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In spite of the fact that literature shows that big data analytics (BDA) pass on a distinct corporate ability, little is thought about their performance impacts, specifically logical conditions. Establishing this research in the dynamic capability view (DCV) and corporate culture and dependent on an sample of 310 Indian production industries, the purpose of this paper is to experimentally study the impacts of BDA on corporate social performance (CSP) and corporate green performance (CGP) using variance-based structural equation modeling (for example, PLS).

A questionnaire was used to accumulate data sets to examine research hypothesis. The authors pre-examined the survey with six scholastics and six directors from production firms in India. With the help of their sources of data, the authors have adjusted their wordings to improve the transparency and guarantee that length of the survey is accurate. Finally, the questionnaire was prepared for definite data collection.

The authors conclude that BDA has noteworthy effect on CSP/CGP. Notwithstanding, the authors did not find proof for directing role of flexible direction and control direction in the connections among BDA and CSP/CGP. This research offers a more nuanced comprehension of the performance ramifications of BDA, and in this way, it is tending to the critical inquiries of how and when BDA can improve in supply chains.

This investigation makes helpful commitments to the BDA research and its effect on CSP/CGP. To the authors’ best of information, this is the first hypothesis-focused approach to clarify the effect of BDA on ecological and social supportability. Second, this investigation likewise gives empirical proof that BDA impact on CSP/CGP and is free of flexible or control direction of the industry.

Humanoids have become the center of attraction for many researchers dealing with robotics investigations by their ability to replace human efforts in critical interventions. As a result, navigation and path planning has emerged as one of the most promising area of research for humanoid models. In this paper, a fuzzy logic controller hybridized with genetic algorithm (GA) has been proposed for path planning of a humanoid robot to avoid obstacles present in a cluttered environment and reach the target location successfully. The paper aims to discuss these issues.

Here, sensor outputs for nearest obstacle distances and bearing angle of the humanoid are first fed as inputs to the fuzzy logic controller, and first turning angle (TA) is obtained as an intermediate output. In the second step, the first TA derived from the fuzzy logic controller is again supplied to the GA controller along with other inputs and second TA is obtained as the final output. The developed hybrid controller has been tested in a V-REP simulation platform, and the simulation results are verified in an experimental setup.

By implementation of the proposed hybrid controller, the humanoid has reached its defined target position successfully by avoiding the obstacles present in the arena both in simulation and experimental platforms. The results obtained from simulation and experimental platforms are compared in terms of path length and time taken with each other, and close agreements have been observed with minimal percentage of errors.

Humanoids are considered more efficient than their wheeled robotic forms by their ability to mimic human behavior. The current research deals with the development of a novel hybrid controller considering fuzzy logic and GA for navigational analysis of a humanoid robot. The developed control scheme has been tested in both simulation and real-time environments and proper agreements have been found between the results obtained from them. The proposed approach can also be applied to other humanoid forms and the technique can serve as a pioneer art in humanoid navigation.

To navigate humanoid robots in complex arenas, a significant level of intelligence is required which needs proper integration of computational intelligence with the robot's controller. This paper describes the use of a combination of genetic algorithm and neural network for navigational control of a humanoid robot in given cluttered environments.

The experimental work involved in the current study has been done by a NAO humanoid robot in laboratory conditions and simulation work has been done by the help of V-REP software. Here, a genetic algorithm controller is first used to generate an initial turning angle for the robot and then the genetic algorithm controller is hybridized with a neural network controller to generate the final turning angle.

From the simulation and experimental results, satisfactory agreements have been observed in terms of navigational parameters with minimal error limits that justify the proper working of the proposed hybrid controller.

With a lack of sufficient literature on humanoid navigation, the proposed hybrid controller is supposed to act as a guiding way towards the design and development of more robust controllers in the near future.

Innovation and entrepreneurship are regarded as the key drivers to steer the engine of economic development in any nation. As a result, to understand the context and process of innovation and entrepreneurship there has been a steady rise in scientific literature and empirical studies. The purpose of this paper is to study the trends and progress of academic research on innovation and entrepreneurship in India by identifying the key articles, journals, authors and institutions.

Scientometric methods especially bibliometrics is used, for measuring the maturity of this research field in the country. The paper studies the research landscape in innovation and entrepreneurship in India by doing a bibliometric analysis using data from publications indexed in the Scopus database from the year 2000 to 2018. The study takes a multidisciplinary review of the literature in innovation and entrepreneurship research in India and could be used as a reference for future studies in this theme.

The study finds an increase in the scholarly studies in innovation and entrepreneurship in India in the last decade. It was also found that a large number of publications were joint-authored and collaborations between Indian and foreign universities is happening. The paper also highlights the authorship patterns, top journals and the most cited papers.

A major limitation of this study is that it has considered publications which are indexed in Scopus. This paper has contributed by highlighting the growth of studies in the field of innovation and entrepreneurship in the Indian context. The results can be used by future studies in this area as a starting point to highlight the nature of this research area.

The study attempts to present a trend analysis of published literature on innovation and entrepreneurship in India.