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In the current exploration, the machinability of three different nickel-based super-alloy materials (Inconel 625, Inconel 718 and Nimonic 90) was experimentally investigated by using a die-sinking electrical discharge machining (EDM). The effect of changing important input process parameters such as pulse on time (T_on), off time (T_off), peak current (Ip) and tool rotation (TR) was investigated to get optimum machining characteristics such as material removal rate, roughness, electrode wear rate and overcut.

Experimentation has been performed by using Taguchi L9 orthogonal design. An integrated route of fuzzy and grey relational analysis approach with Taguchi’s philosophy has been intended for the simultaneous optimization of machining output parameters.

The most approbatory factors for machining setting have been attained as: (T_on = 100 µs, T_off = 25 µs, Ip = 14 A, TR = 725 rpm) for machining of Inconel 625 and Inconel 718; and (T_on = 100 µs, T_off = 75 µs, Ip = 14 A, TR = 925 rpm) for machining of the Nimonic 90 material. Peak current has been observed as an overall influencing factor to achieve better machining process. Microstructural study through SEM has also been carried out to figure out the surface morphology for the EDMed Ni-based super alloys.

The proposed machining variables and methodology has never been presented for Nimonic 90 alloy on die-sinking EDM.

In the current exploration, the machining of a Nimonic 90 superalloy material was carried out in a die-sinking electric discharge machine. Experimentation was performed to investigate the impact of three input machining factors – current (I), pulse on time (T_on) and pulse off time (T_off) – on various response characteristics such as material removal rate (MRR), surface roughness (R_a) and electrode wear rate (EWR).

A Taguchi L9 design and ANOVA were used to assess machine response characteristics. The study also involved a grey relational analysis (GRA) multi-objective technique of optimization.

For single-objective performance, the most appropriate machining factors for achieving the best performance were attained as: MRR (I = 20 A, T_on = 200 µs and T_off = 45 µs), R_a (I = 14 A, T_on = 100 µs and T_off = 25 µs) and EWR (I = 17 A, T_on = 150 µs and T_off = 45 µs). The proposed grey relational approach provided the optimal settings (i.e. 14 A I, 100 µs T_on and 25 µs T_off) for the variables used to calculate the predicted and experimental results. Also, a confirmation test indicated that the final experimental grey relational grade value was enhanced when the experimentation was performed at optimal setting.

To the best of the authors’ knowledge, the present work is the first to examine the proposed machining variables (i.e. current, pulse on time and pulse off time) in relation to the optimization technique of GRA for a Nimonic 90 alloy using a die-sinking electric discharge machining method.

Strategic Marketing, Marketing Management, Services Marketing.

MBA and Executive MBA.

The case talks about the inception and growth of OYO Rooms, a company that originally started as ORAVEL Stays Ltd. in 2012, as a platform for booking budget and premium accommodations, but graduated to become OYO Rooms, an online aggregator of hotels, with a unique business model of “managing the partial inventory of rooms” in hotels and offering a proposition of affordable, consistent, quality experience to business, leisure and pilgrim travellers. The company received rounds of funding from Greenoaks Capital, Lightspeed Ventures, Sequoia Capital and DSG Consumer Partners. Moreover, unlike its competitors, OYO adapted itself to the fast-changing consumer preference and grew at an enviable pace and by 2016, was present across 190 cities through a network of 6,500 hotels. However, OYO Rooms had to face a multitude of challenges both from the consumer and hotel owners’ ends, primarily service quality concerns from the customers and majorly concerns out of payment irregularities or non-abidance to written contracts from the hoteliers’ end. The dissatisfaction levels increased to an extent that experts started raising questions on the viability of the business. OYO was growing at an aggressive rate but breakeven point was yet to be achieved. Moreover, growing dissatisfaction and switching amongst its customers as well as hoteliers threatened the very existence of the model. The case allows the students to critically analyse the strategies of OYO for deliberation on whether the business model was sustainable in the long run. It also encourages the students to deliberate on the possible growth strategies for OYO as also on the service recovery strategies for OYO.

The case has been positioned around the following modules: industry analysis; value of a two-sided business model to both parties; sustainability of a unique business model, against the challenges that it faces; applying the VRIO framework (resource-based view); complaint handling and service recovery strategies; applying the Ansoff’s grid for possible growth options.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 11: Strategy.

This chapter conceptualises a link between Industrial Revolution 4.0 (IR 4.0), big data, data science and sustainable tourism.

The author adopts a grounded theory and conceptual approach to endeavour in this exploratory research.

The outcome shows a significant rise of big data in the tourism sector under three major dimensions, i.e. business, governance and research. And, some exemplary evidence of institutions promoting the use of big data and data science for sustainable tourism has been discussed.

The conceptualised interlinkage of concepts like IR 4.0, big data, data science and sustainable development provides a valuable knowledge resource to policy-makers, researchers, businesses and students.

The purpose of this paper is to discuss the implementation of lean methodology to reduce the turnaround time (TAT) of a clinical laboratory in a super speciality hospital. Delays in report delivery lead to delayed diagnosis increased waiting time and decreased customer satisfaction. The reduction in TAT will lead to increased patient satisfaction, quality of care, employee satisfaction and ultimately the hospital’s revenue.

The generic causes resulting in increasing TAT of clinical laboratories were identified using lean tools and techniques such as value stream mapping (VSM), Gemba, Pareto Analysis and Root Cause Analysis. VSM was used as a tool to analyze the current state of the process and further VSM was used to design the future state with suggestions for process improvements.

This study identified 12 major non-value added factors for the hematology laboratory and 5 major non-value added factors for the biochemistry lab which were acting as bottlenecks resulting in limiting throughput. A four-month research study by the authors together with hospital quality department and laboratory staff members led to reduction of the average TAT from 180 to 95minutes in the hematology lab and from 268 to 208 minutes in the biochemistry lab.

Very few improvement initiatives in Indian healthcare are based on industrial engineering tools and techniques, which might be due to a lack of interaction between healthcare and engineering. The study provides a positive outcome in terms of improving the efficiency of services in hospitals and identifies a scope for lean in the Indian healthcare sector.

Applying lean in the Indian healthcare sector gives its own potential solution to the problem caused, due to a wide gap between lean accessibility and lean implementation. Lean helped in changing the mindset of an organization toward providing the highest quality of services with faster delivery at an optimal cost.

This paper is an effort to reduce the gap between healthcare and industrial engineering and enhancing the use of lean practices in Indian healthcare. The study is motivated toward implementing lean methodology successfully in services.

COVID-19 pandemic led to changes in the mental processes of tourists towards online travel agents. Therefore, the study aims to determine the factors affecting experiential loyalty intention of travellers during pre- and post-COVID times.

Empirical data analysis using structural equation modelling was performed in the study.

Results indicate that there is a change in the mental process of tourists. Travel companies need to understand that post-COVID, travel has transformed into a completely new world and it is essential to change behaviour accordingly. Traveller’s satisfaction would still be the key to driving loyalty of travellers towards a company.

The study implies that managers must put more effort into creating confidence among travellers because many people are still scared to travel due to the prevalence of the COVID-19 virus. Motivation to travel has declined significantly, which can only be regenerated if managers develop great strategies to drive demand from people.

This study will help in filling the gap that exists in extant literature of tourism by developing a robust model for analysing the factors enhancing experiential loyalty intention of travellers towards online travel agents in the pre- and post-COVID scenarios.

Through this case, participants will be able to:

▪ understand the different approaches to preparing operating budgets;

▪ classify the costs based on traceability to its cost centres;

▪ understand the difference in budget preparation and its analysis under different cost centres;

▪ put together the required information, identify the format and prepare major operating budgets; and

▪ evaluate operating budgets and give suggestions to the company based on budget analysis.

This case is about a manufacturing company that is going to introduce a budgeting system. It highlights the process of information collecting from key employees for budget preparation. This case also deals with various decisions to be made during the implementation of the new system such as the context of budgets, cost units and sequence of budgets.This case will help students to enhance their understanding of the operating budgets. The students will able to visualize the difficulty faced by companies to implement a new system.

This case is applicable in the courses such as Master of Business Administration, Master of Commerce or other postgraduate studies. This can also be discussed in professional courses such as Chartered Accountants, Certified Management Accountants, Company Secretaries, Institute of Cost and Works Accountants of India and Chartered Financial Analysts.

Teaching Notes are available for educators only.

CSS 1: Accounting and Finance.

The present study examines the fluctuations in Socioeconomic and demographic (SED) factors and the prevalence of Non-Communicable Diseases (NCDs) across clusters of states in India. Further, it attempts to analyze the extent to which the SED determinants can serve as predictive indicators for the prevalence of NCDs.

The study uses three rounds of unit-level National Sample Survey self-reported morbidity data for the analysis. A machine learning model was constructed to predict the prevalence of NCDs based on SED characteristics. In addition, probit regression was adopted to identify the relevant SED variables across the cluster of states that significantly impact disease prevalence.

Overall, the study finds that the disease prevalence can be reasonably predicted with a given set of SED characteristics. Also, it highlights age as the most important factor across a cluster of states in understanding the distribution of disease prevalence, followed by income, education, and marital status. Understanding these variations is essential for policymakers and public health officials to develop targeted strategies that address each state’s unique challenges and opportunities.

The study complements the existing literature on the interplay of SEDs with the prevalence of NCDs across diverse state-level dynamics. Its predictive analysis of NCD distribution through SED factors adds valuable depth to our understanding, making a notable contribution to the field.

The purpose of this study was to uncover the impact of social media in supporting environmental conservation (EC) in protected areas.

The study has employed both quantitative and qualitative approaches of a cross-sectional type with simple random and purposive sampling were followed. Primary and secondary data sources were also entertained. A total of 146 observations were used in the analysis. A multiple linear regression analysis was used to measure the impact of social media.

The result revealed user-generated content and ease of language were significant in explaining EC. Environmental activism and social media usage shall be enhanced with environmental concerns (EnvCs) and objectives.

This is s an original research that tried to address the impact social media on EC and its dimensions in Lake Tana Biosphere Reserve. Unlike the research studies so far, this research attempted to uncover the impact of each social media element's impact on each EC dimensions. Besides, the impact of social media element is also assessed on EC as a construct in general. Thus, it will be helpful for policy makers, government and destination management organizations and other stakeholders to identify the areas which should be promoted and areas that need intervention.