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Nonperforming assets in any banking system have stressed the economic health of nations. Resultantly, literature has given considerable impetus to predict failures and bankruptcy. Past studies have focused on the outcome of failures, while, there is a dearth of studies focusing on ongoing firms in bad shape. We plug this gap and attempt to identify underlying communication patterns for firms witnessing prolonged underperformance. Using text mining, we extract and analyze semantic, linguistic, emotional, and sentiment-based features in non-numeric communication channels of these poor-performing firms and their peers. These uncovered patterns highlight the use of vocabulary and tone of communication, in correspondence to their financial well-being. Furthermore, using such patterns, we deploy various Machine Learning algorithms to identify loser firm(s) way ahead in time. We observe promising accuracy over a time window of five years. Such early warning signals can be of critical importance to various stakeholders of a firm. Exploration of writing style-related features for any firm would help its investors, lending agencies to assess the likelihood of future underperformance. Firm management can use them to take suitable precautionary measures and preempt the future possibility of distress. While investors and lenders can be benefitted from this incremental information to identify the likelihood of future failures.

Tourism industry has extensively embraced technologies to enhance operational competencies, service quality over and above customer satisfaction. This chapter presents Information Technologies as an innovative approach to promote tourism destination from Destination Management Organization’s (DMO’s) perspective. Precisely, attention has been given on how destination managers are applying different types of technological tools to promote their tourism business. In recent times, DMOs are implementing several promotional tools with the use of technology like embracing the mobile technology, Social Media, online ads, and building effective marketing strategies innovatively to compete with the cut-throat competition in travel trade. It also tried to provide an insight understanding of the changes in destination manager’s promotional strategies with the advancement of technologies. Based on primary research with destination managers and using the literature review, a collection of technology-based tools used by DMOs for the promotion of tourism at the destination level was identified and their individual impacts were measured to identify the effects on the profit generation. To accomplish the mentioned objectives, an explorative study based on basic demographic analysis along with Pearson correlation and Simple Linear Regression was conducted to examine the individual impacts of the different promotional tools used by DMOs.

Improved production with quality, safety, and security is the biggest challenge of the food industry. Modern technologies, including robotics and automation systems, can help to cope with such issues. This chapter gives a brief view of robotics and automation for the sustainable food industry along with packaging, warehousing, distribution, marketing, and consumer services. It describes the recently implemented solutions of robotic automation in different supply chain operations and various food commodities. The benefits of robotic and automation technology for perishable and semi-perishable items have also been covered. The present research may assist the food industry professionals, supply chain managers, and academicians in implementing automation and robotics in the food industry.

The objective of this research work is to study the artificial intelligence (AI)-based product benefits and problems of the agritech industry. The research variables were developed from the existing review of literature connecting to AI-based benefits and problems, and 90 samples of primary data from agritech industry managers were gathered using a survey of a well-structured research questionnaire. The statistical package of IBM-SPSS 21 was utilized to analyze the data using the statistical techniques of descriptive and inferential statistical analysis. Results show that better information for faster decision-making has been ranked as the topmost AI benefit. This implies that the executives of agritech units have a concern about the quality of decisions they make and resistance to change from employees and internal culture has been ranked as the topmost AI problem.

The Internet of Things (IoT) is becoming increasingly popular in agribusiness to help increase food production capacity for the ever-expanding global population. This chapter provides a holistic overview of the latest trends around the applications of IoT in agriculture. We begin by giving an overview of IoT and its capabilities, followed by a deep dive into the practical and realistic aspects of leveraging IoT into the agroecosystem. IoT is already being used for many intelligent agriculture applications, such as open-field agriculture, controlled environment agriculture (greenhouse), livestock breeding, agricultural machinery, and more. This chapter examines those applications and ventures beyond the farm into several other aspects of the ecosystem, including storage, warehouse ambiance control, agri-data analytics and decision control, logistics, environmental safety, etc. The contents of the chapter would be based on extensive studies and empirical analysis of the latest research papers on this subject from around the globe, accurately interpreted and transformed by the authors in light of their academic background and professional experience in the digital transformation arena.

The world is experiencing technological disruptions due to the dynamic business environment, technological advancements, customer preferences, increasing competitive pressure, globalization of supply chains, and environmental disruptions. Industry 4.0 technologies are paving the way for increased production efficiency and worker safety while optimizing resource utilization and improving sustainability. Industry 4.0 technologies find their applications in almost all sectors, but few studies explore industry 4.0 technologies in agriculture. The agri-food sector has experienced an upward trend in digitalization projects. The digital agri-food supply chains will help in the autonomous decision-making process, leading to enhanced visibility in the agri-food supply chains through real-time traceability solutions, thereby leading to improved food quality. It is anticipated that industry 4.0 technologies in the agri-food supply chains will impact climate change disruptions and improve the unequal distribution of resources in the agricultural sector. The present study highlights various industry 4.0 technologies and their applications in the agri-food supply chains. Based on the findings from a literature review, the study establishes 10 key performance indicators that will benefit decision-making in a digital, data-centered environment.

India's agri-food industry is rapidly expanding to keep up with the country's growing population. With the help of the fourth Industrial Revolution (Industry 4.0), modernization is creating a new revolution in the agri-food sector. Its applications in the food supply chain as a supply chain 4.0 (SC 4.0) have made it convenient to deliver products efficiently from farms to consumers. The various technologies such as the internet of things (IoT), artificial intelligence (AI), big data analytics and blockchain, etc., have impacted emerging supply chains. But many challenges are perceived by stakeholders toward the adoption of SC 4.0 technologies in India. The authors identified the challenges of adopting SC 4.0 for the agri-food sector and used the Total Interpretive Structural Modeling (TISM) tool to analyze those challenges. Based on literature research, nine major issues were diagnosed and then simulated using expert opinion. Primary data were also gathered with the help of a questionnaire to identify the status of acceptance level of these technologies. This study highlights the importance of government support, availability of sources of funds, customer orientation toward food safety, the commitment of management toward modernization, aware and well trained and motivated employees are a few of the major factors impacting the adoption of SC 4.0 technologies.