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This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.

The authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.

Fifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.

The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.

Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

Sunit Raj was the Vice President, Marketing of Schematic Software Company (SSC), a Software-as-a-Service (SaaS) company. He was pondering how to preserve the company's growth momentum it had achieved over the last few years. In the third quarter of 2021, the company's valuation reached USD 25 billion, representing a year-over-year gain of 50%. Within 12 years of operation, it had over 50,000 employees worldwide and over 100,000 paying customers in more than 150 countries. Raj had to decide the company's future direction among new territories, buyer segments and product categories that would bring revenue and aid in sustaining its growth.

The case on Moodcafe captures the journey of the start-up and its entrepreneurs from the beginning till the fund-raising stage. The case brings forth critical decisions that each entrepreneur or the team of co-founders have to address during their start-up journey. This short case gives opportunity to delve into two aspects mainly a) As a founder, which investor should one choose for seeking funds and what should be the terms and conditions of investment? and b) How can one review and assess the business model of a start-up?

The AirAsia India 2017 (AAI) case presents the situation faced by Tony Fernandes, the CEO of the AirAsia group of companies, in 2017, when he had to respond to the changes in aviation policy made by the Ministry of Civil Aviation (MCA). As per the changes, an airline operating in India could start its international operations without having five years of domestic flying experience provided it deployed 20 of its aircraft or 20% of the total capacity, whichever was higher, for domestic operations. The objective of this case is to help discuss issues relating to sustaining late entry and exploring new growth opportunities in the context of regulatory changes.

How psychological variables especially self-efficacy plays significant role to attain workplace well-being is yet to be explained. The extant literature calls for further research works in the field of sustainability practices to bridge the gap between self-efficacy and workplace well-being. The purpose of this paper is to extend the literature of workplace well-being while scientifically examining the moderating role of sustainability practices.

The study collected data from 527 full-time executives of Indian public and private manufacturing industries. The authors performed moderated regression analysis through a series of hierarchical models to test the hypotheses of the study.

The result indicates positive relationship between self-efficacy and workplace well-being. Furthermore, the result suggests that the relationship between self-efficacy and workplace well-being was stronger among executives with high level of sustainability practices and vice versa.

The cross-sectional sample of executives employed in Indian manufacturing organizations limits the generalizability of the findings.

HR functionaries and senior management may benefit by closely examining their sustainability practices along with their employees perceived ability to address workplace well-being.

The study contributes to extend the literature on self-efficacy and workplace well-being. This research work is one of the first few studies to examine the moderating effect of sustainability practices.

The purpose of this study is to examine the relationship between organisational learning and adaptive performance. Furthermore, the study investigates the moderating role of emotional intelligence in the perspective of organisational learning for addressing adaptive performance of executives employed in manufacturing organisations.

The participants were selected through purposive sampling. The study has used established scales on organisational learning, emotional intelligence and adaptive performance to collect data from the respondents. Data were analysed through structural equation modelling using linear structural model (LISREL 8.72). Moderated regression analysis was carried out through a series of hierarchical models to test the hypotheses. The authors have followed the interaction graphs recommended by Aiken and West (1991) to check the moderating effect of emotional intelligence.

The result of the study indicates a significant relationship between organisational learning and adaptive performance. The significant moderation effect was observed in the interaction graph, wherein it was found that the relationship between organisational learning and adaptive performance was stronger among the executives with high levels of emotional intelligence and weaker for those having low levels of emotional intelligence.

The present study gains significance through highlighting the role of emotional intelligence in the perspective of organisational learning and, thus, offers insights to practitioners for addressing adaptive performance of employees.

AutoDx Case narrates an exciting story of how organizations in one industry (buyers, suppliers, and suppliers of suppliers), who fiercely compete with each other in the marketplace, collaborated to develop an online platform which would bring in significant efficiency in the system and benefit all the players. The case shows that first attempt to develop such a platform failed in the late 90s. However, similar attempt, later on, was inching towards success. That shows the impact of timing of technology and Shared Beliefs. While Case A narrates the problems faced by a few managers and needs for autoDx, Case B details how the project became successful and was under the process of adoption by various organizations.

With the development of research toward damage detection in structural elements, the use of artificial intelligent methods for crack detection plays a vital role in solving the crack-related problems. The purpose of this paper is to establish a methodology that can detect and analyze crack development in a beam structure subjected to transverse free vibration.

Hybrid intelligent systems have acquired their own distinction as a potential problem-solving methodology adopted by researchers and scientists. It can be applied in many areas like science, technology, business and commerce. There have been the efforts by researchers in the recent past to combine the individual artificial intelligent techniques in parallel to generate optimal solutions for the problems. So it is an innovative effort to develop a strong computationally intelligent hybrid system based on different combinations of available artificial intelligence (AI) techniques.

In the present research, an integration of different AI techniques has been tested for accuracy. Theoretical, numerical and experimental investigations have been carried out using a fix-hinge aluminum beam of specified dimension in the presence and absence of cracks. The paper also gives an insight into the comparison of relative crack locations and crack depths obtained from numerical and experimental results with that of the results of the hybrid intelligent model and found to be in good agreement.

The paper covers the work to verify the accuracy of hybrid controllers in a fix-hinge beam which is very rare to find in the available literature. To overcome the limitations of standalone AI techniques, a hybrid methodology has been adopted. The output results for crack location and crack depth have been compared with experimental results, and the deviation of results is found to be within the satisfactory limit.

This study aims to identify and prioritize various growth-accelerating factors in the Indian automotive industry. It further develops a hierarchical model to examine the mutual interactions between the factors, their dependence and their driving power.

This study first identifies the growth-accelerating factors and then uses the modified total interpretive structural modeling (m-TISM) framework, which is an extended version of TISM. It further uses MICMAC analysis to analyze the mutual interrelation between the identified factors.

This study highlights the interrelation amongst the factors using m-TISM model. A hierarchical model shows the level of autonomous, dependence, linkage and independent factors considering the Indian automotive industry. This study also provides the understanding related to the interdependence of growth-accelerating factors.

The government and practitioners could evaluate the growth-accelerating factors which have higher driving power for implementing efficient policies and strategy formulation. By implementing m-TISM model in the Indian automotive industry, auto manufacturers can become more productive and profitable. Future studies could use other methods such as expert opinion to derive the factors, and further model could be verified using structural equation modeling technique.

This study uses a novel m-TISM framework for the analysis of growth-accelerating factors in the context of the Indian automotive industry. It further provides a detailed theoretical and conceptual understanding relating to the philosophy and establishes an interrelation amongst these under-researched growth-accelerating factors.