Search results

This study aims to examine the intricate relationships in the making of a box office through a stakeholder lens that considers the influence of filmmakers and theatres on moviegoers' intention to watch a movie at the theatre.

Employing covariance-based structural equation modelling (CB-SEM), this study analyses survey data on cinema-going experience collected from 673 moviegoers in digital era of a new normal.

The findings elucidate that movie branding, movie genre and theatre preference positively influence moviegoers' intention to watch a movie at the theatre. Furthermore, the study unveils that theatre preference is swayed by an array of personal and social factors, including control belief and social companion. Intriguingly, promotional elements, both commercial and non-commercial, were found to influence movie branding, yet not the genre when predicting theatre attendance intentions.

Amid the burgeoning alternatives for watching movies (e.g. cable television and online streaming platforms), this article offers a contemporary exploration of the variables that motivate audiences to partake in the cinema-going experience, thereby serving as a proxy to decipher the factors that drive a movie's box-office success in digital era.

Unlike prior studies relying on archival data, the present study collects and uses survey data to develop a novel stakeholder theory-based marketing framework for the box office and moviegoers. The study also provides seminal insights on the box office and moviegoers in the digital era of a new normal.

This chapter investigates pandemic impact in a variety of industries, including food, travel, education and pharmaceuticals, considering elements such as isolation, emotions and social influences, which can lead to panic buying. The goal of this research is to ascertain how COVID-19 influences the buying decisions of customers. Additionally, the study aims to identify consumer consumption trends for a spectrum of products and services, including fast-moving consumer goods (FMCGs), entertainment, pharmaceuticals, travel and tourism. A comprehensive review of different research papers is done to conclude. The papers considered are from 2020 to 2022. Different keywords are used to search the relevant papers such as ‘pandemic’, ‘COVID-19’, ‘behaviour’, ‘impulsive’, etc. TCCM framework has been applied while reviewing the articles. During the isolation, consumer behaviour moved to panic buying and stockpiling, favouring organic basics, and encouraging e-commerce, as well as economic nationalism favouring made-in-India products. This study helps in knowing the reasons for change in consumers' behaviour for different products and services due to unforeseeable situations like COVID-19 and can find possible ways to deal with them. Business owners learn about changing consumer purchasing behaviours and how to modify products. The government can change policies to improve medical tourism and social protection.

Integrating digital technologies such as artificial intelligence and blockchain make the agri-food supply chain (ASCM) transparent, resilient and flexible. However, its adoption is quite complex due to various anticipated barriers. So, the presented research purposes to explore and investigate the barriers.

This study employs hybrid approach including Best-Worst Method (BWM) and Graph Theoretic Approach (GTA). Data were collected from industry experts employed in the agri-food sector and analyzed by means of standard operating procedures.

GTA results show that Technological barriers have the highest barrier intensity. Moreover, BWM results show that “Increased operational complexity” is the topmost barrier to adopting blockchain in ASCM. “Lack of interoperability” ranks second among the identified barriers.

The results benefit the managers, practitioners and researchers to understand the anticipated barriers so that necessary strategies can be developed, and organizations can become more resilient, agile, transparent and traceable.

The presented work is the first to develop a mathematical model and assess the industry’s eagerness to adopt blockchain in ASCM. The proposed framework will greatly benefit the stakeholders working in agri-food sector.

Stringent environmental regulations and the need for a robust supply chain (SC) network have necessitated organizations to adopt circular economy (CE) practices. With proven impact of CE practices on SC activities, digital technologies are prompting organizations to digitalize SC networks. Yet, the correlation between SC digitalization and CE practices has been less examined. This study aims to identify and evaluate, the critical success factors (CSFs) necessitating SC digitalization and strategies helping in SC digitalization.

An extensive literature review was performed to identify CSFs and strategies for SC 4.0 (SC4.0), and for finalization, experts’ input was obtained with the Delphi approach. An integrated Fermatean fuzzy set – analytic hierarchy process – decision-making trial and evaluation laboratory – combined compromise solution technique was used to evaluate CSFs and strategies.

Smart work environment, performance monitoring and data reliability and relevance were identified as the top three important CSFs for SC digitalization. Enhancement of analytical capability, data-driven process optimization and development of an integrated digital platform were identified as potential SC4.0 transition strategies.

This study helps SC practitioners better understand the CSFs and strategies for the SC4.0 transition. Furthermore, this study explores the integration of CE principles within these digital strategies, emphasizing how sustainability practices can be embedded in the SC4.0 framework to foster a more resilient and environmentally conscious electronics SC in India.

To the best of the authors’ knowledge, this work is the first to analyze CSFs for SC4.0 in the Indian electronics industry.

The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses.

The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis.

Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs.

The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each.

The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses.

The weld joint mechanical properties of friction stir welding (FSW) are majorly reliant on different input parameters of the FSW machine. The study and optmization of these parameters is uttermost requirement and aim of this study to increase the suitability of FSW in different manufacturing industries. Hence, the input parameters are optimized through different soft computing methods to increase the considered objective in this study.

In this research, ultimate tensile strength (UTS), yield strength (YS) and elongation (EL) of FSW prepared butt joints of AA6061 and AA5083 Aluminium alloys materials are investigated as per American Society for Testing and Materials (ASTM E8-M04) standard. The FSW joints were prepared by changing the three input process parameters. To develop experimental run order design matrix, rotatable central composite design strategy was used. Furthermore, genetic algorithm (GA) in combination (Hybrid) with response surface methodology (RSM), artificial neural network (ANN), i.e. RSM-GA, ANN-GA, is exercised to optimize the considered process parameters.

The maximum value of UTS, YS and EL of test specimens on universal testing machine was measured as 264 MPa, 204 MPa and 14.41%, respectively. The most optimized results (UTS = 269.544 MPa, YS = 211.121 MPa and EL = 17.127%) are obtained with ANN-GA for the considered objectives.

The optimization of input parameters to increase the output objective values using hybrid soft computing techniques is unique in this research paper. The outcomes of this study will help the FSW using manufacturing industries to choose the best optimized parameters set for FSW prepared butt joint with improved mechanical properties.

This study aims to investigate the impact of titanium oxide (TiO₂) filler on the coefficient of friction (COF) and specific wear rate (SWR) in flax fiber reinforced epoxy composites (FFRCs) under abrasive wear conditions utilizing the Taguchi approach. The primary objective is to enhance wear resistance and promote the development of sustainable materials for various applications.

Epoxy/flax composites with varying TiO₂ filler content (0–8 wt%) are fabricated through the hand layup method. Subsequently, wear testing is conducted following ASTM G99-05 standards. The Taguchi design of experiments (DOE) and analysis of variance (ANOVA) are utilized for statistical analysis.

Results indicate a significant improvement in abrasive wear properties with the incorporation of TiO₂ filler. The COF is found to be most influenced by the normal load (55.19%), followed by grit size, wt% TiO₂ filler and sliding distance. SWR is found to be most influenced by the grit size (42.92%), followed by wt% TiO₂, normal load and sliding distance. Notably, the Taguchi model aligns well with experimental results, demonstrating its efficacy in predicting the abrasive wear behavior of FFRCs.

This research introduces a novel hybrid composite that combines TiO₂ filler and flax fibers, showcasing their potential to enhance the tribological properties of epoxy composites. The study offers valuable insights into optimizing abrasive wear test variables in natural fiber-reinforced composites using Taguchi DOE and ANOVA, crucial for improving the performance of sustainable materials in engineering applications.

The learning outcome of this case study is to help students identify issues of the electric two-wheeler industry in India, revisiting conventional business models and transitioning toward sustainable business models. Eventually, this case study will enhance students’ analytical, qualitative analysis, multidisciplinary approach and strategic decision-making skills.

This case study can be used to discuss Michael Porter’s five forces model, TOWS matrix and Michael Porter’s generic strategies for competitive advantage.

Bounce was established in 2014 by Vivekananda Halkere, Anil G. and Varun Agni. The startup was an on-demand service provider of scooters. It also claimed to be the world’s fastest-growing scooter rental startup. As of March 2020, Bounce operated in 12 Indian cities, namely, Bengaluru, Jaipur, Hassan, Kolar, Mysore, Bhuj, Udaipur, Belgavi, Hyderabad, Ahmadabad, Hampi and Delhi. Bounce’s revenue grew to INR 1,000m in the fiscal year (FY) 2020 compared to INR 160m in FY 2019. Halkere was happy and proud of what his friends and he had achieved in the past two years. However, he was concerned about competition. What plan of action was needed to help thwart competition. What would be the best strategy to achieve growth and monetize operations? and How would Bounce address these major challenges to capture market share?

This case study can be taught in advanced undergraduate, MBA or executive-level programs dealing with strategic management. This case study helps students in dealing with issues pertaining to a given market sector where a firm is operating and the strategies to thwart competition.

Teaching notes are available for educators only.

CSS11: Strategy.

This paper aims to report the effect of titanium oxide (TiO₂) particles on the specific wear rate (SWR) of alkaline treated bamboo and flax fiber-reinforced composites (FRCs) under dry sliding condition by using a robust statistical method.

In this research, the epoxy/bamboo and epoxy/flax composites filled with 0–8 Wt.% TiO₂ particles have been fabricated using simple hand layup techniques, and wear testing of the composite was done in accordance with the ASTM G99-05 standard. The Taguchi design of experiments (DOE) was used to conduct a statistical analysis of experimental wear results. An analysis of variance (ANOVA) was conducted to identify significant control factors affecting SWR under dry sliding conditions. Taguchi prediction model is also developed to verify the correlation between the test parameters and performance output.

The research study reveals that TiO₂ filler particles in the epoxy/bamboo and epoxy/flax composite will improve the tribological properties of the developed composites. Statistical analysis of SWR concludes that normal load is the most influencing factor, followed by sliding distance, Wt.% TiO2 filler and sliding velocity. ANOVA concludes that normal load has the maximum effect of 31.92% and 35.77% and Wt.% of TiO2 filler has the effect of 17.33% and 16.98%, respectively, on the SWR of bamboo and flax FRCs. A fairly good agreement between the Taguchi predictive model and experimental results is obtained.

This research paper attempts to include both TiO₂ filler and bamboo/flax fibers to develop a novel hybrid composite material. TiO₂ micro and nanoparticles are promising filler materials, it helps to enhance the mechanical and tribological properties of the epoxy composites. Taguchi DOE and ANOVA used for statistical analysis serve as guidelines for academicians and practitioners on how to best optimize the control variable with particular reference to natural FRCs.