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Purpose: The study aims to extract insights into five significant industries, pharmaceutical, space, defence, renewal energy, and information technology (IT), which have huge potential to make India achieving a five trillion-dollar economy in the future.

Design/methodology/approach: The authors focus on future-driven industries which are not only making India a third highest gross domestic product (GDP) producer country but also reviewing the different aspects of these industries and how they can assist India in achieving a five trillion-dollar economies along with determining India’s self-reliance through different governments initiatives in this direction.

Findings: The findings highlight the importance of inclusiveness of policymakers, stakeholders, private players, foreign investors, and the masses. Their significant contributions especially in the pharmaceutical, space, defence, renewal energy, and IT sectors in terms of creativities, innovations, intellect, executions, implementations, and improvements can assist India in achieving its five trillion-dollars economy soon.

Practical implications: This study offers (1) convincing insights into five key industries, pharmaceutical, space, defence, renewal energy, and IT, which have huge potential to increase total GDP volume shortly and (2) the investment areas for the masses where they can see their world not only self-reliant but also will see huge growth in their invested amount in these industries in future.

Originality/value: The insights of five key industries, pharmaceutical, space, defence, renewal energy, and IT, highlight that India has the potential to achieve a five trillion-dollar economy in the future; however, it does not ignore the significant contribution of other industries in making of total GDP.

The rise and popularity of digitalization have made the addictive use in the virtual world more common, which has aroused wide attention from academia and public. Uncovering the underlying mechanism of addictive use is essential to address this serious issue.

By utilizing the context of massively multiplayer online games (MMOGs), this study developed virtual-domain perfectionism of seeking excellence and avoiding failure from the dual process model of perfectionism and identified four affordances in MMOGs from the perspective of technology affordance. The authors surveyed 302 valid samples in MMOGs to empirically test the research model.

The results demonstrate that two processes of virtual-domain perfectionism influence addictive use positively in MMOGs. Technology affordances perform as the antecedents of virtual-domain perfectionism and conduct distinct impacts in MMOGs. Specifically, affordances of interaction and identity are positively related to virtual-domain perfectionism, while achievement affordance is unrelated to virtual-domain perfectionism. Immersion affordance is positively related to virtual-domain perfectionism of seeking excellence and negatively associated with virtual-domain perfectionism of avoiding failure.

This study identified virtual-domain perfectionism and specific MMOGs affordances. The research model provides insights into addictive use in MMOGs by leveraging context and combining lenses. Research findings help elucidate the role of virtual-domain perfectionism on the addictive use from MMOGs affordances with the corresponding technical features.

In this final chapter, we explore the ever-evolving 21st century landscape where ethics drive community development toward resilience and progress. Drawing inspiration from the subheadings mapping our journey, we traverse international case studies spanning Canada, Brazil, Sweden, Kenya, China, Australia, Antarctica, and India. Through these global insights, we uncover the impacts of dynamic forces on communities worldwide, navigating ethical dilemmas and opportunities. We present strategies tailored to diverse continent-specific needs, explore inclusive governance models, and highlight the transformative power of ethical engagement. This journey underscores the vital role of resilience and concludes with a global call to embrace ethical approaches for inclusive community development and a sustainable future.

This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the limitations of expert demonstration data and reduces the dimensionality of the agent’s exploration space to speed up the training convergence rate.

Firstly, the decay weight function is set in the objective function of the agent’s training to combine both types of methods, and both RL and imitation learning (IL) are considered to guide the agent's behavior when updating the policy. Second, this study designs a coupling utilization method between the demonstration trajectory and the training experience, so that samples from both aspects can be combined during the agent’s learning process, and the utilization rate of the data and the agent’s learning speed can be improved.

The method is superior to other algorithms in terms of convergence speed and decision stability, avoiding training from scratch for reward values, and breaking through the restrictions brought by demonstration data.

The agent can adapt to dynamic scenes through exploration and trial-and-error mechanisms based on the experience of demonstrating trajectories. The demonstration data set used in IL and the experience samples obtained in the process of RL are coupled and used to improve the data utilization efficiency and the generalization ability of the agent.

This paper aims to explore the impact of COVID-19 on office space in Johannesburg. This study further explores the role of changing work practices in the office sector in South Africa because of the pandemic and its impact on future office space use planning and management.

To understand the footprints that the COVID-19 pandemic has left on the office space market in Johannesburg, this study uses semi-structured interviews, which were administered to corporate office users, and a thematic analysis was adopted to understand the views, perspectives and expectations of office users.

The study showed that space users perceive COVID-19-induced remote working as having benefits, opportunities and challenges. A notable shift in office space utilization has emerged, with employees increasingly opting for roles that permit remote work. This newfound flexibility, accommodating both on-site and remote work, often makes working from home more appealing than traditional office environments that may no longer align with users’ preferences for office spaces.

The study is limited to Johannesburg, South Africa, and may not apply to other African markets. Ten in-depth interviews were conducted, and analysis and results were deduced; this may be considered a limitation of this study.

The pandemic’s impact has brought about irreversible changes, compelling policymakers and business leaders to strategize and prepare. This proactive stance aims to prevent avoidable challenges for employees and companies during future pandemics. A thoughtful approach to the post-pandemic world can usher positive changes in the office and property sector. This includes the coexistence of both remote work and on-site working models.

This paper provides valuable insight into some of the outcomes of the COVID-19 pandemic in South Africa that are essential for future office space use planning and management. The insights from this study extend the literature and provide novel knowledge based on an office sector in the “global south.”

This article takes into account object identification, enhanced visual feature optimization, cost effectiveness and speed selection in response to terrain conditions. Neither supervised machine learning nor manual engineering are used in this work. Instead, the OTV educates itself without instruction from humans or labeling. Beyond its link to stopping distance and lateral mobility, choosing the right speed is crucial. One of the biggest problems with autonomous operations is accurate perception. Obstacle avoidance is typically the focus of perceptive technology. The vehicle's shock is nonetheless controlled by the terrain's roughness at high speeds. The precision needed to recognize difficult terrain is far higher than the accuracy needed to avoid obstacles.

Robots that can drive unattended in an unfamiliar environment should be used for the Orbital Transfer Vehicle (OTV) for the clearance of space debris. In recent years, OTV research has attracted more attention and revealed several insights for robot systems in various applications. Improvements to advanced assistance systems like lane departure warning and intelligent speed adaptation systems are eagerly sought after by the industry, particularly space enterprises. OTV serves as a research basis for advancements in machine learning, computer vision, sensor data fusion, path planning, decision making and intelligent autonomous behavior from a computer science perspective. In the framework of autonomous OTV, this study offers a few perceptual technologies for autonomous driving in this study.

One of the most important steps in the functioning of autonomous OTVs and aid systems is the recognition of barriers, such as other satellites. Using sensors to perceive its surroundings, an autonomous car decides how to operate on its own. Driver-assistance systems like adaptive cruise control and stop-and-go must be able to distinguish between stationary and moving objects surrounding the OTV.

One of the most important steps in the functioning of autonomous OTVs and aid systems is the recognition of barriers, such as other satellites. Using sensors to perceive its surroundings, an autonomous car decides how to operate on its own. Driver-assistance systems like adaptive cruise control and stop-and-go must be able to distinguish between stationary and moving objects surrounding the OTV.

The purpose of this paper is to model a process for moving toward sustainable ecosystem service decisions in a Coastal Biodiversity and discuss the directions of the process for decision-makers to apply in ocean ecosystem services.

After the development of theoretical approaches to understand their prospects for the future development of ecosystem services, the authors worked on a process for developing factors for sustainable decision-making. It uses the Delphi method to develop all the factors supported by six dimensions in two specific moments: deductive-inductive and inductive-deductive.

This process of modeling the factors expands the possibility of adaptive governance to make prior and subsequent decisions using factors related to dimensions, stakeholders and benefits, risks, opportunities and costs.

Considering the limitations, future studies could use another database to widen the view in terms of the studies, factors, dimensions and other additional information to maintain the evolution of this process in ocean ecosystem services decision-making. Another limitation arose in the number of projects and experts defining the factors. This may prevent the opportunity to have more impact in terms of future decisions if more sources are used in the market. In addition, time and the access to experts during this modeling process demonstrate a limitation, as does the time for feedback.

This set of factors developed for adaptive governance decision-making can be applied to develop a prior alignment of stakeholder interests with sustainable practices.

This set of factors developed with the intervention of experts reinforces the importance of sustainable collective decisions on ocean ecosystem services. This is a joint approach with participants in the NextOcean project, sponsored by the European Commissions (EC)’s Horizon 2020 program. An Earth Observation-based Consortia aims to create sustainable value for Space, Land and Oceans.

This modeling process generated dimensions and factors to support adaptive governance stakeholders in making sustainable decisions in a coastal biodiversity zone.

This study aims to explore the use of a double diamond design method to engage the industry in a sector-wide response to the issues of food waste as constructed by consumers. This particular design method is achieved by an exploration of a collective intelligence-participatory design (CIPD) project to engage industry participants in understanding and responding to consumers’ perceptions of the role of packaging in reducing food waste.

Using the UK Design Council’s double diamond design method as a guiding conceptual principle, the project recruited industry participants from medium to large food businesses across various food categories. Two scoping workshops with industry were held prior to the initiation of a 12-stage project (n = 57), and then two industry workshops were held (n = 4 and 14). Eighty participants completed an online qualitative survey, and 23 industry participants took part in a Think Tank Sprint Series. The Think Tanks used participatory design approaches to understand barriers and opportunities for change within food industry sub-sectors and test the feasibility and acceptability of package designs to reduce consumer waste.

For CIPD to work for complex problems involving industry, it is vital that stakeholders across macro- and micro-subsystems are involved and that adequate time is allowed to address that complexity. Using both the right tools for engagement and the involvement of the right mix of representatives across various sectors of industry is critical to reducing blame shift. The process of divergence and convergence allowed clear insight into the long-term multi-pronged approach needed for the complex problem.

Participatory design has been useful within various behaviour change settings. This paper has demonstrated the application of the double diamond model in a social marketing setting, adding value to an industry-wide project that included government, peak bodies, manufacturing and production and retailers.

This paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of nodes and deploy in free space for reliable trajectory planning.

Traditional PRM is modified by developing a decision-making strategy for the selection of optimal nodes w.r.t. the complexity of the environment and deploying the optimal number of nodes outside the closed segment. Subsequently, the generated trajectory is made smoother by implementing the modified Bezier curve technique, which selects an optimal number of control points near the sharp turns for the reliable convergence of the trajectory that reduces the sum of the robot’s turning angles.

The proposed technique is compared with state-of-the-art techniques that show the reduction of computational load by 12.46%, the number of sharp turns by 100%, the number of collisions by 100% and increase the velocity parameter by 19.91%.

The proposed adaptive technique provides a better solution for autonomous navigation of unmanned ground vehicles, transportation, warehouse applications, etc.