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This study aims to examine whether agricultural commodities exhibited deviations in the lead-lag relationship between future and spot prices of farmer producer organizations (FPOs) traded commodities in the Indian derivative market after trade suspensions during Covid-19. The study may help buyers and sellers to get a fair price for their commodities after lockdown-trade disruptions.

The study applied the Granger causality (GC) test and the vector error correction model (VECM) to analyse short-run and long-run lead-lag relationships. Moreover, the study examined the pre-post-trade suspension effect on the lead-lag relationship of commodity prices.

The GC test results show that five out of the 13 agri-commodities have changed their lead-lag relationship from future to spot in the short run. Simultaneously, VECM captured changes in the lead-lag relationship for the same five commodities in the long run due to trade suspensions.

The findings indicate a reverse lead-lag relationship between future and spot prices for aforesaid commodities after trade suspension. The stakeholders may use the lead prices for these commodities to perform a fair trade. The study may be helpful in structuring price discovery strategy to achieve optimal price and efficient derivative trading.

To the best of the authors’ knowledge, this is the first study examining the effects of trade suspension on price discovery in FPO-traded agri-derivatives caused by the COVID-19 pandemic.

The study aims to analyze the impact of market participation on small paddy farmers' income and consumption expenditure. The study also estimates various determinants affecting the market participation of smallholders. Further, the study computes the efficiency of different paddy marketing channels and identifies the determinants that impact the marketing channel selection of paddy growers in Eastern India.

The study used the propensity score matching (PSM) approach to measure the impact of market participation on farm income and per capita consumption. Further, the study employed Acharya and Aggarwal's composite index approach to estimate the marketing efficiency of various paddy marketing channels. Further, a multinomial logit model was used to determine the marketing channel selection constraints.

The outcomes indicate that market participation positively impacts farm income and consumption expenditure. Education, membership in farmers' organizations, price information and distance to the marketplace significantly affect farmers' market participation. The results show that the producer–retailer marketing channel is the most efficient compared to others. However, most paddy farmers sell paddy to farmgate collectors due to a lack of market information, vehicle ownership, storage system, and inability to take the risk of venturing out of the farmgate into markets.

The study uses primary data and captures only farmers' perspectives to measure the impact of market participation, marketing channel efficiency and determinants for market channel selection. The other stakeholder's perceptions can be included in future studies.

Rarely does any study identifies the efficiency of different marketing channels for paddy farmers in India and includes cognitive factors like risk perception and trust in buyers as constraints for market channel selection.

Data envelopment analysis (DEA) has wide applications in the agricultural sector to evaluate the efficiency with crisp input and output data. However, in agricultural production, impreciseness and uncertainty in data are common. As a result, the data obtained from farmers vary. This impreciseness in crisp data can be represented in fuzzy sets. This paper aims to employ a combination of fuzzy data envelopment analysis (FDEA) approach to yield crisp DEA efficiency values by converting the fuzzy DEA model into a linear programming problem and machine learning algorithms for better evaluation and prediction of the variables affecting the farm efficiency.

DEA applications are focused on the use of a common two-step approach to find crucial factors that affect efficiency. It is important to identify impactful variables for minimizing production adversities. In this study, first, FDEA was applied for efficiency estimation and ranking of the paddy growers. Second, the support vector machine (SVM) and random forest (RF) were used for identifying the key leading factors in efficiency prediction.

The proposed research was conducted with 450 paddy growers. In comparison to the general DEA approach, the FDEA model evaluates fuzzy DEA efficiency giving the user the flexibility to measure the performance at different possibility levels.

The use of machine learning applications introduces advanced strategies and important factors influencing agricultural production, which may help future research in farms' performance.

The purpose of this paper is to examine the relationship between customer loyalty and customer dependence in the context of modern format and traditional format stores. In the process, the role of switching cost and trust in this relationship has been explored.

Building on the literature, the authors have postulated a conceptual model and formulated relevant hypotheses. Quantitative methodology is applied with previously established. The data were collected through convenient sampling. Methods like Factor analysis, cross-tab and regression analysis have been used.

The findings indicate a significant relationship between customer loyalty and customer dependence. Switching cost and trust have been found to have a moderating effect over the relationship in both modern and traditional environments.

The limitation is the restriction to the Jammu context. The studies have brought about the difference in attitudinal and behavioural loyalty. Future research can be carried out on the role of dependence in explaining and strengthening this relationship.

The present study provides an insight into for the customer loyalty and customer dependence in the context of modern and traditional retail formats.

The study assesses the relationship between institutional credit access and farmer satisfaction using contextual mediating and moderating variables. This study identifies various socioeconomic, service features and service quality determinants impacting institutional credit access.

The authors used the stratified random sampling method and selected 512 farmers from 40 villages in Maharashtra, India. Initially, the study employed probit regression analysis to identify the credit adoption determinants. Subsequently, the relationship between institutional credit and farmer satisfaction is identified through moderated-mediation analysis using the Statistical Package for the Social Sciences and Analysis of a Moment Structures (SPSS - AMOS model).

Probit model's results suggest that socioeconomic variables like education and bank distance; service quality variables like prompt service and employee behavior; and service characteristics variables like the interest rate, loan sanction time, repayment period, and documents for loan application significantly affect institutional credit adoption across the smallholders. Subsequently, the results of the moderating-mediation analysis show that working capital, perceived value and risk perception partially mediate the association between credit adoption and farmer satisfaction. The mediated effects are further moderated by farm advisory services and financial knowledge and skills.

The study is restricted in opportunity due to primary data, and it considers only farmers' perspectives to measure service quality and service features as constraints for institutional credit access.

The government, nongovernment organizations, civil societies and private institutions should provide sufficient financial knowledge and training to the farmers via extension services to utilize the borrowed capital effectively to bring economic welfare and mental satisfaction.

The existing literature rarely considered banking service quality and service features (demand side) variables as determinants of credit access. Further, the study brings novelty in examining how the capital management cognitive factors of the formal credit adopters influence the relationship between credit access and satisfaction.

The purpose of this paper is to develop a framework to understand how bottom of the pyramid (BoP) retailers adopt brands who sell to a very different set of customers and are served through long indirect channels.

In this study, 60 retailers belonging to different villages of Central and North Gujarat were interviewed. The interviews were audio recorded, transcribed and analyzed. A grounded theory-based analysis was carried out.

The analysis brought out six criteria used by the retailers in selecting brands with demand for the brand as the most dominant factor. Other criteria included brand adoption by other retailers, profitability, influence of wholesaler/distributor and packaging.

Previous studies with regard to brand adoption by retailers have focused on large retailers who are approached directly by the brands. There is a lack of studies on how BoP retailers adopt brands. Most studies have approached the subject from a distribution perspective of reaching these markets.

The purpose of this paper is to examine the role of playfulness on innovative consumers’ pre-order behavior for new products.

Drawing upon self-congruity theory and early adoption literature, the effects of playfulness and innovativeness on pre-order behavior and the role of self-congruity are tested using four experimental studies that are analyzed using generalized linear model (GLM) and structural equation modeling.

Results indicate that playfulness amplifies the advance-purchasing propensity, especially when the pre-launch information cues come from a credible source.

This paper refines playfulness measurement scales and proposes how both enjoyment- and creativity-based playfulness amplify the purchase intention among innovative consumers. The results assist product managers in developing advanced marketing plans before a new product is launched.

BigBasket.com, an online supermarket established in December 2011 in Bangalore, India, had become one of the major players in the Indian online grocery market by the end of March 2016.₁ Run by Innovative Retail Concepts Private Limited, BigBasket.com was operating in more than 23 cities across the country in 2016. The online grocery market in India was in a stage of growth and transformation, fuelled by India's large urban population who sought a lifestyle of convenience and ease. It had also attracted many entrepreneurs who competed fiercely with each other in a market characterised by thin margins. Intense competition ensured that only a few companies were able to survive and sustain themselves. One of these companies was Big Basket, which succeeded in spite of the competition, attracting Series D_a funding worth USD 150_b million from the United Arab Emirates-based Abraaj Group in March 2016.₂

Parsana Health Centre Private Limited, a part of the INR 4,500 crore¹ fitness industry, was a fitness centre established at Ahmedabad (Gujarat) in India in December 2002, as an integral part of the organized players of the fitness industry. It had been relentlessly working towards creating and nurturing a healthy lifestyle for the people of Ahmedabad over the previous two eventful decades. Under the able guidance of skilled trainers and dieticians, the fitness enthusiast could enjoy state of the art gym facilities, in the upcoming mega city of Ahmedabad. Parsana Health Centre Private Limited enjoyed the first mover advantage in Ahmedabad and tapped the fitness club² market through its 13 franchises opened in select vantage locations of the city. It was started by the Parsana brothers: Vijay and Dinesh. They strived hard to inculcate the fitness regime in people and attempted to interweave the benefits of fitness with their occupations. However, the road undertaken threw challenges at them – sometimes from people who failed to underline the importance of fitness in their daily schedule, and sometimes from other fitness brands which emerged as strong competitors. The emergence of many individual and branded fitness chains started making inroads into the busy streets of Ahmedabad and they too worked hard to pull out fitness enthusiasts to these social fitness centres by providing personal health counseling, rejuvenation, yoga, etc. Sustaining competitive advantage became a tough task.

The learning outcomes of this paper are as follows: to identify the pros and cons of waged employment and entrepreneurship, to identify the contextual factors influencing entrepreneurship, to set up a new venture, namely, steps, challenges involved and decision-making process, to scale up a small business; when, how and where? And to tradeoff required for scaling up a small business.

Pooja, a young management graduate from Varanasi, decided to overcome all challenges and barriers faced by a women entrepreneur and chase her lifelong dream of creating her own event management startup. After having achieved phenomenal success in a short period of time within the city, she began to receive interest from neighbouring cities as well. The decision to scale up operations was particularly difficult for Pooja, as she had funded the venture through her personal funds and personally nurtured the business and her team based on the values of quality and creativity. Like any small business, she had to decide what level of trade-off was required between scaling and dilution of control over the operations.

The case study is applicable for students of management. The learnings from the case can be applied by an individual who is looking to start a business or expand one.

Teaching Notes are available for educators only.

CSS 3: Entrepreneurship.