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Purpose: With this study, the authors aim to highlight the application of machine learning in smart appliances used in our day-to-day activities. This chapter focuses on analysing intelligent devices used in our daily lives to examine various machine learning models that can be applied to make an appliance ‘intelligent’ and discuss the different pros and cons of the implementation.

Methodology: Most smart appliances need machine learning models to decrypt the meaning and functioning behind the sensor’s data to execute accurate predictions and come to appropriate conclusions.

Findings: The future holds endless possibilities for devices to be connected in different ways, and these devices will be in our homes, offices, industries and even vehicles that can connect each other. The massive number of connected devices could congest the network; hence there is necessary to incorporate intelligence on end devices using machine learning algorithms. The connected devices that allow automatic control appliance driven by the user’s preference would avail itself to use the Network to communicate with devices close to its proximity or use other channels to liaise with external utility systems. Data processing is facilitated through edge devices, and machine learning algorithms can be applied.

Significance: This chapter overviews smart appliances that use machine learning at the edge. It highlights the effects of using these appliances and how they raise the overall living standards when smarter cities are introduced by integrating such devices.

Purpose: This chapter aims to analyse and highlight the current landscape of performance management (PM) systems, and the benefits of integrating modern technology such as smart analytics (SA) and artificial intelligence (AI) into PM systems. The chapter discusses the application of AI in PM tasks which successively simplify many offline PM tasks.

Methodology: To carry out this analysis, a systematic literature review was performed. The review covers literature detailing PM components as well as research concerned with the integration of SA and AI into PM systems.

Findings: This study uncovers the merits of using SA and AI in PM. SA technology provides organisations with a clear direction for improvement, rather than simply state failure in performance. AI can be used to automate redundant tasks while retaining the human element of decision-making. AI also helps reduce the time required to take action on feedback.

Significance: The findings of this research provide insights into the use of SA and AI to make PM tasks fast, scalable, and error-free.

This study develops a multidimensional framework using data envelopment analysis (DEA) as a benchmarking tool to assess the performance of the commercial banks in India. Using the DEA approach, this study compares the relative performance of 35 banks against one another with 8 variables as the benchmark parameters. This study finds that most of the banks are consistently performing well over a period from 2005 to 2009. The study also shows the areas in which inefficient banks are lagging behind and how they can improve their performance to bring them at par with the efficient commercial banks.

This chapter explores the significance of blockchain technology in protecting data for intelligent applications across various industries. Blockchain is a distributed ledger that ensures the immutability and security of transactions. Given the increasing need for security measures in industries, understanding blockchain technology is crucial for preparing for its future applications.

This chapter aims to examine the use of blockchain technology across industries and presents a compilation of existing and upcoming blockchain technologies for intelligent applications. The methodology involves reviewing research to understand the security needs of different industries and providing an overview of methods used to enhance multi-institutional and multidisciplinary research in areas like the financial system, smart grid, and transportation system.

The findings highlight the benefits of blockchain networks in providing transparency, trust, and security for industries. The Responsible Sourcing Blockchain Network (RSBN) is an example that utilizes blockchain's decentralized ledger to track sustainable sourcing from mine to final product. This information can be shared with auditors, corporate governance organizations, and customers.

The practical implications of this chapter are significant, serving as a valuable resource for industries concerned with identity privacy, traceability, immutability, transparency, auditability, and security. Understanding and implementing blockchain technology can address the growing need for secure and intelligent applications, ensuring data protection and enhancing trust in various sectors.

One major impact of demonetisation is rise of cashless or digital transactions. The extension of the transition from a cash-based to a cashless economy has expanded even more now, based on the lessons learnt from the COVID-19 pandemic. This chapter discusses the various electronic payment methods used by the people, the frequency of using these methods and also to examine the reasons of changing habits in using electronic modes of payments. This study is both theoretical and empirical in nature, based on both primary and secondary data. Digitalising rural and poor population is much in talks but earlier literature did not acknowledge the status of slums and its inhabitants. Slum dwellers are the ones to be in the margin, and therefore are subject to more societal sufferings. In the context of female population particularly, the mechanism of urbanisation and increment in urban slums are subject to unique causes and unique consequences, and still these challenges are greatly underexplored by earlier literature in this field. Thus, the aim of this chapter is to find out the schemes, achievements and challenges for the cashless transaction practised by the female slum dwellers. To be extremely explicit, the sample area consists of two biggest slums of Kolkata and 100 female respondents are inquired for this study, taking 50 from each slum. For analysing the collected data, descriptive statistics tools and percentage analysis have been used. This chapter will also analyse India's gradual transition towards a cashless economy. Through the examination of digitalisation of slum dwellers, this study also attempts to identify whether digital modes result in empowerment of these women, of any kind. By paying a visit in the discussion of women empowerment, this chapter wants to revisit the 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDGs) adopted by world leaders in 2015, that embodies a roadmap for progress which leaves no one behind. The questions impacting achievement of SDG through women empowerment may not seem of utmost concern during the current situation but is equally important and needs to be discussed on a platform of its own.

This paper assesses the impact of a pioneering and unique initiative by Hindustan Lever Ltd, the Indian subsidiary of Unilever Ltd through its Project Shakti program. The study used qualitative interviews of women microentrepreneurs participating in this program about personal and occupational issues. Our analysis suggested several themes such as entrepreneurial development, economic empowerment, and social empowerment.

Budget hotels are becoming an emerging industry for convenience and affordability, where consumer sentiments are of paramount importance. Tourism has become increasingly dependent on social media and online platforms to gather travel-related information, purchase travel products, food, lodging, etc., and share views and experiences. The user-generated data helps companies make informed decisions through predictive and behavioural analytics.

Design/Methodology/Approach: This study uses text mining, deep learning, and machine learning techniques for data collection and sentiment analysis based on 117,151 online reviews of the customers posted on the TripAdvisor website from May 2004 to May 2019 from 197 hotels of five prominent budget hotel groups spread across India using Feedforward Neural Network along with Keras package and Softmax activation function.

Findings: The word-of-mouth turns into electronic word-of-mouth through social networking sites, with easy access to information that enables customers to pick a budget hotel. We identified 20 widely used words that most customers use in their reviews, which can help managers optimise operational efficiency by boosting consumer acceptability, satisfaction, positive experiences, and overcoming negative consumer perceptions.

Practical Implications: The analysis of the review patterns is based on real-time data, which is helpful to understand the customer’s requirements, particularly for budget hotels.

Originality/Value: We analysed TripAdvisor reviews posted over the last 16 years, excluding the Corona period due to industry crises. The findings reverberate in consonance with the performance improvement theory, which states feed-forward a neural network enhances organisational, process, and individual-level performance in the hospitality industry based on customer reviews.

Purpose – Exploration of the methodological aspects of male sex work is rather limited. Without a strong methodological toolkit to draw from, research in male sex work will not be able to accurately capture changes in the dynamic sex work environment. Thus, the author provides a comprehensive review of methods in male sex work along with a broad spectrum of methodological insights through which future research can be advanced.

Methodology/approach – Drawing from two studies that the author conducted in the male independent escorting space, this chapter provides a range of methodological insights and offers avenues for future research.

Findings – This chapter reviews the methods used in male sex work research over the years and details the lack of research on methodological inquiry in the field.

Originality/value – With the increasing normalization and dynamism of male sex work, it is necessary for the research to provide methodological guidance for the next wave of studies in the field. The recommendations and research directions proposed herein are hoped to have implications for research in the larger sex work context.