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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.

This study aims to conduct a bibliometric analysis of sustainable tourism research published in Scopus-indexed journals covering the period from 1997 to 2021. Articles published during these 25 years were subjected to science mapping and performance analysis to propose potential areas for future research.

A bibliometric analysis using performance analysis and science mapping was conducted on 1,754 research papers retrieved from the Scopus database using the keyword “sustainable tourism.” Biblioshiny and VOSviewer are commonly used bibliometric tools. Science mapping techniques use coauthorship, keyword co-occurrence and co-citation analyses.

This study revealed the sustainable tourism publications’ spatial and temporal patterns, indicating a yearly growth rate of 19.9% during a 25-year period. The study identified Stefan Gossling as the most influential author, the “Journal of Sustainable Tourism” as the leading journal and Australia as the most productive country in sustainable tourism literature. The study used co-citation analysis to identify five thematic clusters, namely, reconceptualization and criticism, the role of residents, eco-labeling and the role of stakeholders, community-based tourism and the shift toward establishing sustainability indicators and effective governance and policymaking. The coauthorship analysis identifies the most influential author in collaborative efforts, and the most common pattern of collaboration is between researchers from different institutions in the same country, such as China and the Philippines, followed by collaborations between authors from other countries. The keyword co-occurrence analysis uncovered keywords that aligned with theme clusters generated from the co-citation analysis.

This study comprehensively uncovers five thematic clusters that have never been extracted so far in the literature. Also, it attempts to fill the gaps related to sustainable tourism by suggesting directions for future research.

The objective is to develop an empirical model estimating the relationship and interaction amongst the factors affecting and enhancing green finance (GF) in developing economies like India.

Around nine growth-accelerating enablers of green financing were found through literature and unstructured interviews and analysed using the total interpretive structural modelling (TISM) method. The hierarchical link between each factor is established using TISM, and further to evaluate the driver-dependent relationship the Matriced’ Impacts Croises Appliquee Aaun Classement (MICMAC) approach is utilised.

The findings demonstrate an interrelationship between growth-accelerating factors, where the political environment and information and communication technology (ICT), have minimal dependency but a strong driving force. Political environment and ICT are found as strategic-level factors lying at the bottom of the model driving towards the dependent variables. The government should focus on enacting effective policies such as the green credit guarantee scheme and carbon credit and establishing a regulatory framework to enhance green financing.

This study examines the literature to generalise the findings and focus on the primary motivators for developing green financing. To increase green financial activity, practitioners must concentrate on aspects with significant driving forces. Furthermore, it makes organisations more profitable, efficient and competitive and promotes long-term growth.

The study is the first in the literature which identifies the growth-accelerating factors of green financing using the TISM and MICMAC-based hierarchical models.

As of 2022, the scope of the engagement and interest of debt capital providers in ESG reporting is mainly untapped. However, a vast amount of literature has produced conflicting findings about the importance of debt capital (leverage) as a factor in sustainability reporting (SR). This is the first meta-analysis reconciling the mixed results of 85 single country studies containing 131 effect sizes across 24,482 firms conducted over past three decades (1999–2022) investigating the influence of leverage on SR. The study emphasizes the significance of contextualizing research by identifying the macro-environmental elements modifying debt's impact on SR, through the use of the institutional theory. Eleven country variables were tested on the collected dataset, spread across 36 countries.

Meta-analysis technique for aggregation of existing extant empirical work. Continuous and categorical variable-based moderator analysis to demystify the influence of country characteristics affecting the leverage–SR relationship.

Results show positive significant impact of debt capital providers on SR. Country's level of development, GDP, extent of capital constraints in a country, financial sector development within a nation, country governance factors and corruption levels, country's culture, number of sustainability reporting instruments operational in a country and geographical location proved to be significant moderators.

The study details relevant meaningful research gaps, worthy of uptake by researchers to produce targeted research.

Governments must increasingly go beyond their mandated disclosure role and acknowledge the important institutional factors that have contributed to the expansion of ESG reporting through the creation of nation-specific tools, incentive structures and disclosure-encouraging regulations. To secure a steady flow of funding and prevent negative effects on company value and cost of capital in the midst of prolonged global economic upheaval, businesses must address the information requirements of lenders. The limited total effect size emphasizes the necessity for debt providers to step up their ESG activism and exercise their maximum power and potential in stimulating extensive SR firm-level practices.

The present study is the first meta-analysis reconciling the mixed results of 85 single-country studies containing 131 effect sizes across 24,482 firms conducted over the past three decades (1999–2022) investigating the influence of leverage on SR and demystifying the macro-environmental factors affecting the leverage–SR association.

The study explores the barriers to ESG adoption and develops a hierarchical relationship between identified barriers to determine the driving and dependence power.

Through literature and unstructured interviews nine barriers affecting the adoption of ESG reporting were identified and examined using the modified Total Interpretive Structural Modelling (m-TISM) approach. Further, MICMAC analysis is used to analyse the driver-dependence power amongst the barriers.

In this analysis, the variable lying at the lowest level of hierarchy are considered to be the critical factor and lack of clarity around regulatory and reporting standards is found to be very critical for ESG adoption. To address impediments to ESG adoption, the government should make ESG disclosure mandatory and clearly explain the rules, regulations and advantages associated with ESG implementation.

The current study is very few among examining the barriers to ESG adoption and steppingstone towards the mandatory implementation of ESG disclosures in current scenario.

In the wake of the COVID-19 pandemic, remote working (RW) has emerged as a viable alternative to working employees in general and knowledge workers in particular. However, previous researchers have worked on the concept, development and facilitation of RW since the 1970s. Therefore, this study aims to review the existing literature on RW to ascertain the evolution of the concept in the business and management domain and provide for requisite arguments to extend the settings for future research agendas.

The authors based this study on a bibliometric analysis of articles (n = 349) retrieved from the Web of Science database published between January 1990 and October 2021. The authors have used a bibliometric toolbox comprising performance analysis, science mapping and network analysis in various software namely, VOSviewer, Gephi and Biblioshiny package in R.

The study’s results accentuated important themes like work–life balance, strengthening digital infrastructure, performance and productivity, hybrid work models and well-being and clustered them under four heads with proposed future research questions.

The study is based on a single database; the authors have used an extensive but not exhaustive list of keywords to retrieve the articles. The analysis employs certain threshold limits while using the science mapping technique.

This study would enable managers and academics to comprehensively understand remote work and offer logical implications to appreciate its nuances.

This study is unique as it recognizes the intellectual structure in the existing literature on RW and traces the advancements and exponential growth post-COVID-19. The authors recapitulated the literature as network analysis of the RW facilitation model comprising the antecedents, outcomes, mediators and moderators.

This paper aims to provide insight into the evolving relationship between humans and machines, understanding its multifaceted impact on our lifestyle and landscape in the past as well as in the present, with implications for the near future. It uses bibliometric analysis combined with a systematic literature review to identify themes, trace historical developments and offer a direction for future human–machine interactions (HMIs).

To provide thorough coverage of publications from the previous four decades, the first section presents a text-based cluster bibliometric analysis based on 305 articles from 2,293 initial papers in the Scopus and Web of Science databases produced between 1984 and 2022. The authors used VOS viewer software to identify the most prominent themes through cluster identification. This paper presents a systematic literature review of 63 qualified papers using the PRISMA framework.

Next, the systematic literature review and bibliometric analysis revealed four major historical themes and future directions. The results highlight four major research themes for the future: from Taylorism to advanced technologies; machine learning and innovation; Industry 4.0, Society 5.0 and cyber–physical system; and psychology and emotions.

There is growing anxiety among humankind that in the future, machines will overtake humans to replace them in various roles. The current study investigates the evolution of HMIs from their historical roots to Society 5.0, which is understood to be a human-centred society. It balances economic advancement with the resolution of social problems through a system that radically integrates cyberspace and physical space. This paper contributes to research and current limited knowledge by identifying relevant themes and offering scope for future research directions. A close look at the analysis posits that humans and machines complement each other in various roles. Machines reduce the mechanical work of human beings, bringing the elements of humanism and compassion to mechanical tasks. However, in the future, smart innovations may yield machines with unmatched dexterity and capability unthinkable today.

This paper attempts to explore the ambiguous and dynamic relationships between humans and machines. The present study combines systematic review and bibliometric analysis to identify prominent trends and themes. This provides a more robust and systematic encapsulation of this evolution and interaction, from Taylorism to Society 5.0. The principles of Taylorism are extended and redefined in the context of HMIs, especially advanced technologies.

This study aims to investigate the connection between digital literacy and women’s empowerment in the rural Himachal Pradesh. It explores how improved digital skills contribute to increased empowerment among women with a specific focus on the role of education in enhancing digital literacy.

This study included 250 rural participants who completed structured questionnaires. Analytical tools, including independent-sample t-tests and partial least squares structural equation modeling, were applied to the data to gain insights into the relationship between digital literacy and women’s empowerment.

This study revealed a significant positive link between digital literacy and women’s empowerment in the rural Himachal Pradesh context. Education has emerged as a key factor that influences women’s digital skills and empowerment levels.

This research adds novelty by examining the digital literacy–women’s empowerment nexus in rural Himachal Pradesh and emphasizing the impact of education. The combination of statistical methods offers a robust approach to understanding this relationship and underscores the importance of digital inclusion and education for gender equality and women’s progress.

The hygroscopic properties of 3D-printed filaments and moisture absorption itself during the process result in dimensional inaccuracy, particularly for nozzle movement along the x-axis and for micro-scale features. In view of that, this study aims to analyze in depth the dimensional errors and deviations of the fused filament fabrication (FFF)/fused deposition modeling (FDM) 3D-printed micropillars (MPs) from the reference values. A detailed analysis into the variability in printed dimensions below 1 mm in width without any deformations in the printed shape of the designed features, for challenging filaments like polymethyl methacrylate (PMMA) has been done. The study also explores whether the printed shape retains the designed structure.

A reference model for MPs of width 800 µm and height 2,000 µm is selected to generate a g-code model after pre-processing of slicing and meshing parameters for 3D printing of micro-scale structure with defined boundaries. Three SETs, SET-A, SET-B and SET-C, for nozzle diameter of 0.2 mm, 0.25 mm and 0.3 mm, respectively, have been prepared. The SETs containing the MPs were fabricated with the spacing (S) of 2,000 µm, 3,200 µm and 4,000 µm along the print head x-axis. The MPs were measured by taking three consecutive measurements (top, bottom and middle) for the width and one for the height.

The prominent highlight of this study is the successful FFF/FDM 3D printing of thin features (<1mm) without any deformation. The mathematical analysis of the variance of the optical microscopy measurements concluded that printed dimensions for micropillar widths did not vary significantly, retaining more than 65% of the recording within the first standard deviation (SD) (±1 s). The minimum value of SD is obtained from the samples of SET-B, that is, 31.96 µm and 35.865 µm, for height and width, respectively. The %RE for SET-B samples is 5.09% for S = 2,000µm, 3.86% for S = 3,200µm and 1.09% for S = 4,000µm. The error percentage is so small that it could be easily compensated by redesigning.

The study does not cover other 3D printing techniques of additive manufacturing like stereolithography, digital light processing and material jetting.

The presented study can be potentially implemented for the rapid prototyping of microfluidics mixer, bioseparator and lab-on-chip devices, both for membrane-free bioseparation based on microfiltration, plasma extraction from whole blood, size-selection trapping of unwanted blood cells, and also for membrane-based plasma extraction that requires supporting microstructures. Our developed process may prove to be far more economical than the other existing techniques for such applications.

For the first time, this work presents a comprehensive analysis of the fabrication of micropillars using FDM/FFF 3D printing and PMMA in filament form. The primary focus of the study is to minimize the dimensional inaccuracies in the 3D printed devices containing thin features, especially in the area of biomedical engineering, by delivering benefits from the choice of the parameters. Thus, on the basis of errors and deviations, a thorough comparison of the three SETs of the fabricated micropillars has been done.

Cryptocurrency has emerged as a significant component on the surface of the financial industry. With its growing popularity and blockchain as an underlying technology, cryptocurrency has the potential to disrupt the digital payments market. In light of this, this study aims to identify and empirically validate factors that influence the continuous intention of customers toward the adoption of cryptocurrency.

The study extends consumption value theory by incorporating additional variables – monetary value, perceived trust and perceived risk – to enhance the predictive power of the proposed model. The data were analyzed using the partial least square technique on the sample of 285 customers.

The results indicate that trust is the most significant factor to influence customers’ intention to use cryptocurrency, followed by conditional value, epistemic value, emotional value and monetary value. The authors also found the significant moderating effect of personal innovativeness on behavioral intention and actual usage of cryptocurrency.

The analysis of the study gives policymakers valuable information for the establishment of the regulatory framework that supports innovation while protecting the rights of the consumer.

The study embeds great theoretical and practical significance by generating a new technical thread that will facilitate multiple players to use their resources optimally.