating role of KM enablers (KMEs) and KSB.

In purview of previous literature, several hypotheses were framed. Structural equation modeling (SEM) using SPSS 20, PROCESS macro and AMOS 20 was used to examine the research hypotheses in a sample of empirical data collected from 350 employees of information technology (IT) service provider firms.

This paper empirically proves the existence of mediation effect of the proposed mediators (KME, KSB) between predictors (KMS, KSB) and outcomes (KSB, KP) in different hypothesized relationships. Result provides empirical evidence toward the positive influence of KMS dimensions (internal-oriented KMS, external-oriented KMS) on KSB and also confirms the influence of KSB on KP.

This study examines the effect of KMS and KSB on KP with reference to the IT sector, thereby limiting generalization to other sectors. Practical and managerial implications have been discussed in the later sections of the study.

This study adds value to the existing KM literature by adjoining the links among knowledge strategy, sharing behavior and performance.

The purpose of this work is to present an approach for autonomous detection of eye disease in fundus images. Furthermore, this work presents an improved variant of the Tiny YOLOv7 model developed specifically for eye disease detection. The model proposed in this work is a highly useful tool for the development of applications for autonomous detection of eye diseases in fundus images that can help and assist ophthalmologists.

The approach adopted to carry out this work is twofold. Firstly, a richly annotated dataset consisting of eye disease classes, namely, cataract, glaucoma, retinal disease and normal eye, was created. Secondly, an improved variant of the Tiny YOLOv7 model was developed and proposed as EYE-YOLO. The proposed EYE-YOLO model has been developed by integrating multi-spatial pyramid pooling in the feature extraction network and Focal-EIOU loss in the detection network of the Tiny YOLOv7 model. Moreover, at run time, the mosaic augmentation strategy has been utilized with the proposed model to achieve benchmark results. Further, evaluations have been carried out for performance metrics, namely, precision, recall, F1 Score, average precision (AP) and mean average precision (mAP).

The proposed EYE-YOLO achieved 28% higher precision, 18% higher recall, 24% higher F1 Score and 30.81% higher mAP than the Tiny YOLOv7 model. Moreover, in terms of AP for each class of the employed dataset, it achieved 9.74% higher AP for cataract, 27.73% higher AP for glaucoma, 72.50% higher AP for retina disease and 13.26% higher AP for normal eye. In comparison to the state-of-the-art Tiny YOLOv5, Tiny YOLOv6 and Tiny YOLOv8 models, the proposed EYE-YOLO achieved 6–23.32% higher mAP.

This work addresses the problem of eye disease recognition as a bounding box regression and detection problem. Whereas, the work in the related research is largely based on eye disease classification. The other highlight of this work is to propose a richly annotated dataset for different eye diseases useful for training deep learning-based object detectors. The major highlight of this work lies in the proposal of an improved variant of the Tiny YOLOv7 model focusing on eye disease detection. The proposed modifications in the Tiny YOLOv7 aided the proposed model in achieving better results as compared to the state-of-the-art Tiny YOLOv8 and YOLOv8 Nano.

The learning outcomes of this paper are as follows: to identify the pros and cons of waged employment and entrepreneurship, to identify the contextual factors influencing entrepreneurship, to set up a new venture, namely, steps, challenges involved and decision-making process, to scale up a small business; when, how and where? And to tradeoff required for scaling up a small business.

Pooja, a young management graduate from Varanasi, decided to overcome all challenges and barriers faced by a women entrepreneur and chase her lifelong dream of creating her own event management startup. After having achieved phenomenal success in a short period of time within the city, she began to receive interest from neighbouring cities as well. The decision to scale up operations was particularly difficult for Pooja, as she had funded the venture through her personal funds and personally nurtured the business and her team based on the values of quality and creativity. Like any small business, she had to decide what level of trade-off was required between scaling and dilution of control over the operations.

The case study is applicable for students of management. The learnings from the case can be applied by an individual who is looking to start a business or expand one.

Teaching Notes are available for educators only.

CSS 3: Entrepreneurship.

The purpose of the present study is to synthesize the extant literature on augmented reality and virtual reality in the apparel industry using bibliometric and network visualization techniques. This paper also highlights the existing gaps in the literature and sets out the future research trajectory.

This study investigated research articles in the domain of augmented and virtual reality in the apparel industry to assess global trends in research production in this area, and top contributors to research by way of authors, journals, countries and institutions. The study carried out an analysis of 239 research articles from the Scopus database during the period 1995 to 2021. The study used open-source bibliometric tools such as Biblioshiny and VOSviewer to analyze the research literature over the search period and also identify emerging research avenues.

The bibliometric analysis reveals that there is significant interest in this research domain. A total of 673 authors contributed to the 239 research articles analyzed and the number of multi-author documents exceeded those by single authors. Research in this domain is led by China with the maximum number of articles in the data set followed by the USA and France. However, the USA has received the highest number of citations. Donghua University from China is the largest contributor to research in this domain with 13 articles in the data set. The keyword co-occurrence analysis indicates that “virtual reality” has the most number of co-occurrences and linkages with other keywords. Other important keywords include “augmented reality,” “virtual try-on” and “cloth simulation.” The network visualization exercise also revealed significant collaboration between different countries in this research domain.

The gaps highlighted in this study will act as a reference point for researchers to conduct future studies in the field of augmented and virtual reality in apparel industry. Practitioners will also gain a comprehensive understanding of this research domain.

This study, to the best of the authors’ knowledge, is the first attempt to integrate the disjoint literature of augmented and virtual reality in apparel industry through a mapping of the intellectual structure of this research domain. The study also contributes by way of providing a snapshot of future research avenues in the knowledge domain of augmented and virtual reality in the apparel industry.

The purpose of our research on blockchain technology is to unveil its immense potential, understand its applications and implications and identify opportunities to revolutionize existing systems and processes. This research aims to inspire the creation of new innovative solutions for industries. By harnessing blockchain technology, organizations can pinpoint key areas that could significantly benefit from its use, such as streamlining operations, providing secure and transparent digital solutions and fortifying data security.

This study presents a robust multi-criteria decision-making framework for assessing blockchain drivers in selected Indian industries. We initiated with an extensive literature review to identify potential drivers. We then sought the opinions of experts in the field to validate and refine our list. This meticulous process led us to identify 26 drivers, which we categorized into five main categories. Finally, we employed the Best-Worst Method to determine the relative importance of each criterion, ensuring a comprehensive and reliable assessment.

The authors have ranked the blockchain drivers based on their degree of importance using the Best-Worst Method. This study reveals the priority of BC implementation, with the retail industry identified as the most in need, followed by the Banking and Healthcare industries. Various critical factors are identified where blockchain technology could help reduce costs, increase efficiency and enable new innovative business models.

While this study acknowledges potential bias in driver assessment relying on literature and expert opinions, its findings carry significant practical implications. We have identified key areas where blockchain technology could be transformative by focusing on select industries. Future research should encompass other industries and real-world case studies for practical insights that could delve into the adoption challenges and benefits of blockchain technology in many other industries, thereby amplifying the relevance of our findings.

Blockchain is a groundbreaking, innovative technology with immense potential to revolutionize industries. Past research has explored the benefits and challenges of blockchain implementation in specific industries or sectors. This creates a gap in research regarding systematically classifying and ranking the importance of blockchain across different Indian industries. Our research seeks to address this gap by using advanced multi-criteria decision-making techniques. We aim to provide a comprehensive understanding of the significance of blockchain technology in critical Indian industries, offering valuable insights that can inform strategic decision-making and drive innovation in the country’s business landscape.

This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

This case study covers marketing concepts, including marketing mix, segmentation, targeting and brand positioning and communication. After completion of the case study, the students will be able to understand the importance of segmentation and targeting; recognize the differences between business-to-business (B2B) and business-to-customers (B2C) segments; gain knowledge about the points of parity and points of difference while positioning; and examine the elements of a marketing mix.

The case centered around Mr. Ashvinder Singh, founder and director of Uni Style Image (USI), who initiated the polo T-shirt business in 1990 in Okhla, Delhi. The brand expanded across the country, but from 2010, USI faced fluctuating demand due to the rise of online marketing and intense competition from global fashion brands. Revenues dropped massively, leading to a significant downsizing from over 300 employees to just 11 by the end of fiscal year 2016–2017. In 2018, Singh explored the B2B model; however, the onset of the COVID-19 pandemic in 2020 impacted many small- and mid-sized apparel businesses, including USI. In the fiscal year 2021–2022, the B2B segment accounted for 90% of total revenue, but the business size could not cover significant operating expenses. Despite only 10% of revenue coming from the B2C segment, Singh wanted to leverage the online space. In September 2022, Singh closed his factory in Noida, National Capital Region, Delhi. Amid the uncertainty, Singh explored various opportunities in the Indian market. In 2023, he even engaged a consultancy for expertise in marketing initiatives. He had to choose the target segment/s, develop a positioning strategy and create an effective marketing mix with very limited resources.

This case is designed for undergraduate and postgraduate students, offering a valuable teaching tool for essential marketing concepts, such as the marketing mix, segmentation, positioning and brand communication. It can be used in both core marketing courses and elective courses like brand management, consumer behavior and integrated marketing communication. The decision dilemma presented in the case enriches the understanding of these concepts, making it a valuable resource for marketing education.

Teaching notes are available for educators only.

CSS 8: Marketing.

Social media use is prevalent today, but there is a possibility that it might go out of control and cause negative consequences. Furthermore, by using social media at work, businesses may develop their networks, communicate in a productive manner and ultimately expand the efficiency. The purpose of this study is to investigate the effect of social media use (SMU) on job performance (JP) through sequential mediators such as social capital dimensions (SC), self-efficacy (SE), job satisfaction (JS) and knowledge sharing (KS) in Indian Public Universities.

Serial mediation model has been used in the study to analyse the relationship. Data is collected from teaching faculty (n = 702) who use social media in Indian public universities. The study has assessed the association between variables using structural equation modelling.

The findings suggest that the dimensions of SC, SE, JS and KS sequentially mediated the effect of SMU on JP. In light of the results, the SMU specifies prerequisites for the development of various dimensions of SC. Similarly, the rest of the mediating constructs further affect the other constructs, which ultimately positively affect JP. The final result shows that the indirect effect between social media use and job performance is positive and significant.

The study provides practical suggestions for university administration regarding the use of social media for teaching faculty.

No research has been done regarding social media use affecting the job performance of teaching faculty through serial mediation in public universities. In this respect, this study represents an original attempt to conduct such research.

One of the most marginalized communities in India is the Lesbian, Gay, Bisexual and Transgender (LGBT) community which commonly experiences discrimination. Many studies have countered that the LGBT community faces high discrimination in the banking and financing industry. As a result, this study concentrates on this marginalized community and its acceptance and continuation habit regarding mobile wallets. Consequently, this study has considered continuance intentions as a response to confirm the progress of the mobile-wallet industry. Also, this study tried to study the relationship between behavioral intention (BI) and continuous intention (CI) which is seriously lacks in the library of literature. The research operationalized the stimulus–organism–response (SOR) framework for the conceptual model and surveyed 100 self-proclaimed members of the LGBT community in India. The analysis has been done using the partial least structure (PLS). The findings demonstrate that variables like perceived trust (PT) directly influence the BI. On the other hand, variables like perceived ease of use (PEoU), social influence (SI), and satisfaction (S) doesn’t influence BI of the LGBT Community. The main outcome was a favorable association between BI and CI. It will help the stakeholders to understand how important this new market avenue is and how it can be explored. To ensure safe and secure transactions, a group think tank composed of important parties (financial institutions, mobile-wallet providers, the government, security specialists, etc.) should make recommendations. Mobile-wallet providers will attain benefit from this study’s understanding of user categories and ability to tailor their service offers as per the community.