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The purpose of this study is to describe the use of complementary and alternative medicine (CAM), pain reliever use and the expectations refugees have of physicians about their practice of CAM use in the USA. Individuals with a refugee background are one of the populations who use CAM for treatment. However, to date, there is insufficient empirical evidence to describe CAM use among refugees resettled in the USA. In addition, collecting information about the use of pain relievers would help better understand the experiences of individuals with a refugee background.

Data was collected from August 2018 to November 2019 using a self- or interviewer-administered survey from 94 refugees 18 years of age or older who had settled in the USA.

This study found the following: CAM practice is very common among refugees resettled in the USA, most refugees use non-prescription pain medicine and refugees prefer to see physicians who understand CAM. This study contributes valuable findings in the usage of CAM among refugees and determines that CAM is commonly used among refugees resettled in the USA for pain management.

By better understanding CAM, physicians can address a direct need for the refugee population-seeking health care in the USA and other countries that host refugee resettlement.

Although India has a number of health issues, the healthcare facilities in India are insufficient due to poor quality of care. The purpose of this paper is to examine the factors affecting the structural quality of healthcare facilities in India.

This study used the medical facility data from the India Human Development Survey-II, 2011–2012 (ICPSR 36151) (n=4,218). Logistic regression was conducted to predict structural quality of healthcare facilities.

The results suggest that it is difficult to have all standard resources available at health care facilities in India. Surprisingly, having a drinking water source inside the health facility appears to be an indicator of poor structural quality of health care facilities. Having a water source inside a health care facility is associated with not having a separate exam room and not having a sink to wash hands. A higher registration fee was associated with good structural quality and with having a separate exam room and having a sink to wash hands.

This study shows the complexity of providing quality health care to the poor, particularly in developing countries. Research on quality of healthcare facilities in India is needed to improve the health of the population. Little research has been done on the factors influencing the structural quality of the healthcare facilities in India. This study is an important contribution to the current knowledge of structural healthcare facility standards and its influences in India.

Manufacturing industries are facing dynamic challenges in today’s highly competitive world. In the recent past, integrating Industry 4.0 with the lean six sigma improvement methodologies has emerged as a popular approach for organizational excellence. The research aims to explore and analyze critical success factors of lean six sigma integrated Industry 4.0 (LSSI).

This research study explores and analyzes the critical success factors (CSFs) of LSSI. A three-phase study framework is employed. At first, the CSFs are identified through an extensive literature review and validated through experts’ feedback. Then, in the second phase, the initial list of CSFs is finalized using the fuzzy DELPHI technique. In the third phase, the cause-effect relationship among CFSs is established using the fuzzy DEMATEL technique.

A dyadic relationship among cause-and-effect category CSFs is established. Under the cause category, top management commitment toward integrating LSSI, systematic methodology for LSSI and organizational culture for adopting changes while adopting LSSI are found to be topmost CSFs. Also, under the effect category, organizational readiness toward LSSI and adaptability and agility are found to be the uppermost CSFs.

The study offers a framework to understand the significant CSFs for LSSI implementation. Insights from the study will help industry managers and practitioners to implement LSSI and achieve organizational excellence.

To the best of the authors’ knowledge, CSFs of LSSI are not much explored in the past by researchers. Findings will be of great value for professionals in developing long-term operations strategies.

The purpose of this study is to identify the prominent research constituents in the domain of integration of Lean manufacturing and Industry 4.0 techniques and analyze the intellectual structure among them.

A bibliometric analysis of articles based on Donthu et al. (2021a) has been adopted to conduct a systematic review of the integration of Lean manufacturing and Industry 4.0 using the Scopus database.

The co-citation analysis and bibliographic coupling depicted three clusters and themes around which the research related to the integration of Lean manufacturing and Industry 4.0. Publications related to the topic have majorly focused on the development of conceptual models and frameworks for integrating Lean manufacturing and Industry 4.0, analyzing the compatibility between the two techniques for better implementation of one another and the techniques' combined impact on operational performance.

Most of the review studies related to the domain of integration of Lean manufacturing and Industry 4.0 have adopted a systematic literature review methodology. The present study has tried to infer the intellectual framework of the research being conducted in the said domain using the bibliometric analysis to identify the prominent research constituents in the field and examine the intellectual relationship between them.

Introduction: AI technologies are transforming the industrial sectors, and the impact of AI technologies does not leave behind human resource management (HRM). From recruitment to development and payroll, AI has its own impact. In recruitment, selection, training and development, compensation, and remuneration AI play an important role.

Purpose: The main purpose of this chapter is to analyse the challenges in adopting AI in HRM. This chapter investigates the various strategies to overcome challenges encountered by companies while adopting AI in HR practices. Moreover, this chapter also examines the role of AI in HR practices.

Methodology: To achieve the purpose of this chapter, various case studies were analysed and literature studies with emphasis on what types of challenges are face in adopting AI in HR practices. The authors of various newspaper articles, books, published journals, and websites on AI analyse the various newspaper articles, books, published journals, and websites on AI in human resources (HR). Electronic databases are used as the most effective technique to begin a literature search for the current overview, specifically Science Direct, Google Scholar, and Emerald. In addition to this, the application of AI in HRM practices used by leading organisations globally is also reviewed. The analysis used four keywords: HRM, AI, challenges and adopting. This research has been conducted by searching scholarly papers and relevant studies using similar keywords.

Findings: The adoption of AI technologies is continuously increasing in HR practices. AI performs various HR functions such as recruitment, selection, training and development practices, scanning resume, etc. Organisations can be benefitted in many ways by adopting AI in HRM practices, such as better employees engagement and relations, accelerating competitive advantages and effectively utilising HR budgeting. The findings show that many companies like IBM, Deloitte, Amazon, etc., adopt AI in their HR practices.

The purpose of this paper is to predict the machining performance of electrical discharge machining of Ti-13Nb-13Zr (TNZ) alloy, a promising biomedical alloy, using artificial neural networks (ANN) models.

In the research, three major performance characteristics, i.e. the material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR), were chosen for the study. The input parameters for machining were the voltage, current, pulse-on time and pulse-off time. For the ANN model, a two-layer feedforward network with sigmoid hidden neurons and linear output neurons were chosen. Levenberg–Marquardt backpropagation algorithm was used to train the neural networks.

The optimal ANN structure comprises four neurons in input layer, ten neurons in hidden layer and one neuron in the output layer (4–10-1). In predicting MRR, the 60–20-20 data split provides the lowest MSE (0.0021179) and highest R-value for training (0.99976). On the contrary, the 70–15-15 data split results in the best performance in predicting both TWR and SR. The model achieves the lowest MSE and highest R-value for training in predicting TWR as 1.17E-06 and 0.84488, respectively. Increasing the number of hidden neurons of the network further deteriorates the performance. In predicting SR, the authors find the best MSE and R-value as 0.86748 and 0.94024, respectively.

This is a novel approach in performance prediction of electrical discharge machining in terms of new workpiece material (TNZ alloys).

The case focuses on the importance of the brand-building process, which takes place in B2B companies. Commodity companies focus a lot on the sales and distribution aspect of their marketing strategies but do not emphasize the importance of developing their brands. At the end of the discussion, the participants would be able: to examine the steps involved in conceptualizing the brand identity for an existing product in a highly competitive B2B market, as per Kapferer’s Brand Identity Matrix. To understand the steps involved in the journey of internal and external brand-building processes in B2B. To analyze the various challenges and issues faced by large organizations dealing in the metals and commodity business.

The case discusses a marketing challenge faced by Jindal Steel and Power Limited (JSPL) in launching a new brand of thermomechanical treatment (TMT) products in the market. Traditionally, the company had focused on the sales and distribution aspect of their marketing strategies but did not emphasize the importance of developing their brands. This case is based upon the challenges faced in the creation of a new brand identity for JSPL’s TMT products by the protagonist, Mr Paras Sharma (who is the brand custodian and manager in this case).

Postgraduate/Masters in Business Administration (MBA), Masters in Management Studies, Executive MBA.

Teaching Notes are available for educators only.

CSS 8: Marketing.

This article aims to explore synergies between Lean, Green and Six Sigma practices in order to propose an integrated LGSS framework for continuous and incremental improvement in the Indian manufacturing industries. The three-dimensional LGSS framework seeks to provide various combinations and support operational, financial, environmental and social needs.

In the research method, first, the current problems faced by Indian manufacturing industries are considered and proposition of a conceptual framework that qualitatively integrates synergistic aspects of Lean, Green and Six Sigma practices, and second, the framework is checked by a survey taken from 203 Indian firms by using SPSS-AMOS.

The hypothesized result suggests that the positive impact of integrated practices on firm performance in terms of operational, financial, social and environmental outcomes. It also provides a systemic and holistic approach to problem-solving through constant and incremental enhancement in the manufacturing sector.

In this research, only Indian manufacturing industries have been studied but can be extending into different geographical areas and sectors. Future research is also possible for different behavior and characteristics of companies that can lead to recommending strategies on how companies can improve performance. Most importantly, future research can try to understand which specific practice can contribute to competitive advantage and business success.

Manufacturing firms that want to improve environmental sustainability should implement integrated LGSS practices into their supply chain. The set of combined practices improves operational, social, economical and environmental benefits.

The research presents an integrated approach of LSS for the manufacturing industry which leads their business processes to achieve economic sustainability through continuous growth and improved operational efficiency. Manufacturing industries result in outcomes like reduced cost, lead time, improved quality, sustainable market position, profitability, customer satisfaction, etc.

This research is different from previous studies because it integrates Lean, Green and Six Sigma practices into a unique framework that fulfills a specific need of the Indian manufacturing sector that guides operational, social, environmental and financial issues in Indian industries.