Search results

The purpose of this paper is to study the anodising process of a portable amplifier production process to identify and eliminate the sources of variations, in order to improve the process productivity.

The study employs the define-measure-analyse-improve-control (DMAIC) Six Sigma methodology. Within the DMAIC framework various tools of quality management such as SIPOC analysis, cause and effect diagram, current reality tree, etc., are used in different stages.

High rejection rate was found to be the main problem leading to lower productivity of the process. Four types of defects were identified as main cause of rejections in the baseline process. Pareto analysis resulted in detection of the top defects, which were then analysed in details to find the root cause of the problem. Further study resulted in finding improvement measures that were discussed with the management before implementation. The process is sampled again to check the improvements, and control measures were established.

The study provides a framework for implementation of DMAIC Six Sigma methodology for a manufacturing firm. The results presented are based on the data collected from the shop floor. Results and findings of the study were implemented for quality improvement of the process.

The study is based on an original research conducted with the objective of quality improvement in the anodising process of the production process. Besides presenting an approach to DMAIC Six Sigma methodology, an application of the current reality tree tool for root cause analysis is presented, a tool used limitedly in the Six Sigma studies. The tool finds its uniqueness in its ability to address problems relating multiple factors than isolated factors.

This case study attempts to sensitize the impact of restructuring on the organization’s employer brand. The students shall learn to appreciate the criticality of maintaining a balance between being an employee-centric organization and building a sustainable business model, to analyze the alternative people management strategies in emerging start-ups.

This case study illustrates the innovative human resource (HR) policies adopted by the start-up Meesho. Meesho was started as “Fashnear” by two Indian Institute of Technology graduates Sanjeev Barnwal and Vidit Aatrey in the year 2015, with the headquarters located in Bengaluru, Karnataka, India. It was a social commerce platform wherein the local apparel sellers or manufacturers could register themselves on the app and sell their products online to nearby consumers and the product would be delivered to their homes. Later, it was renamed Meesho (Meri E-Shop) with an improved business model. The innovative people-centric policies got Meesho recognition as one of the most employee-friendly start-ups and an innovative employer. However, later as part of the restructuring exercise, it had to lay off employees, which had a counter impact on its reputation and image as a desirable employer. This case study captures the dilemma faced by start-ups like Meesho who were in the process of sustaining their growth and optimizing their workforce and, at the same time, have to manage their employer brand in the process.

This case study can be used at the postgraduate level of management and in executive management programs.

Teaching notes are available for educators only.

CSS6: Human resource management.

The paper aims to research the current understanding of Slow Food in the Indian hospitality sector and to identify how the industry can embrace the concept and its sustainability. To begin, underpinnings are considered in relation to traditional, locally produced food for patrons that is actually “farm to fork” in terms of its delivery model as evidenced by backward integration in the supply of key ingredients. The economics of the backward integration is analysed to measure its impact on businesses’ bottom-line in the context of an inflationary economy.

Existing published literature is reviewed with reference to the “Slow Food movement” from both an international and Indian perspective. Vedatya’s approach to sustainable culinary value chain creation and its applicability for industry adoption with an intent to offer Slow Food on commercial menus is documented and discussed. A round table discussion with key food and beverage leaders is also documented and analysed to establish the current state of awareness and readiness of the sector to offer “Slow Food” through an integrated supply chain in India.

Slow Food as a concept is new to India; there is a huge shift in many parts of the world towards food that is fresh, traditional and drawn from locally available ingredients. This research shares Vedatya’s experience in developing an integrated value chain that can provide a sustainable Slow Food model for the Indian hospitality and restaurant sector to deploy with a positive impact on profitability too.

There is need for more research to better understand the feasibility of hospitality businesses working on supply chain with backward integration, to offer “Slow Food” to consumers. While there seems to be a demand for traditional food, this paper does not research that aspect; further research is required to ascertain the potential demand for Slow Food in India.

The popularity of Slow Food is global; however, the Indian hospitality sector is yet to warm up to this potential. The customer focus on healthy, traditional, fresh food opens an opportunity to innovate, and businesses that build capacity to offer real farm-to-fork menus can become market leaders and will reap bottom-line benefits through lower input costs because of supply chain integration.

This paper is unique in terms of offering a discussion on the potential of Slow Food as the next realm of culinary innovation in India. It also adds value by sharing the Vedatya experience in terms of developing an integrated supply chain that facilitates the Slow Food offering in a farm-to-fork format. The model can be emulated by commercial hospitality businesses resulting in cost advantages and higher satisfaction levels of customers.

The paper aims to profile the theme issue of Worldwide Hospitality and Tourism Themes titled “How is the need for innovation being addressed by the Indian hospitality industry?” with reference to the experiences of the theme editor, contributors from the industry and academia and the theme issue outcomes.

The paper uses structured questions to enable the theme editor to reflect on the rationale for their theme issue question, the starting-point, the selection of the writing team and material and the editorial process.

It highlights recent innovations that have taken place in the Indian hospitality industry especially in the areas of customer service, cost competitiveness, culinary management, revenue management and technology.

As hotel sector investment in India intensifies, this theme issue will be of interest to hoteliers, policy makers, analysts and others interested in the role that innovation can play in helping to facilitate differentiation between competing hotel products and services.

There is limited literature available on industry innovations in the Indian context. All the papers in this theme issue were written after several cycles of interaction between academics and practitioners and so they incorporate real–time, relevant and contemporary data.

The study aims to investigate the impact of social media influencer information overload (SMIIO) on customer purchase avoidance through mediation of customer confusion along with the moderation of prior product knowledge through the stressor-strain-outcome (SSO) framework.

The data collected from 429 participants (YouTube and Instagram followers) from an online survey were analyzed using structural equation modeling.

The findings reveal that SMIIO significantly leads towards customer purchase avoidance. Customer confusion mediates between SMIIO and purchase avoidance, while prior product knowledge weakens the impact of SMIIO on confusion through moderation.

The findings provide a wide range of applications for brand managers and social media influencers to adopt clear, concise communication strategies. Reducing information overload and minimizing confusion can enhance consumer decision-making. Tailored messaging based on consumer product knowledge can further optimize marketing efforts and reduce purchase avoidance.

This study uniquely applies the SSO framework to examine the effects of SMIIO on purchase avoidance, highlighting the mediating role of customer confusion and the moderating influence of prior product knowledge, offering a fresh perspective on consumer behavior.

The purpose of this study is to monitor suspended particulate matter (SPM), PM2.5 and source apportionment study for the identification of possible sources during the year 2018–2019 at Raipur, India.

Source apportionment study was performed using a multivariate receptor model, positive matrix factorization (PMFv5.0) with a view to identify the various possible sources of particulate matter in the area. Back-trajectory analysis was also performed using NOAA-HYSPLIT model to understand the origin and trans-boundary movement of air mass over the sampling location.

Daily average SPM and PM2.5 aerosols mass concentration was found to be 377.19 ± 157.24 µg/m³ and 126.39 ± 37.77 µg/m³ respectively. SPM and PM2.5 mass concentrations showed distinct seasonal cycle; SPM – (Winter ; 377.19 ±157.25 µg/m?) > (Summer; 283.57 ±93.18 µg/m?) > (Monsoon; 33.20 ±16.32 µg/m?) and PM2.5 – (Winter; 126.39±37.77 µg/m³) > (Summer; 75.92±12.28 µg/m³). Source apportionment model (PMF) have been applied and identified five major sources contributing the pollution; steel production and industry (68%), vehicular and re-suspended road dust (10.1%), heavy oil combustion (10.1%), tire wear and brake wear/abrasion (8%) and crustal/Earth crust (3.7%). Industrial activities have been identified as major contributing factor for air quality degradation in the region.

Chemical characterization of aerosols and identification of possible sources will be helpful in abatement of pollution and framing mitigating strategies. It will also help in standardization of global climate model.

The findings provide valuable results to be considered for controlling air pollution in the region.

The current study investigates the role of consumer ethnocentrism (CE) in the context of locally produced organic food. This research work further extends the extended theory of planned behavior (TPB) model by examining the mediating effect of extended TPB variables (ATT, SN, PBC, PV) between CE and PI for locally produced organic food.

Data were obtained from the visitors of two shopping malls situated in a large, heavily populated city of India using survey method. Further, two-step approach was applied to analyze the hypothesized model.

Findings indicate that CE is a substantial determinant of PI for locally produced organic food. Moreover, extended TPB mediates the relation between CE and PI for locally produced organic food.

Post Covid-19, market size of organic food is rapidly growing in India. In this regard, this study presents useful implications for the marketers of organic food for gaining better consumer insights to further develop appropriate marketing strategies.

CE has been found to be a useful predictor of their food attitudes. However, studies, investigating the role of CE in the context of sustainable food consumption, are scant. Moreover, studies exploring the mediating effect of extended TPB variables are also very limited.

Background: Artificial intelligence (AI) is a booming sector that has profoundly influenced every walk of life, and the education sector is no exception. In education, AI has helped to develop novel teaching and learning solutions that are currently being tested in various contexts. Businesses and governments across the globe have been pouring money into a wide array of implementations, and dozens of EdTech start-ups are being funded to capitalise on this technological force. The penetration of AI in classroom teaching is also a profound matter of discussion. These have garnered massive amounts of student big data and have a significant impact on the life of both students and educators alike.

Purpose: The prime focus of this chapter is to extensively review and analyse the vast literature available on the utilities of AI in health care, learning, and development. The specific objective of thematic exploration of the literature is to explicate the principal facets and recent advances in the development and employment of AI in the latter. This chapter also aims to explore how the EdTech and healthcare–education sectors would witness a paradigm shift with the advent and incorporation of AI.

Design/Methodology/Approach: To provide context and evidence, relevant publications were identified on ScienceDirect, PubMed, and Google Scholar using keywords like AI, education, learning, health care, and development. In addition, the latest articles were also thoroughly reviewed to underscore recent advances in the same field.

Results: The implementation of AI in the learning, development, and healthcare sector is rising steeply, with a projected expansion of about 50% by 2022. These algorithms and user interfaces economically facilitate efficient delivery of the latter.

Conclusions: The EdTech and healthcare sector has great potential for a spectrum of AI-based interventions, providing access to learning opportunities and personalised experiences. These interventions are often economic in the long run compared to conventional modalities. However, several ethical and regulatory concerns should be addressed before the complete adoption of AI in these sectors.

Originality/Value: The value in exploring this topic is to present a view on the potential of employing AI in health care, medical education, and learning and development. It also intends to open a discussion of its potential benefits and a remedy to its shortcomings.

The study attempts to investigate the role of social media in spreading awareness regarding ayurvedic immunity boosters (AIB) and changes in diet. Further, the study examines the factors affecting the willingness to pay for ayurvedic immunity boosters (WPIB) during the pandemic and new normal situation with the moderating effect of the “fear of COVID-19 infection.”

The data were collected from millennials in two phases, i.e. the first phase (1 July–August 2021) with 300 respondents and a second phase with (June–August 2022) 257 respondents. An online questionnaire was shared with millennials using the snowball sampling technique. Descriptive statistics with SPSS and SmartPLS 4.0 software were applied to analyze the data.

The results found a variation in AIB content sharing on social media during 2021 and 2022. Results found that respondents reported significant changes in their lifestyle and diet, like consuming honey, khada, tulsi tea, etc. In 2021, health consciousness and trust significantly affected WPIB, whereas in 2022, only health consciousness was substantially affected. Fear of COVID-19 infection moderates the relationship between health consciousness, perceived fear and willingness to pay for ayurvedic products, whereas the effect on consumer preference and trust remains insignificant.

Results could help ayurvedic product manufacturing companies understand the consumers' mindset and the factors that stimulate consumers to buy these immunity boosters. Ayurvedic advertisers should design unambiguous messages that focus on health consciousness and have trustable components to encourage consumers to adopt a healthy lifestyle.

This is one of its kinds of studies that presents the contrasts of how the COVID-19 crisis has significantly changed individuals' dietary intake and affected lifestyle patterns.