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The impact of climate change (CC) has become the most defining issue of the present times. From an increase in temperature to food and water scarcity, the adverse effect of CC is faced globally by all countries on an unprecedented level. Environmentally polluting industries are considered one of the primary contributors to the problem of CC. This chapter aims to provide an understanding of the emerging global threat of CC and various strategies that environmentally polluting firms could undertake to tackle the climate change crisis.

Based on the review of the literature, this chapter presents deliberation on the climate change crisis and various strategies for environmentally polluting industries to tackle CC issues.

This chapter presents a bird's eye view of the CC issue and various strategies that could be undertaken by environmentally polluting industries to address the CC crisis.

This chapter should be very useful for policymakers, practitioners and corporations to understand the issue of climate change and global warming and its implications. Further, it will also help polluting companies to reduce greenhouse gas (GHG) emissions and address the adverse impact of their business activities.

Considering the dearth of sector-specific studies based on climate change, this chapter is one of the few studies that explore CC strategies in the context of polluting industries.

This study delves into the multifaceted landscape of online advertising, focusing specifically on the customer perceptions of advertisements from prominent e-commerce platforms, AJIO and Myntra. With a sample size of 137 participants, the research employs robust statistical techniques, including simple percentage analysis and chi-square, to unravel insights embedded within the collected data.

Exploring how customers perceive online advertisements, particularly those originating from AJIO and Myntra, and how these perceptions shape their purchasing decisions, the study underscores the importance of transparent and accurate representation of products and services in online ads to foster trust and confidence among consumers. The study provides insights specifically relevant to AJIO and Myntra customers.

This research adds to the existing understanding of online advertising, presenting insights that hold significance for both advertisers and consumers navigating this complex landscape. With the digital domain continuing its rapid evolution, this study serves as a valuable resource, aiding in comprehending.

This case study aims to familiarize the participants with the functioning of the herbal tea industry in an emerging economy like India; understand core concepts, key terminologies and the business relevance of different types of business forecasting; and execute time series forecasting models using MS Excel and interpreting the results.

This case study unveils an important operational concern faced by Deepshika Das, the production manager at Sri Sai Tea Trading Company located at Cuttack in Odisha, India, about future sales projections. The company was gaining popularity for a unique herbal tea called “Chaa Lemon Tea.” However, the company had been experiencing frequent overstocking and understocking due to inappropriate qualitative forecasting. This case study underscores the importance of the concepts associated with quantitative forecasting. It demonstrates the analysis of time series data, building forecasting models and their interpretations using MS Excel.

This case study can be used as a systematic learning tool for postgraduate business school students and master’s level industrial engineering students. This case study can be discussed in courses such as operations and supply chain management, business statistics and quantitative decision-making.

Teaching notes are available for educators only.

CSS 9: Operations and Logistics.

In the present study, a steel lifting lug is replaced with a composite (carbon fiber-reinforced epoxy [CFRP]) lifting lug made of a carbon/epoxy composite. The purpose of this paper was to obtain a composite lifting lug with a higher level of strength that is capable of carrying loads without failure.

The vibration and static behaviors of steel and composite lifting lugs have been investigated using finite element analysis (FEA), ANSYS software. The main consideration in the design of the composite (CFRP) lifting lug was that the displacement of both steel and composite lugs was the same under the same load. Hence, by using the FEA displacement result of the steel lifting lug, the thickness of the composite lifting lug is determined using FEA.

Compared to the steel lifting lug, the composite (CFRP) lifting lug has much lower stresses and much higher natural frequencies. Static behavior was experienced by the composite lifting lug, showing a reduction in von Mises stress, third principal stress and XZ shear stress, respectively, by 48.4%, 34.6% and 89.8%, respectively, when compared with the steel lifting lug. A higher natural frequency of mode shape swaying in X (258.976√1,000 Hz) was experienced by the composite lifting lug when compared to the steel lifting lug (195.935√1,000 Hz). The safe strength of the design composite lifting lug has been proven by FEA results, which showed that the composite (CFRP) lifting lug has a higher factor of safety in all developed stresses than the steel lifting lug. According to von Mises stress, the factor of safety of the composite lifting lug is increased by 76% when compared to the steel lifting lug. The von Mises stress at the edge of the hole in the composite lifting lug is reduced from 23.763 MPa to 20.775 MPa when compared to the steel lifting lug.

This work presents the designed composite (CFRP) lifting lug, which will be able to carry loads with more safety than a steel one.

This study investigates the moderating effects of consumers’ occupations on their purchase intentions (PIs) for food takeout services using a modified unified theory of acceptance and use of technology model. It evaluates how different occupations influence the relationships between social influence (SI), expectation confirmation (EC), facilitating conditions (FC) and PI.

The study collected data from individuals in various occupations, including technical/associate professionals, executives/professionals, administrative/service workers and manual/operative workers. The data were analyzed using structural equation modeling, while hierarchical analysis assessed how occupation moderated the relationships between latent variables (SI, EC and FC) and PI.

Different occupations have a certain moderating effect on the relationships between SI/EC/FC and PI. For the technical and associate professionals and manual and operative occupations, the moderating effect of FC on PI is stronger than that of EC and SI. For executives and professionals and administrative and service occupations, the moderating effect of EC on PI is stronger than that of SI and FC.

This study provides new insights into how occupational differences influence consumer behavior in the context of online food ordering services. The results expand the application of the unified theory of acceptance and use of technology model and the understanding of the influence of occupation on consumer’ behavior.

The purpose of this study is to investigate the impact of titanium oxide (TiO₂) filler on the abrasive wear properties of bamboo fiber reinforced epoxy composites (BFRCs) using a Taguchi approach. The study aims to enhance the abrasive wear resistance of these composites by introducing TiO₂ filler as a potential reinforcement, thus contributing to the development of sustainable and environmentally friendly materials.

This study focuses on the fabrication of epoxy/bamboo composites infused with TiO₂ particles within the Wt.% range of 0–8 Wt.% using hand layup techniques. The resulting composites were subjected to wear testing according to ASTM G99-05 standards. Statistical analysis of the wear results was carried out using the Taguchi design of experiments (DOE). Additionally, an analysis of variance (ANOVA) was used to determine the influential control factors impacting the specific wear rate (SWR) and coefficient of friction (COF).

The study illuminates how integrating TiO₂ filler enhances abrasive wear in epoxy/bamboo composites. Statistical analysis of SWR highlights abrasive grit size (grit) as the most influential factor, followed by normal load, Wt.% of TiO₂ and sliding distance. Analysis of the COF identifies normal load as the primary influential factor, followed by grit, Wt.% of TiO₂ and sliding distance. The Taguchi predictive model closely aligns with experimental results, validating its reliability. The morphological study revealed significant differences between the unfilled and TiO₂-filled composites. The inclusion of TiO₂ improved wear resistance, as evidenced by reduced surface damage and wear debris.

This research paper aims to integrate TiO₂ filler and bamboo fibers to create an innovative hybrid composite material. TiO₂ micro and nanoparticles show promise as filler materials, contributing to improved tribological properties of epoxy composites. The utilization of Taguchi’s DOE and ANOVA for statistical analysis provides valuable guidance for academic researchers and practitioners in optimizing control variables, especially in the context of natural fiber reinforced composites.

The purpose of this paper is to identify the challenges surrounding the implementation of digital technology (DT) agri-food supply chain (AFSC) and explore how these challenges relate to the various sustainability dimensions. Additionally, it aims to assess how these challenges are interconnected in relation to achieving sustainable development goals (SDGs).

The study employs a mixed-method approach utilizing the EFA-ISM-Fuzzy DEMATEL technique. To support and validate the findings, exploratory factor analysis (EFA) categorized 12 critical challenges in sustainable dimensions from 141 participants' responses. Furthermore, interpretive structural modeling (ISM) and decision-making trial and evaluation (DEMATEL) methods were used to obtain the interrelationship and hierarchical structure of the challenges.

The study identified 12 critical challenges while adopting DT in AFSC. These challenges were categorized into four sustainable dimensions: technological, economic, environmental and social. These challenges hinder the achievement of SDGs as well. Lack of regulatory and policy framework with security and privacy issues were the key challenges faced while adopting DT. These observations emphasize the necessity for government and policymakers to prioritize tackling the identified challenges to successfully endorse and execute DT initiatives in AFSC while also fulfilling the SDGs.

The implication underscores the need for collaboration among various stakeholders, such as governments, policymakers, businesses and researchers. By collectively addressing these challenges, DT can be leveraged optimally, fostering sustainable practices and making progress toward achieving the SDGs within the AFSC.

The study uses a combination technique of EFA and ISM-DEMATEL to identify the challenges faced in Indian AFSC while adopting DT and categorizes the interrelation between the challenges along with fulfilling the SDGs.

The study examines the production, operational, technological, environmental, economic and financial risks affecting agribusinesses. The primary objective is to identify and prioritise the barriers to the humanitarian system's operational dynamics that focus on indemnifying the farmers' income in India.

The integrated interpretive structural modelling (ISM)-fuzzy analytical network process (FANP) approach systematically analyses the dynamic interrelationships among barriers, offering a comprehensive framework for agribusiness risk management. The barriers are identified by synthesising literature with the PSALSAR framework. The 18 barriers are clustered into five groups based on phases: planning, designing, execution, implementation and disbursement. The ISM constructs structural hierarchies to identify the interactions among these barriers, while FANP quantifies and establishes the interlinkages between them.

The proposed model's results reveal that “Skewed Stakeholder Engagement and Data-Deficient Ecosystem” are the most severe barriers to the humanitarian system's operational dynamics. By highlighting the significance of these obstacles, the study contributes to a targeted approach for optimizing resource allocation and enhancing the resilience of humanitarian operations.

Findings enable decision-makers to design more effective interventions and improve operational workflows, particularly essential in contexts with limited resources and pressing time constraints. The study suggests collaboration between humanitarian organisations, governments and stakeholders in developing strategies for addressing barriers.

The study investigates barriers to the dynamic settings of humanitarian operations within the agricultural sector. The research employs a novel approach to analysing the barriers across the various phases of the humanitarian system operating in distinct political, environmental and social settings.