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Prior research studies have discussed the role of corporate social responsibility (CSR) during crisis situations in increasing the resilience and sustainability of the companies. There are two basic models of crisis management – reactive and proactive. When a crisis occurs, suddenly firms tend to act reactively and progressively take proactive steps to manage the crisis. CSR can also be reactive and proactive during crisis situations. Against this backdrop, this paper aims to explore whether CSR during the COVID-19 pandemic moved from a reactive to a proactive stance, with specific focus on CSR legislation, corporate CSR response and corporate thinking about CSR.

This paper adopts a mixed methods approach, using both qualitative and quantitative research designs. This study draws upon both primary and secondary data.

The results highlighted the change in the CSR approach from being reactive to being proactive as the pandemic progressed. This was observed through the increase in frequency of CSR legislation, and the shift in the intent of CSR legislation from “prompting to donate” to “prompting to volunteer.” Similarly, the shift in reactive to proactive CSR corporate response was observed through the increased spending on CSR and improved COVID-related CSR reporting.

This study recommends companies to manage crises by becoming more proactive. CSR activities need to be closely aligned with national developmental objectives, and collaborate with various stakeholders to achieve the intended outcomes of the activities.

To the best of the authors’ knowledge, this research paper is one of the few to study the impact of COVID-19 pandemic on CSR in India at a time when India went through three waves of the pandemic. This study corroborates with other studies in terms of managing crisis.

Better membrane oxygenators need to be developed to enable efficient gas exchange between venous blood and air.

Optimal design and analysis of such devices are achieved through mathematical modeling tools such as computational fluid dynamics (CFD). In this study, a control volume-based one-dimensional (1D) sub-channel analysis code is developed to analyze the gas exchange between the hollow fiber bundle and the venous blood. DIANA computer code, which is popular with the thermal hydraulic analysis of sub-channels in nuclear reactors, was suitably modified to solve the conservation equations for the blood oxygenators. The gas exchange between the tube-side fluid and the shell-side venous blood is modeled by solving mass, momentum and species conservation equations.

Simulations using sub-channel analysis are performed for the first time. As the DIANA-based approach is well known in rod bundle heat transfer, it is applied to membrane oxygenators. After detailed validations, the artificial membrane oxygenator is analyzed for different bundle sizes (L/W) and bundle porosity (epsilon) values, and oxygen saturation levels are predicted along the bundle. The present sub-channel analysis is found to be reasonably accurate and computationally efficient when compared to conventional CFD calculations.

This approach is promising and has far-reaching ramifications to connect and extend a well-known rod bundle heat transfer algorithm to a membrane oxygenator community. As a variety of devices need to be analyzed, simplified approaches will be attractive. Although the 1D nature of the simulations facilitates handling complexity, it cannot easily compete with expensive and detailed CFD calculations.

This work has high practical value and impacts the design community directly. Detailed numerical simulations can be validated and benchmarked for future membrane oxygenator designs.

Future membrane oxygenators can be designed and analyzed easily and efficiently.

The DIANA algorithm is popularly used in sub-channel analysis codes in rod bundle heat transfer. This efficient approach is being implemented into membrane oxygenator community for the first time.

The learning outcomes of this case study are to understand the business model canvas and value propositions and apply advanced business innovation tools in electric vehicle business models; evaluate the current cargo vehicle scenarios at national and global levels and draw out the possibilities and costs for a new player; extrapolate the future scenario of the cargo economy, its electrification and positioning in a business-to-business (B2B) and business-to-customer (B2C) segment, especially for a developing economy; and improve the student’s ability to get organisational buy-in and execute new business models.

LoadExx is a fully electrified electric cargo service focusing on logistics in Kolkata, a metropolitan city in the eastern part of the country. The service of LoadExx commenced in January 2021 in the B2B segment after overcoming its then issues of driver hesitancy and customer anxiety and financial issues to adopt electrified cargo systems. The conundrum faced by LoadExx in its commencement thus had been solved under the able guidance of its owner Amit Arora. The case study was positioned four months after the commencement of LoadExx. To gain market power and traction, Arora and his team came up with the idea of market expansion. However, the current conundrum was whether LoadExx would enter the B2C segment in its current location or expand with the same business model to other parts of the country. The expansion was to be implemented in the immediate future to retain its rarity and reduce the imitability of the business model of LoadExx. This case study details the logistics and market operations of the cargo sector, especially electric cargo, in a developing economy, especially India. A teaching note supplementing the “Cracking the conundrum of e-cargo logistics: curious case of LoadExx” case study has been provided.

This case study is designed for undergraduate and postgraduate students and senior management professionals in executive education programmes undertaking courses in logistics management and supply chain operations and related cargo logistics courses. This case study denotes integrating key processes from end-users and gaining the trust of drivers, thereby showing the perspective of the plight and conundrums of a cargo aggregator working in the B2C segment. This case study could be used to discuss concepts related to not-for-profit firms, aggregators, policymakers and think tanks.

Teaching notes are available for educators only.

CSS 9: Operations and logistics.

The purpose of the study is to develop a structural and a predictive model of the future purchase behavior of the consumers from value, quality and satisfaction and also finding the role of consumer loyalty in the above-mentioned model.

Based on survey and purchase data of a sample of 235 respondents, the authors have used structural equation modeling to develop a structural model and three-stage least square regression to develop and validate the predictive model.

In the structural model, the authors found that perceived service quality and network quality leads to customer satisfaction which also leads to loyalty intentions. However, neither past purchase behavior nor loyalty has significant predictive power to predict future usage. But the interaction effect of loyalty and past purchase predicts future purchase significantly.

The study went beyond structural model and developed a behavioral predictive model which can overcome self-reporting bias. Also, the study focused on the moderating role of loyalty in predicting future purchase quantity, thus contributing toward the theoretical understanding of the effects of loyalty.

Other than providing a forecasting model, the study helps the service managers to understand the importance of the relational constructs than the tangible constructs. Moreover, it also suggests optimally target the big buyers through the loyalty programs to ensure higher future revenues.

The study provides new insight on the impact of loyalty intention of consumer’s purchase behavior and shows the boundary conditions of predictive power of loyalty intention and past purchase on future purchase. Moreover, this is one of the very few studies that have focused on these relationships in Indian context.

This study investigates the aerodynamics of the airflow over low-rise houses subjected to turbulent cyclonic winds along the South-eastern peninsular India, routinely afflicted by tropical cyclones. The purpose of this paper is to demonstrate how the power of modern computational fluid dynamics (CFD) and its engineering application accentuate decision-making at the planning stage of house designing in vulnerable areas.

The Weather Research and Forecasting (WRF) model was used for first simulating the landfall of cyclone Hudhud, a real storm, and its effect in extant and new house designs. Results from the WRF model were utilized to configure further CFD simulations of airflow around house designs. The analyses yielded deep insights, often non-intuitive, into airflow patterns around these houses with disparate roof forms indicating new possibilities in redesigning houses along Indian coastal areas.

This study shows that storm-induced high TKE values warranted a fuller CFD-based study. The second major finding showed that for a 90° angle of attack, arguably the most destructive attack angle, a pitched roof (with a pitch angle of 10°) worked best – this is about half the recommended angle sourced from earlier empirical estimates dating back to the British Raj period. There is a thin layer of padded air cushion shielding the roof's vulnerable surface from the storm's most energetic parts.

The originality of this research lies in its discourse to systematically resolve the TKE distribution of a cyclone impacting a standalone house. In particular, the study presents a lucid demonstration of all the probable scenarios connecting cyclonic stresses with a roof response, inferred from a careful combination of results garnered from cyclonic storm modelling coupled with CFD analysis. Additionally, the paper also shows a graphic visual representation of the forces induced on different roof designs, presented as a checklist for the first time. This should serve as a ready reckoner for civic authorities involved in disaster management over cyclone-ravaged areas.

The present piece of research aims at enhancing our understanding of situational and intentional showrooming behaviour. The study further tests and validates a model based on the stimulus–organism–response framework to draw richer insights.

The study adopts a two-phased approach to discover the consumers' rationale behind showrooming. In the first phase, a narrative-based examination followed by an inductive thematic analysis was employed. In the second phase, the stimulus–organism–response model was validated through structural equation modelling method.

The results of the study highlighted the factors that contribute to intentional and situational showrooming behaviour. Results show that consumers also showroom on account of situational circumstances such as assortment issues, poor sales-staff assistance and long payment queues at offline stores. However, intentional showroomers are primarily driven by perceived showrooming value which emerges as a combination of in-store search value and online purchase value. Past showrooming experience also plays a role in stimulating consumers to showroom. The results also revealed the moderating impact of product involvement and perceived product type, barring time pressure. The impact of showrooming self-efficacy was also observed.

The study majorly validates the factors stimulating intentional showrooming conduct intertwined with product-related factors, time pressure and showrooming self-efficacy. Hence, the future scope of the study lies in quantitatively validating the findings concerning situational showroomers as this would help draw richer insights.

The findings of the study can be utilized by both offline and online retailers for managing showroomers.

The study offers rich insights on showrooming which has been identified as a major challenge being faced by offline retailers nowadays.

This paper aims to identify the role of internet of things (IoT) in water supply chain management and helps to understand its future path from the junction of computer science and resource management.

The current research was studied through bibliometric review and content analysis, and various contributors and linkages were found. Also, the possible directions and implications of the field were analyzed.

The paper’s key findings include the role of modern computer science in water resource management through sensor technology, big data analytics, IoT, machine learning and cloud computing. This, in turn, helps in understanding future implications of IoT resource management.

A more extensive database can add up to more combinations of linkages and ideas about the future direction. The implications and understanding gained by the research can be used by governments and firms dealing with water management of smart cities. It can also help find ways for optimizing water resources using IoT and modern-day computer science.

This study is one of the very few investigations that highlighted IoT’s role in water supply management. Thus, this study helps to assess the scope and the trend of the case area.

The purpose of this study is to fabricate and compare the mechanical and thermal properties of Sansevieria and Kaans fiber reinforced polyester matrices composites.

Treated Sansevieria and Kaans fiber was used as reinforcement for the fabrication of polymer matrix composites. Kaans fiber, which was available plenty in the delta region, but physical and mechanical properties of Kaans fiber were low when it compared with Sansevieria fiber. To make use of Kaans fiber for the fabrication of composite, the physical and mechanical properties have to be enhanced. So Egg shell powder was selected as a filler material to enhance the Kaans fiber reinforced composite. The selected fibers were properly weaved after alkali treatment. A three-layered (0°/45°/0°) Sansevieria fiber reinforced polymer (S-FRP) and Kaans fiber reinforced polymer (K-FRP) composite plates were fabricated using the compression molding method. As per American Society for Testing and Materials standards, the specimens were cut and mechanical, thermal and absorption properties of Sansevieria and Kaans fiber composites were investigated experimentally.

Tensile and flexural test reveals that K-FRP composite has good ductility and bending property than S-FRP composite plate. But from the other test results, S-FRP possesses high elongation capability than K-FRP. Thermo gravimetric analysis, moisture absorption and swelling test too done which clearly appeared S-FRP composite plate has prevalent execution than K-FRP composite plate.

This original research study enlists the mechanical, thermal properties and absorption properties of fabricated S-FRP and K-FRP composite plates.

This study aims to examine the influencing factors of green innovation and their effect on economic performance of the hotel industry.

The study used a quantitative and cross-sectional research design, and primary data were collected using structured questionnaire. To analyze this data, AMOS software was used. Exploratory factor analysis (EFA) was performed to purify the measurement model. Moreover, validities and model fitness were confirmed through confirmatory factor analysis (CFA). Structural equation modeling (SEM) was used to test the study hypothesis.

The study results showed green organizational culture, green organizational strategies, energy conservations and environmental regulations as key influencing factors in the adoption of green innovation. Moreover, the results also reveal a significant positive effect of green innovation on hotels’ economic performance.

This study is limited to hotels operating in the sole city of Shanghai, China, and for more generalized results, the future study can be made by incorporating hotels in other cities as well. Moreover, the study is conducted in China and replication of this research might be possible in a different cultural and environmental context. Furthermore, this study address only the hotel industry, and future study can be made to investigate the implementation of green practices in industries other than hotels.

Previously, many studies have highlighted the influencing factors of green innovation, but there is limited research in the context of the hotel industry. The relationship between economic performance and green innovation is well established, but still, it is not fully understood how sustainable economic performance is contributed by green innovation in the tourism industry. To the best of the authors’ knowledge, this study first examines the influencing factors of green innovation and its potential effect on economic performance in the context of the Chinese hotel industry.