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Indigenous knowledge is an essential element for unveiling the evolutionary journey of socio-culture phenomena. One of the key challenges in foresight exercises is to incorporate social-culture issues such as culture, lifestyle and behavior (referred as indigenous knowledge) into the study. However, the statistical trends of those factors tend to be either not available or limited unlike the population or economic related factors. The purpose of this study is to present the use of valuable data from indigenous knowledge to enhance the foresight exercise through the better understanding of social dynamics and changes.

The fragmented form of indigenous knowledge is analyzed and converted into a structured data format and then interpreted to unveil the evolutionary journey of socio-cultural phenomena. This study applies a scenario development method to visualize the results of foresight by comparing before and after the integration of indigenous knowledge. Finally, an assessment was conducted to reflect the value enhancement resulting from the integration of indigenous knowledge into the foresight process.

With the proposed approach, the foresight study on the future development of Thai food was demonstrated. The findings of this study show that the use of indigenous knowledge on eating behavior, cooking style and food flavor helps improve the alternative scenarios for the future development of Thai foods.

Indigenous knowledge can be applied to develop plausible scenarios and future images in foresight exercises. However, by nature, indigenous knowledge is not well-structured and, therefore, needs to be analyzed and turned into structured data so that it can be interpreted before integrating into the foresight process.

This study is one of few studies addressing the opportunities for integrating indigenous knowledge into foresight process. Indigenous knowledge can unveil the evolution of socio-cultural changes to improve the results of foresight study, especially the cases where statistical data and trends may not be sufficient to foresee future development.

The purpose of this study was to explore the potential benefits of Coriandrum sativum (C. sativum) on anxiety, depression, sleep quality and memory among students.

This randomized controlled trial involved university students aged 18–25 years, who had no known allergies to C. sativum or were using psychotropic medication. After giving informed consent, participants were randomly assigned using a computer-generated random sequence to either 500 mg C. sativum seeds or a placebo. Primary outcomes measured changes in memory (prospective and retrospective memory questionnaire [PRMQ]), anxiety and depression (Hospital Anxiety and Depression Scale), while secondary outcomes assessed sleep quality (Pittsburgh sleep quality inventory [PSQI]).

A sample of 86 students with a mean age of 20.05 ± 1.6 years was selected for the study. Initial assessments ensured no significant differences in demographic or study variables between the control and intervention groups. Statistical analysis revealed significant improvements in memory (PRMQ: p = 0.006), anxiety (Hospital Anxiety Scale: p = 0.04) and depression (Hospital Depression Scale: p = 0.002), as well as in sleep quality (PSQI: p = 0.03) in the group receiving C. sativum compared to the control group.

This research offers initial insights into the potential benefits of C. sativum intake, specifically its role in enhancing memory performance and mitigating anxiety among student populations. The results present a compelling case for further research in this domain to solidify these preliminary conclusions.

Packaging design has the power to convey persuasive and functional benefits, thereby inducing the brand preference as per empirical studies, but not much has been studied in detail about aesthetic aspects of packaging. This study is a careful attempt to understanding the influence of aesthetic elements—colour, illustrations/images/pictures and information representation’s influence on consumer brand preference for ready-to-eat (RTE) product category of pav bhaji.

The data for this study have been collected in two phases; phase 1 was a quantitative research where structure Google form was used while in order to elite consumer responses regarding their preferences structured interview was conducted in phase 2. Twenty-five respondents were selected using snowball sampling, who were approached for understanding how aesthetic element influenced their brand preference.

This research could help in identifying various underlying subthemes within the three major themes of aesthetic element in packaging. By utilising these, packaging modifications could be made to increase brand preference.

In case of RTE segment, in-store decisions are mostly take in spurn of minutes, hence making it one of essential topics of research. The findings of this research can contribute in placement of correct element in appropriate position to grab consumers’ interest leading to brand preference.

Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of agricultural products. Pesticides can be used to improve agricultural land products. This study aims to make the spraying of cherry trees more effective and efficient with the designed artificial intelligence (AI)-based agricultural unmanned aerial vehicle (UAV).

Two approaches have been adopted for the AI-based detection of cherry trees: In approach 1, YOLOv5, YOLOv7 and YOLOv8 models are trained with 70, 100 and 150 epochs. In Approach 2, a new method is proposed to improve the performance metrics obtained in Approach 1. Gaussian, wavelet transform (WT) and Histogram Equalization (HE) preprocessing techniques were applied to the generated data set in Approach 2. The best-performing models in Approach 1 and Approach 2 were used in the real-time test application with the developed agricultural UAV.

In Approach 1, the best F1 score was 98% in 100 epochs with the YOLOv5s model. In Approach 2, the best F1 score and mAP values were obtained as 98.6% and 98.9% in 150 epochs, with the YOLOv5m model with an improvement of 0.6% in the F1 score. In real-time tests, the AI-based spraying drone system detected and sprayed cherry trees with an accuracy of 66% in Approach 1 and 77% in Approach 2. It was revealed that the use of pesticides could be reduced by 53% and the energy consumption of the spraying system by 47%.

An original data set was created by designing an agricultural drone to detect and spray cherry trees using AI. YOLOv5, YOLOv7 and YOLOv8 models were used to detect and classify cherry trees. The results of the performance metrics of the models are compared. In Approach 2, a method including HE, Gaussian and WT is proposed, and the performance metrics are improved. The effect of the proposed method in a real-time experimental application is thoroughly analyzed.

Interviewing the protagonist and collecting information from secondary resources such as company documents, company and competitor websites, industry reports and online databases like Euromonitor International.

The case explores the metamorphosis of JK Masale from a small-scale family business in India to a regional player. Over a period of six decades, JK Masale (JKM) has emerged against the backdrop of a fiercely competitive spice industry. India, being a confluence of varied regional cultures, poses a diverse consumption pattern. It varies to a great extent with respect to the specific food habits prevalent in each climatic zone of the country. While the brand had successfully captured the Eastern Market and the western market of the country, Mr. Vikash Jain, Managing Director of JK Masale, contemplated to venture in Southern India and introduce new product categories. The case delves into one of the major challenges faced by JKM over the brand architecture and labelling across product categories. Thus, the case provides an excellent opportunity for budding managers to: analyse the company’s performance in the backdrop of a dynamic competitive environment; understand the nature of strategic decision-making and its appropriateness for a small family-owned business; evaluate a brand amongst brands on the architectural framework and select appropriate brand architecture for new products; and understand applicability and risks associated with growth strategies.

The case study can be positioned in both undergraduate and postgraduate level programs for courses on marketing strategy and brand management. Primarily, this case would be ideal to discuss brand relationship and brand architecture in the given context. Instructors have an option to cover concepts like market structure, company analysis, growth strategies and emergent and deliberate strategy through the case.

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.

After completion of this case study, students will be able to apply the triple bottom line concept to a spice manufacturing and export company (RBT 3); to examine the options before Value Ingredients Private Limited (VIPL), namely, to cultivate spices in the traditional way versus adopting integrated pest management (IPM) to cater to international markets (RBT 4); to analyse the returns for an IPM farmer vis-à-vis a conventional farmer, and to compare the returns therein (RBT 4); and to evaluate the ways and means of engaging farmers to change their way of cultivation (RBT 5)

The COVID-19 pandemic heightened awareness about the benefits of spices and buoyed its demand worldwide, which presented an opportunity to VIPL, a spice manufacturing company based in Chennai, to expand its business. However, the export markets demanded residue-free spices grown with little or no use of pesticides. Traditional farmers supplying spices to VIPL were accustomed to spraying pesticides whenever there was a pest attack. This case study discussed the options that the protagonist Mr Sijil Karim, managing director and CEO of VIPL, had, who wanted to onboard farmers for pesticide-free cultivation. The options before him were either to continue traditional farming or adopt IPM. This case study discussed the merits, demerits and challenges of each of these options.

The triple bottom line concept discussed three Ps – people, planet and prosperity – for this case as follows: The farmers and the consumers constituted the people in the spice supply chain. The farmers supplying organic, export-worthy spices under the guidance of VIPL gained 30% more than regular spice farmers, which were accrued through cost savings and better prices. The consumers benefitted from the pesticide-free, organic spices through accrued health gains. The manufacture of organic, pesticide-free spices helped the planet, as the process did not release hazardous chemicals into the atmosphere. VIPL manufactured pesticide-free spice with a focus on prosperity.

The case study can be introduced in a course on sustainability while discussing the triple bottom line concept. This case study showed how a for-profit company grew without losing sight of the planet or its focus on people. This case is best suited for students who have preliminary knowledge of supply chain management, operations and sustainability. Therefore, it is suited for sophomore-year students of MBA.

Teaching notes are available for educators only.

CSS 11: Strategy.

This case study will allow students to critically analyse and develop entry strategies into untapped foreign markets. The case study was designed to introduce students to identifying and analysing information related to target markets for expansions in international business.

The main objectives of this case are to evaluate and make the “Go Global” decision for the company; to take a position on entry timing for a company for entering an overseas market; to select a country for entry based on cultural, administrative, geographic and economic analysis and other relevant factors; and to evaluate a firm’s readiness for exports.

This case study on Satya Pharmaceuticals presents a typical dilemma faced by small and medium enterprises (SMEs) in emerging markets such as India while exploring the untapped overseas markets to expand their business. Satya Pharmaceuticals produced over-the-counter Ayurvedic medicines. With the onset of the COVID-19 pandemic, the consumer preference for Ayurvedic products had increased globally. Home country governments’ emphasis on exports and conducive consumer preferences created an opportune time for such SMEs to explore uncharted markets with a propensity for herbal medicines. Amidst strict regulations regarding safety, efficacy, labelling and packaging norms, along with a subjective understanding of the consumers’ sentiments regarding alternate medicines, SMEs had to select their target market carefully for their products to be successful overseas. This case study presents the basic information that entrepreneurs needed to explore the foreign markets. It revolved around checking firms’ preparedness to explore foreign markets, identifying target markets, timing the entry and entering those markets.

This case is appropriate for graduate-level courses in management that offer subjects such as international business.

Teaching notes are available for educators only.

CSS 5: International business.