Search results

This study aims to analyze the dynamic performance of aerostatic thrust bearing for different geometries of recess. Different geometries of recess of equal recess area, i.e. circular, elliptical, rectangular and annular, have been considered in analysis. The work also analyzes the influence of tilt angle on the performance of thrust bearing. To compute the unknown pressure field, the Reynolds equation governing the flow of compressible lubricant (air) has been solved using finite element formulation. Further, separate finite element formulations have been carried out to compute fluid film stiffness and damping coefficients directly. This method provides quick computation of stiffness and damping coefficients of aerostatic thrust bearing than the usual approach.

As the Reynolds equation governing the flow of compressible lubricant is nonlinear partial differential equation, the computation of the stiffness and damping coefficient follows an iterative procedure. It requires a lot of computational energy. Therefore, in the present work, a novel technique based on finite element formulation is suggested to compute air film stiffness and damping coefficient in aerostatic thrust bearing.

A novel technique based on finite element formulation is illustrated to simulate the performance of tilted pad aerostatic thrust bearing. On the basis of simulated results, following key conclusions may be drawn. The static and dynamic performance of a circular aerostatic tilted thrust pad bearing is significantly affected with a change in the value of tilt parameter and the shape of the recess.

Implications are as follows: direct computation of air film damping coefficient is performed without perturbation method in finite element method (FEM); influence of tilt on aerostatic thrust bearing is studied; influence of recess shape on aerostatic thrust bearing is observed; and finite element formulation of aerostatic thrust bearing is performed.

The present work will be quite useful for bearing designer and academicians.

This study aims to identify the product attributes that influence customer satisfaction related to AI-enabled products with a strong forecast of growth. This study is very timely as the market for AI-based smart home products is still at a nascent stage in emerging economies (Vaishali Dar, 2021). Adding evidence to literature on the experience of customers, identifying the attributes that lead to customer satisfaction and those that lead to dissatisfaction are essential for products that were launched recently during the pandemic. This study makes valuable addition to the existing literature.

Online reviews (12,326 reviews) for EchoDot products launched by Amazon India during the pandemic were collected for the study. The attributes were identified based on the most frequently discussed attributes in the text reviews. Further review valence was determined to group the reviews under positive reviews indicating customer satisfaction and negative reviews indicating customer dissatisfaction. Logistic regression was used to identify the attributes that significantly impact customer satisfaction/dissatisfaction.

The results of the study indicate that while EchoDot is seen to add value to the smart home environment (home variable), video (video variable) and speaker (speaker variable) quality also contribute to customer satisfaction. Further, consumers found the product truly worth their money (value for money variable). Other attributes like a complaint about Bluetooth features are seen to increase the probability of customer dissatisfaction.

This study identifies the most important attributes that influence customer satisfaction in AI-enabled product sales on e-commerce platforms in pandemic times for India. Such studies are scarce in the emerging markets where the AI-based home appliance market is still in its nascent stage, and the customers are trying out their experiences with these products. What the customers expect and are these products fulfill these expectations is an important question that needs to be addressed by research. This study addresses this gap and adds to this literature.

This study aims to find out the influence of green practices used by the five-star hotels on the guest’s online hotel assessment and their revisit intentions. It also evaluated how the use of green practices by the hotels influenced the guest’s willingness to pay a premium price. Apart from the conventional hotel service attributes, this study also identified some new and innovative services offered by the hotels which have an overall effect on the guest’s revisit intentions.

This study applied focus group interviews from 12 hotel managers and accessed the hotel’s internal database to identify the latest and innovative service attributes offered by the hotels. The information regarding the green practices offered by the hotels was collected through TripAdvisor and LEED-IGBC website. It identified 10 independent and four dependent variables based on previous literature. Guest’s revisit intentions were measured on a five-point Likert scale. Data was analysed using a multi-step hierarchical regression model.

The use of green practices by the hotels revealed a positive and significant influence on the guest’s revisit-intentions and their intention to pay a premium price. It was also found that the use of new and innovative green practices has a positive influence on the guest’s overall online evaluation of the hotel.

This study suggests that the amalgamation of green practices along with the conventional service attributes may help in the incremental revisit and online hotel assessment intentions, which might be of use for the managers and hotel policymakers.

Although previous studies have explored the conventional hotel service attributes in the context of Indian Hotel industry, this is one of the first studies which discussed the influence of recent and emerging hotel service attributes on the guest’s revisit and pay a premium price intention. Moreover, the influence of green practices on the guest’s overall online evaluation of the five-star hotels in Delhi was discussed in this study which was not performed before.

This paper aims to derive insights from Kongthong village, popularly known as the “whistling village,” a low-key rural tourism destination that has often gone under the radar. As an upcoming rural tourism destination, mothers create a unique tune for their children, ensuring that their identity remains unique. This is because the residents of Kongthong have two names: an official name and another in the form of a whistled tune. The primary objective of this study is to better understand the rural tourism activities at Kongthong and to explore the symbiotic relationship between indigenous cultural practices and holistic development through tourism.

The study uses an ethnographic approach wherein the researchers conducted in-depth interviews and group discussions. The study respondents are the village elders, youth, men and women across different age groups. The various governing bodies act as secondary data sources concerning tourism and development.

The study observes that rural tourism activities in Kongthong go hand in hand with understanding indigenous knowledge. The governing bodies and the local community are on the right path to achieving potential growth and preserving the village as a holistic rural tourist destination.

Rural tourism in Kongthong highlights the traditional practices of the Khasi community. Owing to this, Kongthong was nominated for the United Nations World Tourism Organization (UNWTO) best tourism village by the Government of India as it showcases local culture through social, economic and political elements at the destination that add value to a tourism product.

Decentralised autonomous organisations (DAOs) are internet-native self-governing enterprises where individual groups, communities, agencies, consumers and providers work together using blockchain-led smart contracts (SCs). This study aims to examine the role of DAO marketplaces in technology-led autonomous organisation design for enterprise technology sourcing industries, with algorithmic trust and governance.

The authors examined the importance of an enterprise marketplace governance platform for technology sourcing using DAO as a decentralised/democratised business model. A total of 98 DAO products/services are evaluated across 11 industries that envisage DAO as a strategic choice for the governance of decentralised marketplace platforms.

The research findings validate how a DAO-led enterprise marketplace governance platform can create a cohesive collaboration between consumers (enterprises) and providers (solution vendors) in a disintermediated way. The proposed novel layered solution for an autonomous governance-led enterprise marketplace promises algorithmic trust-led, self-governed tactical alternatives to a strategic plan.

The research targets multiple industry outlooks to understand decentralised autonomous marketplace governance and develop the theoretical foundation for research and extensive corporate suitability.

The research underpinnings boost the entrepreneurs’ ability to realise the practical potential of DAO between multiple parties using SCs and tokenise the entire product and service offerings over immutable ledger technologies.

To the best of the authors’ knowledge, this research is unique and the first of its kind to study the multi-industry role of algorithmic trust and governance in enterprise technology sourcing marketplaces driven by 98 decentralised and consensus-based DAO products across 11 industries.

The global organic market is expanding, and India is in an advantageous position with the highest number of organic producers worldwide. Although many articles have been published on the value chain of organic products from India, no significant studies were found related to the value chain analysis of organic pineapple. This study aims to know the various aspects of the organic pineapple value chain, i.e. network structure, value addition at various stages of chain actors, value chain upgradation and governance structure.

The study is explorative in nature, and primary data from various actors involved in the chain is collected and analyzed. Primary data through a structured schedule and interviews are collected from farmers and traders. A multistage sampling plan has been adopted. A sample of 75 farmers was randomly selected from the study area. For traders, snowball sampling is used due to the nonavailability of the sampling frame. A total of 10 commission agents, 10 wholesalers and 20 retailers were thus selected for the study. For objectives 1 and 4, descriptive statistics are used. For objective 2, a modified formula described by (Murthy et al., 2007) is used to calculate farmer’s net price and marketing margin. For objective 3, Garrett’s ranking technique is used to identify various constraints in upgrading the organic pineapple value chain in Assam.

This study shows that the value chain of organic pineapple is in the initial stage and proper value addition is required to have a complete regulated value chain. Six marketing channel is identified, and products are sold through farmer producer company only in case of export and trade with distant buyers. The marketing efficiency for channels II and III is 1.69 and 0.99, respectively. The degree of value addition for channel II in the hands of the commission agent, wholesaler and retailer is 11.65%, 4.56% and 12.60%, respectively. In the various constraints in upgrading the value chain, farmers rank “policy support” as a major constraint. In the governance structure, trade with distant traders and exports is done formally and through written contracts.

The study performs value chain analysis of organic pineapple in Cachar district of Assam, India for the year January 2022–January 2023. Future studies are encouraged related to various aspects of the supply chain and value chain of organic pineapple from various northeastern states of India and other states.

The study will help policymakers and key actors to know the existing chain and frame a well-coordinated and regulated value chain.

This study is one of the first study to explore the value chain of organic pineapple of Cachar district of Assam, India. Implementation of these findings can help various actors to strengthen the existing value chain.

This paper aims to explore the challenges faced by start-ups during COVID-19 and highlight solutions for catering to the new-normal consumer behaviour. The study accounts for 15 deep-tech start-ups sailing through the pandemic and their responsiveness. This study brings forth insights and experiences from the Indian start-up founders and CEOs during COVID-19.

This study uses a qualitative approach and is exploratory and phenomenological. A purposive sample of 15 young start-ups founded between the years 2013–2020 by founders aged between 24 and 41 was selected for the study. The recorded telephonic interview was collected from the founders from April 2021 to September 2021. The thematic analysis of the study evolves from Braun and Clarke (2006) using the MAXQDA 2020.

The study emphasizes upon challenges faced by start-ups, crisis management of start-ups and the relevance of technology-based start-ups during challenging times. This research provides a qualitative framework to establish the role of the technology acceptance model (TAM) towards the adaptability, responsiveness and resilience demonstrated by the start-ups. The findings also highlight the solutions to address challenges faced by start-ups and road to recovery.

The study has great relevance and lessons for budding entrepreneurs during crisis management. The study has implications for corporations and governments in terms of setting up incubators and accelerators to support budding entrepreneurs.

The study is unique in highlighting the relevance and importance of TAM for start-ups during crisis management like COVID-19. The study thrusts upon the need of technology acceptance for better crisis management.

Digital transformation (DT) leverages digital technologies to change current processes and introduce new processes in any organisation’s business model, customer/user experience and operational processes (DT pillars). Artificial intelligence (AI) plays a significant role in achieving DT. As DT is touching each sphere of humanity, AI led DT is raising many fundamental questions. These questions raise concerns for the systems deployed, how they should behave, what risks they carry, the monitoring and evaluation control we have in hand, etc. These issues call for the need to integrate ethics in AI led DT. The purpose of this study is to develop an “AI led ethical digital transformation framework”.

Based on the literature survey, various existing business ethics decision-making models were synthesised. The authors mapped essential characteristics such as intensity and the individual, organisational and opportunity factors of ethics models with the proposed AI led ethical DT. The DT framework is evaluated using a thematic analysis of 23 expert interviews with relevant AI ethics personas from industry and society. The qualitative data of the interviews and opinion data has been analysed using MAXQDA software.

The authors have explored how AI can drive the ethical DT framework and have identified the core constituents of developing an AI led ethical DT framework. Backed by established ethical theories, the paper presents how DT pillars are related and sequenced to ethical factors. This research provides the potential to examine theoretically sequenced ethical factors with practical DT pillars.

The study establishes deduced and induced ethical value codes based on thematic analysis to develop guidelines for the pursuit of ethical DT. The authors identify four unique induced themes, namely, corporate social responsibility, perceived value, standard benchmarking and learning willingness. The comprehensive findings of this research, supported by a robust theoretical background, have substantial implications for academic research and corporate applicability. The proposed AI led ethical DT framework is unique and can be used for integrated social, technological and economic ethical research.

The purpose of this study is to identify the major factors influencing the adoption of health-care wearables in generation Z (Gen Z) customers in India. A conceptual framework using push pull and mooring (PPM) adoption theory was developed.

Data was collected from 208 Gen Z customers based on 5 constructs related to the adoption of health-care wearables. Confirmatory factor analysis and structural equation modelling was used to analyse the responses. The mediation paths were analysed using bootstrapping method and examination of the standardized direct and indirect effects in the model.

The study results indicated that the antecedent factors consisted of push (real-time health information availability), pull (normative environment) and mooring (decision self-efficacy) factors. The mooring factor (MOOR) was related to the push factor but not the pull factor. The MOOR, in turn, was related to the switching intention of Gen Z customers for health wearables adoption.

The research study extended the literature related to the PPM theory in the context of the adoption of health wearables among Gen Z customers in India.

The study outcome would enable managers working in health wearable organizations to understand consumer behaviour towards health wearables.

The use of health wearables among Gen Z individuals would lead to future generations adopting a healthy lifestyle resulting in an effective workforce and better economy.

This was one of the few studies which have explored the PPM theory to explore the factors for the adoption of health wearables among Gen Z customers in India.