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Recent decades have witnessed a rising concern regarding the prosperity of the environment and utilisation of resources. A sustainable approach is being promoted in all sectors. In the field of tourism, sustainable tourism is widely discussed among researchers and practitioners. On the other hand, luxury tourism is criticised for lavish resource utilisation to serve the few luxury tourists. There is a need to include sustainability in luxury tourism to benefit the environment, local communities, tourist destination and luxury tourists. However, sustainable luxury tourism is an emerging concept and needs more investigation. This chapter attempts to present the existing knowledge about sustainable luxury tourism by implementing a systematic literature review. Further, the opportunities and challenges associated with sustainable luxury tourism are being highlighted. This study has identified the factors that need to be considered to promote sustainable luxury tourism. Moreover, suggestions of the researchers are being presented to serve as guidelines. This study includes an example of the Diphlu river lodge, which has practised sustainable luxury tourism for many years. The viewpoint of luxury tourists are being understood by analysing the reviews of tourists from TripAdvisor using NVIVO-12 qualitative data analysis software. The combination of literature review and practical information provides insight into sustainable luxury tourism.

This paper aims to address the challenges knowledge actors face when using knowledge codifiability to develop common interests. The challenge is compounded when actors with diverse knowledge domains depend on each other to complete tasks, and, simultaneously, update their knowledge to address novelty in the organizational environment.

Given this context, this paper studies the impact of two moderating variables, systems dependence (Z) and novelty (W), on the relationship between knowledge codifiability (X) and common interests (M). This study also examines whether common interests (M) mediate the relationship between knowledge codifiability (X) and knowledge transfer (Y). To test the hypotheses, the authors collected data from 163 entrepreneurs in the southwest USA.

The results demonstrate that novelty in the knowledge domain of actors provides a supporting context for knowledge codifiability to develop common interests, but only when actors’ dependence on each other to complete tasks is at low to medium level. Moreover, the results also provide evidence that common interests mediate the relationship between codifiability and ease of knowledge transfer.

Using the results, this study provides a decision-making framework for managing tasks based on system dependence and novelty level.

The research first and uniquely explores the antecedent relationship among three highly studied environmental forces – competitive intensity (CI), market turbulence (MT) and technological turbulence (TT) – in a service context. Next, given the importance of services to the USA and global gross domestic product (GDP) and the unique characteristics of services versus product firms, the research examines the impact of environmental forces on innovation speed capability, a less studied but critical enabler of service innovation. Finally, this study aims to suggest the importance of the sequential relationship between two dynamic capabilities – innovation speed and operational flexibility – to realize advantage.

This study surveyed 264 US service firms in a business to business context and tested this research model using structural equation modeling.

The results yielded three major conclusions: in a service context when examining the relationship among the three environmental forces, CI appears to have the driving influence on MT and TT, MT, however, was the only environmental force that this study found to bare positive and significant direct influence on innovation speed. Looking at the zero-order effect of MT and TT on innovation speed this study found each to be positive and significant suggesting a negative suppression effect and innovation speed’s influence on performance relative to competitors is fully mediated by operational flexibility.

The paper contributes to context, as service firms represent the majority of the USA and global GDP. This study extends the literature on the highly studied environmental forces (MT, TT and CI) by examining how they influence each other in an antecedent role and in service context. This study extends service literature by going beyond the influence of environmental forces on innovation to examine the dynamic capability of innovation speed, suggested as uniquely important to service context and distinct from the more highly studied innovation construct. The study also extends prior research in the manufacturing (product) context that suggests the importance of sequential congruence between two critical dynamic capabilities – innovation speed and operational flexibility – necessary to deliver competitive advantage.

The rapid increase in analytics is playing an essential role in enlarging various practices related to the health sector. Big Data Analytics (BDA) provides multiple tools to store, maintain, and analyze large sets of data provided by different systems of health. It is essential to manage and analyze these data to get meaningful information. Pharmaceutical companies are accumulating their data in the medical databases, whereas the payers are digitalizing the records of patients. Biomedical research generates a significant amount of data. There has been a continuous improvement in the health sector for past decades. They have become more advanced by recording the patient’s data on the Internet of Things devices, Electronic Health Records efficiently. BD is undoubtedly going to enhance the productivity and performance of organizations in various fields. Still, there are several challenges associated with BD, such as storing, capturing, and analyzing data, and their subsequent application to a practical health sector.

This paper examines the current state of blockchain governance research. The study’s findings also propose a conceptual framework for the use of blockchain in governance and global governance and provide a global look at how public and private sectors alike are implementing new technologies.

The study is qualitative as well as quantitative in nature. The authors used Preferred Reporting Items for Systematic and Meta-Analysis (PRISMA) to gather data for the study. Furthermore, a bibliometric analysis using VOSviewer visualization tool and R Studio was carried out to attain the research objectives.

Many scholars and practitioners from around the world are interested in the topic, according to the analysis. This is a multidisciplinary study, so researchers have looked at how the blockchain can be used to govern countries, public utilities and global facilities, including corporations. There are numerous examples of how technology has been used in global governance, and the authors found that governments, as well as corporations around the world, have implemented technology in a variety of areas that affect the public and other stakeholders.

This study makes numerous contributions. In the first place, it presents the complex concept of blockchain in an easier to understand way. The numerous governmental and commercial initiatives that have made use of blockchain are also highlighted. As a result, the use of technology in corporate and social governance will continue to grow. Finally, the research will inform the academic community on the current state of the topic and potential future directions.

As a result of this research, academics and scholars can better understand the potential of blockchain in various governance models, ranging from developed to developing economies. The general public, as well as organizations, will benefit from the decentralized nature of the blockchain in a variety of ways related to their day-to-day governance. To the best of authors’ knowledge, this is a first kind of research on blockchain in governance using PRISMA and bibliometrics tools.

Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of agricultural products. Pesticides can be used to improve agricultural land products. This study aims to make the spraying of cherry trees more effective and efficient with the designed artificial intelligence (AI)-based agricultural unmanned aerial vehicle (UAV).

Two approaches have been adopted for the AI-based detection of cherry trees: In approach 1, YOLOv5, YOLOv7 and YOLOv8 models are trained with 70, 100 and 150 epochs. In Approach 2, a new method is proposed to improve the performance metrics obtained in Approach 1. Gaussian, wavelet transform (WT) and Histogram Equalization (HE) preprocessing techniques were applied to the generated data set in Approach 2. The best-performing models in Approach 1 and Approach 2 were used in the real-time test application with the developed agricultural UAV.

In Approach 1, the best F1 score was 98% in 100 epochs with the YOLOv5s model. In Approach 2, the best F1 score and mAP values were obtained as 98.6% and 98.9% in 150 epochs, with the YOLOv5m model with an improvement of 0.6% in the F1 score. In real-time tests, the AI-based spraying drone system detected and sprayed cherry trees with an accuracy of 66% in Approach 1 and 77% in Approach 2. It was revealed that the use of pesticides could be reduced by 53% and the energy consumption of the spraying system by 47%.

An original data set was created by designing an agricultural drone to detect and spray cherry trees using AI. YOLOv5, YOLOv7 and YOLOv8 models were used to detect and classify cherry trees. The results of the performance metrics of the models are compared. In Approach 2, a method including HE, Gaussian and WT is proposed, and the performance metrics are improved. The effect of the proposed method in a real-time experimental application is thoroughly analyzed.

The purpose of this paper is to study the performance metrics of redundant repairable machining system which is applicable in various systems like computer and communication system, manufacturing and production system, etc.

In the present investigation, the authors develop Markov model for the system consisting of identical active operating machines which are prone to breakdown. The operating machines are under the care of one permanent repair facility that provides time-sharing basis repair services. The maintenance is facilitated with the provision of standby machines of mixed type and permanent as well as additional repair facility. From the economic point of view, F-policy and N-policy to control the service and arrival of failed machines effectively are included.

For the performance analysis of the system in long run, the authors compute steady-state probabilities using product-type solution method recursively. Sensitivity analysis is performed numerically for various parameters by developing code in MATLAB.

The performance prediction done may be helpful for the system designers and decision makers for the improvement of the existing machining systems in various industries.

Markovian model for the performance prediction of fault tolerant multi-identical operating and standby machines redundant system is developed in generic frameworks by incorporating many noble features which were not all taken together by other researchers working on the same lines. The key concepts incorporated for the modeling of the concerned system is: F-policy, N-policy, time-sharing, and sensitivity analysis of availability and cost function.

This study aims to understand the current production scenario emphasizing the significance of green manufacturing in achieving economic and environmental sustainability goals to fulfil future needs; to determine the viability of particular strategies and actions performed to increase the process efficiency of electrical discharge machining; and to uphold the values of sustainability in the nonconventional manufacturing sector and to identify future works in this regard.

A thorough analysis of numerous experimental studies and findings is conducted. This prominent nontraditional machining process’s potential machinability and sustainability challenges are discussed, along with the current research to alleviate them. The focus is placed on modifications to the dielectric fluid, choosing affordable substitutes and treating consumable tool electrodes.

Trans-esterified vegetable oils, which are biodegradable and can be used as a substitute for conventional dielectric fluids, provide pollution-free machining with enhanced surface finish and material removal rates. Modifying the dielectric fluid with specific nanomaterials could increase the machining rate and demonstrate a decrease in machining flaws such as micropores, globules and microcracks. Tool electrodes subjected to cryogenic treatment have shown reduced tool metal consumption and downtime for the setup.

The findings suggested eco-friendly machining techniques and optimized control settings that reduce energy consumption, lowering operating expenses and carbon footprints. Using eco-friendly dielectrics, including vegetable oils or biodegradable dielectric fluids, might lessen the adverse effects of the electrical discharge machine operations on the environment. Adopting sustainable practices might enhance a business’s reputation with the public, shareholders and clients because sustainability is becoming increasingly significant across various industries.

A detailed general review of green nontraditional electrical discharge machining process is provided, from high-quality indexed journals. The findings and results contemplated in this review paper can lead the research community to collectively apply it in sustainable techniques to enhance machinability and reduce environmental effects.