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A comprehensive survey on machine learning techniques to mobilize multi-camera network for smart surveillance
Deploying a web of CCTV cameras for surveillance has become an integral part of any smart citys security procedure. This, however, has led to a steady increase in the number of cameras being deployed. These cameras generate a large amount of data, which needs to be further analyzed. Our next step is to achieve a network of cameras spread across a city that does not require any human assistance to detect, recognize and track a person. This paper incorporates various algorithmic techniques used in order to make surveillance systems and their use cases so as to enable less human intervention dependent as much as possible. Even though many of these methods do carry out the task graciously, there are still quite a few obstructions such as computational resources required for model building, training time for the models, and many more issues that hinder the process and hence, constrain the possibility of easy implementation. In this paper, we also intend to shift the paradigm by providing evidence toward the use of technologies like Fog computing and edge computing coupled with the surveillance technology trends, which can help to achieve the goal in a sustainable manner with lesser overheads. 2023, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature. -
A multi-model unified disease diagnosis framework for cyber healthcare using IoMT-cloud computing networks
The past several decades of research into machine learning have been of great assistance to humanity in the diagnosis of a variety of ailments using various forms of automated diagnostic procedures. Machine learning, combined with smart health devices, has improved health monitoring, timely diagnoses, and treatment. This paper introduces a unified disease diagnosis framework, integrating cloud computing, machine learning, and IoT. The framework has three layers: physical (collects patient data), fog (intermediate layer with a domain identification unit to determine input and diagnosis type), and transmission (cloud server with a disease detection unit). The performance evaluation shows the robustness and efficiency of the model as compared to state-of-art models. 2023, Taru Publications. All rights reserved. -
Stacked LSTM and Kernel-PCA-based Ensemble Learning for Cardiac Arrhythmia Classification
Cardiovascular diseases (CVD) are the most prevalent causes of death and disability worldwide. Cardiac arrhythmia is one of the chronic cardiovascular diseases that create panic in human life. Early diagnosis aids physicians in securing life. ECG is a non-stationary physiological signal representing the heart's electrical activity. Automated tools to detect arrhythmia from ECG signals are possible with Machine Learning (ML). The ensemble learning technique combines the power of two or more classifiers to solve a computational intelligence problem. It enhances the performance of the models by fusing two or more models, which extremely increases its strength. The proposed ensemble Machine learning amalgamates the potency of Long Short-Term Memory (LSTM) and ensemble learning, opening up a new direction for research. In this research work, two novel ensemble methods of Extreme Gradient Boosting-LSTM (EXGB-LSTM) are developed, which use LSTM as a base learner and are transformed into an ensemble learner by coalescing with Extreme Gradient Boosting. Kernel Principal Component Analysis (K-PCA) is a significant non-linear dimensionality reduction technique. It can manage highdimensional datasets with various features by lowering the dimensionality of the data while retaining the most crucial details. It has been applied as a preprocessing step for feature reduction in the dataset, and the performance of EXGB-LSTM is tested with and without K-PCA. Experimental results showed that the first method, fusion of EXG-LSTM, has reached an accuracy of 92.1%, Precision of 90.6%, F1-score of 94%, and Recall of 92.7%. The second proposed method, KPCA with EXGB-LSTM, attained the highest accuracy of 94.3%, with a precision of 92%, F1-score of 98%, and Recall of 94.9% for multi-class cardiac arrhythmia classification. (2023), (Science and Information Organization). All Rights Reserved. -
Perception vs. reality: Analysing the nexus between financial literacy and fintech adoption
Fintech has revolutionized the financial services sector, fundamentally transforming how individuals and businesses manage their finances. However, effective and responsible utilization of these innovative services may require a certain degree of financial competence. To explore this possibility, this study investigates the nexus between financial literacy and fintech usage in the Indian context, considering two distinct measures of financial literacy. Primary data were collected conveniently from 391 respondents through a cross-sectional survey. Probit regression was applied to analyze the relationship between the two dimensions of financial literacy and the adoption of fintech services across three segments: mobile banking, mobile payments, and digital lending. The findings reveal a positive relationship between individuals subjectively perceived financial literacy and their propensity to use all three fintech services. Conversely, objectively measured financial literacy demonstrates a positive association only with the likelihood of using mobile banking. The study also identifies demographic characteristics as contributing factors to variations in fintech adoption. The studys findings hold value for policymakers and fintech service providers, as they underscore the importance of enhancing individuals subjective perceptions of their financial abilities to promote wider adoption of fintech services. Shamli Prabhakaran, Mynavathi L., 2023. -
SCSLnO-SqueezeNet: Sine Cosine-Sea Lion Optimization enabled SqueezeNet for intrusion detection in IoT
Security and privacy are regarded as the greatest priority in any real-world smart ecosystem built on the Internet of Things (IoT) paradigm. In this study, a SqueezeNet model for IoT threat detection is built using Sine Cosine Sea Lion Optimization (SCSLnO). The Base Station (BS) carries out intrusion detection. The Hausdorff distance is used to determine which features are important. Using the SqueezeNet model, attack detection is carried out, and the network classifier is trained using SCSLnO, which is developed by combining the Sine Cosine Algorithm (SCA) with Sea Lion Optimization (SLnO). BoT-IoT and NSL-KDD datasets are used for the analysis. In comparison to existing approaches, PSO-KNN/SVM, Voting Ensemble Classifier, Deep NN, and Deep learning, the accuracy value produced by devised method for the BoT-IoT dataset is 10.75%, 8.45%, 6.36%, and 3.51% higher when the training percentage is 90. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Antecedents of brand love leading to purchase intention towards refurbished video game consoles
This paper examines different constructs that influence purchase intention of refurbished video game consoles to assess its multi-factorial association with brand love. The data was collected from video game console cafes in the cities of Bangalore and Pune, India. The findings demonstrate that adoption determinants and social influence have a positive influence on brand love, while notably, environmental involvement has a positive influence on an individuals purchase intention. Brand love would not singularly influence positive purchase intention in the context of refurbished video game consoles. The paper clarifies that brand love alone cannot influence the purchasing decision of an individual in the context of refurbished video game consoles, the companies selling or remanufacturing these products can benefit by advertising these products as being environmentally involved. This is the first paper that examines the effects of brand love and purchase intentions in the context of refurbished video game consoles. Copyright 2023 Inderscience Enterprises Ltd. -
Total Global Dominator Coloring of Trees and Unicyclic Graphs
A total global dominator coloring of a graph G is a proper vertex coloring of G with respect to which every vertex v in V dominates a color class, not containing v and does not dominate another color class. The minimum number of colors required in such a coloring of G is called the total global dominator chromatic number, denoted by Xtgd (G). In this paper, the total global dominator chromatic number of trees and unicyclic graphs are explored. 2023 University of Baghdad. All rights reserved. -
Examining the facilitators of I4.0 practices to attain stakeholders collaboration: a circular perspective
The fourth industrial revolution (I4.0) has changed the traditional business model, bringing various benefits, including increased efficiency and productivity in organizations. However, to attain success in I4.0 practices requires collaboration from various stakeholders. This study objectives to identify the facilitators of I4.0 practices that can lead to successful collaboration among stakeholders from a circular perspective. An extensive literature review is performed to identify 14 potential facilitators. Further, the study adopts a mixed methodology of Best-Worst Method (BWM) and Interpretive Structural Modeling (ISM) to analyze the interconnectedness among the identified facilitators. BWM method was used to determine the relative importance of the identified facilitators, while ISM technique was used to determine the relationships between the facilitators of I4.0 practices. The findings from the study reveal that to strengthen stakeholder collaboration, organizations need to focus more on training and capacity-building programs and create more opportunities for technology exchange. 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Enhancement of Agriculture Feeder Performance by Optimal Sizing and Placing of Solar PV Tree through AEO-Based Optimization Technique
Electrical demand, which makes up a large share of the overall power market, agriculture at the top of the list of priorities. To provide end users with a dependable and high-quality supply via various feeders and renewable energy sources, distribution generations are now being developed. In recent years, solar PV systems have been used to meet the demands of numerous applications, including boosting the efficiency of distribution networks. This paper presents the system with effect ive optimization method like Artificial Eco-System based Optimization Technique for identification of the best location to install distribution generation and the optimum size to minimize feeder losses. To meet service expectations, the integration of a solar PV system is swapped out for a solar tree in this suggested work. A 28-bus Indian agriculture feeder is considered for better understanding the proposed algorithm. MATLAB software is used for implementing the proposed optimization technique and CREO-2.0 is used for designing the 3-dimensional solar PV tree. 2023 by the Kamal Kumar U and Varaprasad Janamala. -
Floral waste as a potential feedstock for polyhydroxyalkanoate production using halotolerant Bacillus cereus TS1: optimization and characterization studies
The versatile properties and high degree of biodegradability of polyhydroxyalkanoates (PHA) have made them the ideal candidate for biomedical and other applications. Although extensive research on PHA-producing bacterial isolates from terrestrial environments is documented in the available literature, the potential of marine bacterial isolates in PHA production remains less explored and offers a great scope for future research. This research work primarily focuses on isolation and characterization of PHA-producing bacterial isolates from samples collected from coastal areas of Kerala, India. Furthermore, the possibility of PHA production from the most potential isolate Bacillus cereus TS1 using jasmine waste hydrolysate-based media was explored in this study. The utilization of floral waste hydrolysate (FWH) for PHA fermentation is not widely discussed in the available literature and is the major novelty factor of this research work. Under optimized conditions of glucose (1.2% w/v), yeast extract (0.15% w/v), NaCl (5.02% w/v), and incubation period (60h), a maximum PHA yield of 1.13g/L was achieved. The characterization of PHA polymer was done using Fourier transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR), X-ray diffraction (XRD) and thermogravimetric analysis (TGA). Thus, this research work integrates floral waste valorisation with microbial biopolymer production and highlights an innovative approach for sustainable development. The scale of this method on an industrial scale in future may prove helpful in the cost-effective production of PHA using cheap raw materials. Graphical Abstract: [Figure not available: see fulltext.]. 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Novel biocompatible zinc oxide nanoparticle synthesis using Quassia indica leaf extract and evaluation of its photocatalytic, antimicrobial, and cytotoxic potentials
Prognostic research points to the necessity and relevance of revamping polluted environments. The toxic effect of textile dyes released into waterbodies can be reduced by the degradation process and alternate methods in nanotechnology are used to lessen the gravity of the situation. Compared with chemical and physical NP synthesis, plant extract-based nanoparticle synthesis is an environmentally friendly alternative method, and the use of waste leaves in this process is an added advantage. Quassia indica zinc oxide nanoparticles (QI-ZnO NPs) were synthesised in the current work employing a simple and cost-effective process using Q. indica leaf extract. The surface plasmon peak was visible in the UV-Vis absorption spectrum of the decreased reaction mixture at 346 nm. The average crystallite size of the QI-ZnO NPs was found to be 16.66 nm. The QI-ZnO NPs were found to have a stable zeta potential of ?28.4 mV. The surface morphology of the optimised QI-ZnO NPs was observed to be hexagonal using field emission scanning electron microscopy and high-resolution transmission electron microscopy. Under UV light irradiation, the photocatalytic degradation of industrial textile dyes Reactive Blue-220, Reactive Yellow-145, Reactive Red-120, and Reactive Blue-222 showed degradation efficiency of 8090%. Antibacterial and antifungal activity was assessed using well diffusion on gram-positive and gram-negative microorganisms. When administered to the A549 and MDA-MB-231 cancer cell lines, QI-ZnO NPs displayed significant anticancer activities. Limited studies in the area of plant extract-based nanoparticle synthesis mark the novelty of this attempt and this trailblazing and pioneering approach using non-toxic QI-ZnO NPs synthesised through green synthesis is futuristic and sustainable helping in effective wastewater treatment. Graphical abstract: [Figure not available: see fulltext.] 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Basic human values of Indian management professionals: a demographic profile
This study tries to check the degree of basic human values among management professionals in India with considerable cultural and linguistic differences and how it varies across the different demographic influences. We have checked the impact of demographic variables like gender, age, education, type of organisation, place of residence, and work experience on basic human values. Hypotheses testing were conducted using MANOVA. It was inferred that the perception regarding the degree of basic human values differs among different management professionals based on their age, gender, education, type of organisation, and place of residence. Surprisingly, the work experience of the person does not have a significant influence on basic human values. Consequently, we imply that the demographics of an individual carve their basic human values. The findings and inferences of the proposed study will be of great importance to policymakers and recruiting managers to fetch the right candidate. Copyright 2023 Inderscience Enterprises Ltd. -
Determinants of Book Built IPO underpricingdifferential issue size and market momentum approach revisited
Pricing of an Initial public offering (IPO) is a complex phenomenon. Price anomalies are commonly observed in IPO markets, especially in emerging markets. Investors perceived underpricing creates undue market momentum during the offer period with an asymmetric effect across different issue sizes. This study examines the determinants of Book Built IPOs underpricing by considering a sample of 180 Book Built IPOs that went public in India between 2011 and 2020. The determinants were verified for differential issue size public offers. Listing day performance was measured using Listing Day-Absolute Return (LD-AR) and Listing Day-Market Adjusted Return (LD-MAR) models. Further, the data obtained was tested for the explanatory capabilities of firm-specific and market momentum factors for underpricing using OLS models. Concerning the differential issue size, the study found a direct relationship between the issue size and underpricing. Dominant underpricing was observed in the case of moderate to large issue size with a linear progressive return, confirming that there was over-optimism on the part of investors. The studys results also revealed that momentum-specific factors have a significant influence along with firm-specific factors such as firm size, cash flows, a subscription rate of QIBs and RIIs in the listing day return, and underpricing. 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Effect of heavy metals on the pigmentation and photosynthetic capability in Jacobaea maritima (L.) Pelser & Meijden
Photosynthesis is a fundamental process in plants that enables them to produce their own food. However, this process can be influenced by multiple factors including external factors such as sunlight, nutrients availability and gas concentrations. The present study aimed to investigate the effects of heavy metal stress on the plant Jacobaea maritima (L.) Pelser & Meijden. Three different heavy metals, namely cadmium, chromium, and lead, were applied to the plants at five concentrations ranging from 50-250 ppm (50, 100, 150, 200, and 250). The growth of the plants was observed, and several parameters including net photosynthetic rate (Pn), transpiration rate (E), leaf stomatal conductance (C), and the photosynthetic active radiation (PAR) were measured. The results revealed that the chlorophyll content was higher in the Cr150 concentration (5.470.4). The chlorophyll values for Pb-100 (9.40.35) and Pb-250 (9.80.26) were in close proximity to each other. The Cd-100 concentration showed the highest chlorophyll content. The net photosynthetic rate was least affected in Pb-150 (30.980.75), while Cr-100 (4.050.09) exhibited the greatest impact. Transpiration rate increased slightly in plants treated with Pb, but significantly decreased in Cd-treated plants. The Cr-50 concentration (0.190.02) showed the lowest transpiration rate. Leaf stomatal conductance was reduced significantly in all treated plants, with Cr-100 showing the least variation (2298.251.85). The photosynthetic active radiation capability was reduced in all treated plants, with Pb-treated plants exhibiting nominal reduction and Cd- and Cr-treated plants experiencing substantial reduction. Statistical analysis confirmed significant variations in the measured parameters following heavy metal treatment. 2023 The Author(s) -
Adapting Employee Engagement Strategies Amid Crisis: Insights from the COVID-19 Pandemic
Crises are unpredictable events that have the potential to strike at any moment, causing significant disruptions to work, daily routines, and the normal course of life. The COVID-19 Pandemic served as a facilitator for transformative changes in the way we work, shifting to an era of remote and flexible work arrangements across industries. This crisis underlined the importance of employee engagement and organizational culture-building in navigating unforeseen situations. As organizations prepare for the future, it becomes crucial to anticipate and adapt to potential crises that may arise. The effect of the pandemic varied from industry to industry. When the technology industry worked towards creating a virtual workspace, the production industry strived to continue production without disruption. However, irrespective of the industry, HR teams across the board were dedicated to identifying and addressing the challenges posed by the crisis. They have worked tirelessly to ensure employee engagement remains a priority. This qualitative study explores the challenges encountered by HR teams during the pandemic and explores the strategies and policies they adopted to foster employee engagement. The data was collected through an in-depth interview with 39 HR Practitioners from different industries. The significant challenges included the need to cultivate a sense of community, navigate muddled up HR processes, sustain productivity amid disruptions, and prioritize employee wellness. To provide a comprehensive analysis, this study examined industry-specific approaches, employing within-case analysis to understand key strategies in communication, rewards and recognition, employee benefits, wellness initiatives, and fostering an enjoyable virtual workplace. This study offers a forward-looking perspective and serves as a guide for organizations aiming to thrive in times of uncertainty, ensuring that employee engagement remains a strategic priority regardless of the crisis at hand. 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
SCN1A Genetic Alterations and Oxidative Stress in Idiopathic Generalized Epilepsy Patients: A Causative Analysis in Refractory Cases
Single Nucleotide Polymorphisms (SNPs) have found it be associated with drug resistance in epilepsy. The purpose of this study was to determine the role of SCN1A gene polymorphism in developing drug resistance in idiopathic generalized epilepsy (IGE) patients, along with increased oxidative stress. The study was conducted at a tertiary care hospital in Delhi, India. We recruited 100 patients diagnosed with IGE patients, grouped as drug-resistant and drug-responsive, and then further compared the SCN1A SNP rs10167228 A*/T analysis between the two groups. We utilized the PCR-RFLP technique to investigate the association between polymorphisms and refractory epilepsy. Serum HMGB1 levels were estimated using the ELISA technique to analyze oxidative stress in both groups. rs10167228 A*/T polymorphism genotypes AT and AA genotypes are significantly associated with an increased risk of developing drug resistance. Serum HMGB1, IL-1?, and IL-6 levels were significantly higher in drug-resistant cases, compared to the drug-responsive group. The association of SCN1A gene polymorphisms, in conjunction with raised oxidative stress, may be predictive of the development of drug-resistant epilepsy. The AT and AA genotypes of rs10167228 may pose a risk factor for developing drug-resistant epilepsy. 2023, The Author(s), under exclusive licence to Association of Clinical Biochemists of India. -
Local post-hoc interpretable machine learning model for prediction of dementia in young adults
Dementia is still the prevailing brain disease with late diagnosis. There is a large increase in dementia disease among young adults. The major reason is over indulgence of young adults on social media resulting in denial of disease and delayed clinical diagnosis. Dementia is preventable and curable if diagnosed at an early stage, however, no attempts are being made to mitigate dementia in young adults. Today artificial intelligence (AI) based advanced technology with real-life consultations in clinical or remote setups are proved beneficial and is used to detect dementia. Most AI-based test is dependent on computer-aided diagnosis (CAD) tools and uses non-invasive imaging technology such as magnetic resonance imaging (MRI) data for disease diagnosis. In this paper, a local post-hoc interpretable machine learning (LPIML) model for prediction of dementia in young adults is proposed. The performance parameters are computed and compared based on accuracy, specificity, precision, F1 score and recall. The proposed work yields 98.87% training accuracy on original images and 99.31% training accuracy on morphologically enhanced images. The performance results are intrinsic and intuitive in learning the prediction results of individual case. The adoption of the proposed work will accelerate the diagnosis process in the era of digital healthcare. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Mamaearth: from a mothers dilemma to a multi-crore brand
Learning outcomes: The case study has several objectives: to gauge the evaluation of the direct-to-consumer industry in the economy of India, to analyse the competition of the brands, to ascertain the evolution of smaller direct-to-consumer (DTC) brands on the purchasing capacity of consumers, to analyse challenges in branding in Tier 2 and 3 cities and to evaluate the strategic branding decisions of Mamaearth. Case overview/synopsis: During her pregnancy, Ghazal Alagh and her husband Varun Alagh, the co-founders of Mamaearth, were looking for some good and natural products for their babys skincare. However, she could not find products that were 100% safe. Hence, as a concerned mother, she started using a few hands-on home remedies for her baby, which were 100% organic, and then the idea clicked to her to start a baby care brand named Mamaearth, which later also included personal care products. The company started as a DTC/internet-first brand in 2016, which only used to sell products online without any intermediaries when it was still trying to make its way in the market and was aware of the stiff competition by giants such as Hindustan Unilever and Proctor & Gamble, who were ruling the market for decades. When the COVID-19 pandemic hit, the market saw a shift in consumer buying patterns. There was greater use of e-commerce touch points for shopping, as various digital platforms such as the official site of products, social media and mobile platforms were used by consumers during the pandemic, leading to digitalization in buying and digitalization of consumer shopping journey. These technology platforms were expected to play a substantial role in reaching and creating consumer awareness, transaction and retention post-COVID according to reports by Deloitte 2020. Moreover, such a shift in behaviour amidst the COVID-19 pandemic shot up sales of this DTC brand and made itself the big shot it is today, where they were looking to get into an initial public offering in just seven years of its launch. They re-evaluated their strategy, which helped them become the biggest brand in no time. Complexity academic level: This case study is suitable for Doctor of Philosophy students. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 8: Marketing. 2023, Emerald Publishing Limited. -
Thermal fatigue characteristics of 8Y2O3-ZrO2, La2Zr2O7, La2(Zr0.7Ce0.3)2O7 and La2Ce2O7 thermal barrier coatings in duplex, multilayer functionally graded and multilayer configurations
La2Zr2O7, La2(Zr0.7Ce0.3)2O7 and La2Ce2O7 pyrochlore plasma sprayable powders were synthesized and plasma spray coated on steel plates with NiCrAlY bond coat. Three different configurations were used: duplex, multilayer functionally graded and multilayer, with different combinations of commercial 8% yttria stabilized zirconia (8YSZ) and NiCrAlY (bond coat) layers. The prepared coatings were compared with the standard duplex 8YSZ thermal barrier coatings (TBCs) with a goal to study their suitability to serve as TBCs. TBCs layer thicknesses and interfaces were studied via SEM on polished cross section metallographic samples removed from the spray coated TBCs. Thermal fatigue resistance was evaluated by directing a gas flame on the ceramic surface at 1200 and 1400 C, followed by its rapid withdrawal and forced cooling by pedestal fan. The maximum number of thermal shock cycles the coatings could withstand before failure was determined. The multilayered TBCs with lanthanum cerate composition stacked with 8YSZ exhibited the superior thermal fatigue resistance characteristics compared to all other studied TBCs. The findings were correlated with the crystalline phases of the ceramic coatings, obtained via XRD, and discussed in the light of existing literature. 2023 University of Novi Sad, Faculty of Technology. All rights reserved. -
From the local to the global: the journey of Suguna Foods
Learning outcomes: On completion of this case study, students will be able to understand collaboration and synergy between farmers and organisations through value creation, like fundraising, based on the comprehension of the resource-based theory; understand the overview and concept of the value chain and supply chain management in the agribusiness to reduce costs of inventories; understand the concept of segmentation and positioning to increase revenue for organisations by leveraging existing resources human and financial; and understand the branding strategy to create a sustainable competitive advantage for Suguna Foods. Case overview/synopsis: Suguna was started by two brothers, B. Soundararajan and G.B. Sundararajan, to help other farmers. Suguna, with just 200 broilers in 1984, grew to be the number 1 poultry company across India. Soundararajan was a pioneer and innovator who started contract farming in India in 1991. This model helped both the farmers and the company to became successful. The farmers always struggled to pay the cost of feed and other materials, as credit was not readily and easily available from financial institutions. Suguna helped farmers by providing feed, medicines, etc., free of cost in return for the good rearing of chickens. Because of the success of this venture, they decided to continue with it. Today, Suguna is a successful company that sells chicken, eggs and processed meat. They modernised the retail chain to supply consumers with fresh, healthy and hygienic meat. Sugunas vision was to Energize rural India by helping farmers succeed. They helped over 40,000 farmers from 15,000+ villages in 18+ Indian states. Although the growth helped both farmers and Suguna, the increased cost of raw materials for Suguna and increased input costs/power costs for farmers had to be tackled on a war footing so that both could have good income despite the increased inflation. Moreover, the retail price of live chicken was more or less stagnant in the past five years, especially after the start of the COVID-19 pandemic. Complexity academic level: This case can be used as the basis for a 90-min class discussion. This case study is suitable for use in an master of business administration course module or in an executive education program on developing an understanding of value creation in the business model in a rural market and also how the supply chain works. This case study can also be used to teach pricing, segmentation in marketing and supply chain perspectives and decision-making skills. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS8: Marketing. 2023, Emerald Publishing Limited.