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Internet of Things (IoT) and artificial intelligence are two leading technologies that bought revolution to each and every field of humans using in daily life by making everything smarter than ever. IoT leads to a network of things which creates a self-configuring network. Improving farm productivity is essential to meet the rapidly growing demand for food. In this chapter, the authors have introduced a smart greenhouse by integration of two leading technologies in the market (i.e., Machine Learning and IoT). In proposed model, several sensors are used for data collection and managing the environment of greenhouse. The idea is to propose an IoT and Machine Learning based smart nursery that helps in healthy growing and monitoring of the seed. The structure will be a dome-like structure for observation and isolation of an egg with various sensors like pressure, humidity, temperature, light, moisture, conductivity, air quality, etc. to monitor the nursery internal environment and maintain the control and flow of water and other minerals inside the nursery. The nursery will have a solar panel from which it stores the electricity generated from the sun, a small fan to control the flow of air and pressure. A camera will also be equipped inside the nursery that will use computer vision technology to monitor the health of the plant and will be trained on the past data to notify the user if the plant is diseased or need attention.

This chapter presents the e-marketing practices followed by the micro, small and medium enterprises (MSMEs) in India. It explored the owner-managers perceptions of MSMEs regarding their average expenditures, budget allocations, management, policy, sources of information, return on investment and their desire for formal training on e-marketing activities in future. Data were collected from 253 MSME owner-managers through an e-questionnaire. The researchers found that the majority of the MSME owner-managers allocate a monthly budget for e-marketing initiatives, and they have increased it over the past few years. However, the total expenditure on e-marketing activities is between 1% and 10% of their total marketing budget. These businesses are partly or fully outsourcing search engine optimization (SEO), display advertising and referral marketing, whereas other e-marketing activities are managed in-house. Generally, these MSMEs are not measuring the success of their digital marketing efforts. If they do it, they are not doing it in a professional manner. MSMEs were found to be slow in posting content and engaging their followers on social media. Surprisingly, two-third of the MSMEs that participated in this study did not show any desire to pursue courses in digital marketing. In conclusion, this study puts forward key implications to practitioners as well as to the government agencies that are involved in the promotion of information technology among MSMEs.

This paper aims to describe the fabrication and characterization of current mirror-integrated microelectromechanical systems (MEMS)-based pressure sensor.

The integrated pressure-sensing structure consists of three identical 100-µm long and 500-µm wide n-channel MOSFETs connected in a resistive loaded current mirror configuration. The input transistor of the mirror acts as a constant current source MOSFET and the output transistors are the stress sensing MOSFETs embedded near the fixed edge and at the center of a square silicon diaphragm to sense tensile and compressive stresses, respectively, developed under applied pressure. The current mirror circuit was fabricated using standard polysilicon gate complementary metal oxide semiconductor (CMOS) technology on the front side of the silicon wafer and the flexible pressure sensing square silicon diaphragm, with a length of 1,050 µm and width of 88 µm, was formed by bulk micromachining process using tetramethylammonium hydroxide solution on the backside of the wafer. The pressure is monitored by the acquisition of drain voltages of the pressure sensing MOSFETs placed near the fixed edge and at the center of the diaphragm.

The current mirror-integrated pressure sensor was successfully fabricated and tested using in-house developed pressure measurement system. The pressure sensitivity of the tested sensor was found to be approximately 0.3 mV/psi (or 44.6 mV/MPa) for pressure range of 0 to 100 psi. In addition, the pressure sensor was also simulated using Intellisuite MEMS Software and simulated pressure sensitivity of the sensor was found to be approximately 53.6 mV/MPa. The simulated and measured pressure sensitivities of the pressure sensor are in close agreement.

The work reported in this paper validates the use of MOSFETs connected in current mirror configuration for the measurement of tensile and compressive stresses developed in a silicon diaphragm under applied pressure. This current mirror readout circuitry integrated with MEMS pressure-sensing structure is new and fully compatible to standard CMOS processes and has a promising application in the development CMOS-MEMS-integrated smart sensors.

Some studies have been reported in the past on diaphragmatic hernia (DH) surgery techniques using additive manufacturing (AM) technologies, symptoms of a hernia and post-surgery complications. But hitherto little has been reported on bibliographic analysis (BA) for health monitoring of bovine post-DH surgery for long-term management. Based on BA, this study aims to explore the sensor fabrication integrated with innovative AM technologies for health monitoring assistance of bovines post-DH surgery.

A BA based on the data extracted through the Web of Science database was performed using bibliometric tools (R-Studio and Biblioshiny).

After going through the BA and a case study, this review provides information on various 3D-printed meshes used over the sutured site and available Internet of Things-based solutions to prevent the recurrence of DH.

Research gaps exist for 3D-printed conformal sensors for health monitoring of bovine post-DH surgery.

The purpose of this study is to comprehensively analyse and compare equity crowdfunding (ECF) regulations across 26 countries, shedding light on the diverse regulatory frameworks, investor and issuer limits and the evolution of ECF globally. By addressing this research gap and providing consolidated insights, the study aims to inform policymakers, researchers and entrepreneurs about the regulatory landscape of ECF, fostering a deeper understanding of its potential and challenges in various economies. Ultimately, the study contributes to the advancement of ECF as an alternative financing method for small and medium enterprises (SMEs) and startups, empowering them to access much-needed capital for growth.

The study used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model for a systematic literature review on global ECF regulations. Starting with 74 initial articles from Web of Sciences and Scopus databases, duplicates were removed and language criteria applied, leaving 42 articles. After a thorough full-text screening, 20 articles were excluded, resulting in the review of 22 papers from 2016 to 2022. PRISMA’s structured framework enhances the quality of systematic reviews, ensuring transparency and accessibility of findings for various stakeholders, including researchers, practitioners and policymakers, in the field of ECF regulations.

This study examines ECF regulations across various countries. Notably, the UK has advanced regulations, while the USA adopted them later through the Jumpstart Our Business Startups Act. Canada regulates at the provincial level. Malaysia and China were early adopters in Asia, but Hong Kong, Japan, Israel and India have bans. Turkey introduced regulations in 2019. New Zealand and Australia enacted laws, with Australia referring to it as “crowd-sourced equity funding”. Italy, Austria, France, Germany and Belgium have established regulations in Europe. These regulations vary in investor and issuer limits, disclosure requirements and anti-corruption measures, impacting the growth of ECF markets.

This study’s findings underscore the diverse regulatory landscape governing ECF worldwide. It reveals that regulatory approaches vary from liberal to protectionist, reflecting each country’s unique economic and political context. The implications of this research highlight the need for cross-country analysis to inform practical implementation and the effectiveness of emerging ECF ecosystems. This knowledge can inspire regulatory adjustments, support startups and foster entrepreneurial growth in emerging economies, ultimately reshaping early-stage funding for new-age startups and SMEs on a global scale.

This study’s originality lies in its comprehensive analysis of ECF regulations across 26 diverse countries, shedding light on the intricate interplay between regulatory frameworks and a nation’s political-economic landscape. By delving into the nuanced variations in investor limits, investment types and regulatory strategies, it unveils the multifaceted nature of ECF regulation globally. Furthermore, this research adds value by comparing divergent perspectives on investment constraints and offering an understanding of their impact on ECF efficacy. Ultimately, the study’s unique contribution lies in its potential to inform practical implementation, shape legislative frameworks and catalyse entrepreneurial ecosystems in emerging economies, propelling the evolution of early-stage funding practices.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

The purpose of this paper is to determine the role of service quality (SQ), trust and commitment to customer loyalty (CL) for telecom service users. Further, the moderating role of gender, marital status and connection type within the model was tested.

A measurement model was created based on valid 615 responses from Indian TSUs for SQ, trust, commitment and loyalty with the help of partial least squares structural equation modeling (PLS-SEM). Multi-group analysis (MGA) was conducted to understand the moderating effect of marital status, gender and connection type within the model.

The results suggest that, out of five dimensions of SQ, only responsiveness, assurance and empathy have a significant positive relationship with both commitment and trust. Tangibility has a significant positive relationship with trust only. Both commitment and trust have a significant impact on loyalty. It was noticed that both commitment and trust act as mediators between three SQ dimensions (assurance, empathy and responsiveness) and CL. MGA revealed that empathy and responsiveness positively induce trust in telecom users who are single. Whereas, assurance increases commitment toward telecom service providers in married users. Assurance and empathy significantly contribute toward commitment and trust, respectively, in male users as compared to females. Empathy was found important for postpaid users for trust-building, whereas trust was found to be more important for prepaid users to stay loyal to the service provider.

This article contributes toward understanding the role of SQ, trust and commitment to CL moderated by marital status, gender and connection type in an integrated model concerning telecom service.

Human resource management, Employee relations, Strategic human resource management.

The given case study is to be used by graduate and post-graduate students of Management in the courses of Human Resource Management & Employee Relations. The case may also be used for the discussions on the concepts such as discipline, disciplinary enquiry, grievance settlement procedure, workplace counseling and strategic human resource management.

The given case study is hypothetical in nature and meant for academic purpose and classroom teaching. In the given case study, the authors present a grievance settlement mechanism of a banking sector organization. The case study is about a grievance and its settlement of a sales executive in the branch office through the involvement of other senior officials at the workplace. The case study is useful to understand the significance of disciplinary issues, grievance settlement and domestic enquiry and counseling at the workplace.

The learning objective of the case is to make students understand the significance and various aspects of employee relations at the workplace. It aims at making students familiar with the requirement of discipline, focus on grievance settlement procedure and conducting disciplinary inquiry. The case study further has purpose to make students learn about the importance of counseling and be familiar with steps in counseling for handling real-life situations in their career.

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 6: Human Resource Management.

The purpose of this paper is to propose a conceptual framework for the application of blockchain in the Public Distribution System (PDS) in India to manage the supply of food grains to the targeted beneficiaries. The framework will help prevent diversions and leakages of grains at the warehouse and Fair Price Shop (FPS) level. The paper also identifies the enablers and disablers in the context of the framework.

This paper will firstly review the previous literature in PDS and blockchain-enabled agricultural and food supply chains. The study then proposes a framework that could be implemented in the PDS in India using blockchain technology.

The proposed framework provides an effective way to combat corruption, exclusion errors of targeted beneficiaries, leakage of PDS food grains and is cost-effective. The identified enablers and disablers give an insight into the application of blockchain in PDS in India.

The research work may have implications for the Ministry of Food and PDS (Central Government), Food Corporation of India and State Governments to manage the supply of the grains more efficiently and effectively.

The current study caters to the implementation of blockchain technology starting from the warehouse level to the FPSs and consumers and simultaneously connecting them to concerned authorities to ensure transparency and accountability.