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Technology has disrupted many industries from the start of Industrialization era to the Industry 4.0 era. There has been an exponential growth in the technological front and people are talking about Industry 5.0. Digital transformation is a critical direction in which organizations will have to move toward in order to succeed in this competitive world. To make a smooth transition, firms must understand the basic building blocks of the digital transformation process and the key areas it touches upon namely customer experience, operational process and dynamic business models. Organizations will also have to identify the enablers of digital transformation which they can work on to smoothen the transformative process. Firms will also need the framework of digital transformation spelling out the roadmap for effective digital transformation. Firms on the urge to go for digital transformation will face numerous challenges in all the stages of implementation namely the initiation phase, the execution phase and the governance phase. A clear understanding of these challenges will help the firms to overcome or mitigate these challenges and be successful in their digital transformation process.

The unavoidable connection between automation and digitalization is already in the business horizon in the name of Industry 5.0. Industry 4.0, the robotic and technological revolution were largely hit among the manufacturing industries, but Industry 5.0 is meant for all sectors across ranges from manufacturing to services. Evolution from the days of mechanization (Industry 1.0) to smart factory (Industry 4.0) witnessed the improvisation of metrics related to efficiency and optimization. And now its turn for the balance between optimization and efficiency with the support from robots in assisting the smarter generation’s technologies and machineries and tools through Industry 5.0 in the domain of marketing too where the change is constant and dynamic would be more accommodative to opportunities and challenges through the next wave of 5.0. The disruption by Industry 5.0 will change existing nature of marketing in terms of customer experience, supply chain, procurement, product development, retail operations, etc. The market which predominantly flourishes with the help of customers in co-creation is going to have robot as bystander with the intervention of this Revolution 5.0 which will level up the existing customer experience. Marketing by its nature demands the cooperation at multiple levels and is becoming easier prey for the Industry 5.0 revolution as it’s expected to create the cooperation between the humans and machines. Product development, customer engagement and customer experience will undergo the transformation due to this industry revolution and also there are other areas in the marketing domain to go through the impact are addressed in this chapter.

The purpose of this paper is to investigate the literature and statistical data on the Indian takeover code cum open offers market and break up the historical changes in takeover code into various phases for better understanding and decision making by mergers and acquisitions advisory, legal advisory, merchant bankers, investment bankers, business houses and academia.

The present study describes literature summary on takeover code and evaluates the growth phase of open offers through trend analysis with respect to amendments in Indian takeover code.

Since 14 years of takeover code presence in India, it evidences that there is an empirical support on growth phase in the open offers market.

The study is developed on the basis of Indian takeover regulations and Securities and Exchange Board of India takeover code to wake up the public shareholding and regulatory bodies, by better conveyance of historical review at one place.

This study is the first of its kind, dividing the complete history of Indian takeover code into various phases for review and identifying the gaps for future research. Further, the paper investigates and finds various untouched facts and variables in both literature and statistical data on open offers.

The Second Brazilian Printed Circuit Association Seminar will take place in Rio de Janeiro from 21–23 September 1988. Papers will be presented on the following topics:

India has acquired global leadership in renewable energy (RE) deployment because of its commitment to achieve 175 GW of installed capacity by 2022. Entrepreneurship driven by innovation and policy push is essential for energy sector transition. Despite policy focus on the diffusion of RE technology, there are several challenges that plague innovation and RE entrepreneurship development in Gujarat, India. Hence, the purpose of this study is to apply an empirical approach to identify major challenges faced by RE entrepreneurs operating in Gujarat.

An empirical correlational analysis has been taken up to explore individual- and firm-level characteristics of 54 RE entrepreneurs in Gujarat across six districts. Moreover, challenges faced by them related to policy and market have been investigated. Gujarat has been selected as the study area, as it has an installed capacity of 11,000 MW and houses around 11% of the total RE potential of the country.

Major challenges faced by RE entrepreneurs in Gujarat comprise of financial risks, market incumbency, low profitability, uncertainty of demand and lack of skilled labour.

This study offers an empirical grounding to policymakers for fostering an ecosystem of entrepreneurship and innovation specific to RE sector in India and other developing nations.

This study is unique, as previous studies on sustainability-driven entrepreneurship are majorly theoretical and lack empirical foundations. Moreover, there are even lesser quantitative studies exploring challenges to RE entrepreneurship specific to India.

The purpose of this paper is to investigate the potential for using chitin and chitosan sustainable materials to absorb copper from PCB manufacturing effluent and to report the results of an initial feasibility study aimed at demonstrating proof of concept.

Crab shells and prawn shells, both waste products of the seafood industry, as well as chitosan, were evaluated as potential absorbents for recovering copper present at low levels in the manufacturing effluent produced in a UK‐based PCB manufacturing facility. Various conditions were investigated and efforts were also made to recover absorbed copper via a regeneration process that enabled the metal to be electroplated from solution.

Although only a short feasibility study, conditions were found that enabled copper to be absorbed by the ground crab shells and chitosan and then subsequently recovered by electrowinning to produce the metal.

Although successful as a feasibility study, the experimental work highlighted the large number of variables that need to be investigated and optimised in order to obtain the most efficient copper capture and recovery. Further work needs to be carried out to determine these optimum conditions and to investigate the potential for recovery of other metals from a wider range of solutions.

The paper details how individual treatment technologies can be combined to enable a much more sustainable approach to PCB manufacturing which offers the benefits of reduced effluent metal levels, metal recovery and a novel use for another sector's waste products.

The purpose of this paper is to propose a novel data-driven approach for predicting energy performance of buildings that can address the scarcity of quality data, and consider the dynamic nature of building systems.

This paper proposes a reinforcing machine learning (ML) approach based on transfer learning (TL) to address these challenges. The proposed approach dynamically incorporates the data captured by the building management systems into the model to improve its accuracy.

It was shown that the proposed approach could improve the accuracy of the energy performance prediction compared to the conventional TL (non-reinforcing) approach by 19 percentage points in mean absolute percentage error.

The case study results confirm the practicality of the proposed approach and show that it outperforms the standard ML approach (with no transferred knowledge) when little data is available.

This approach contributes to the body of knowledge by addressing the limited data availability in the building sector using TL; and accounting for the dynamics of buildings’ energy performance by the reinforcing architecture. The proposed approach is implemented in a case study project based in London, UK.

The inappropriate lighting methods can have irreversible effects on artworks available in museums and exhibitions. Several factors affect the choice of the lighting system in the museums. By surveying all possible elements, this paper aims to propose a sustainability-based solution, as it relates to the development of artwork conservation, visual perception and energy efficiency during operation and maintenance (O&M).

The paper elicits optimal solutions out of the method presented based on functions and expert opinion to improve lighting quality in existing museums. To study the optimization, the energy consumption and life cycle cost (LCC) in both the proposed lighting and the existing lighting system are compared using HoneyBee and LadyBug plugins in GrassHopper, as well as BLCC5 energy cost estimation software.

The results indicated a practical method to select the most suitable solution for museum lighting. By applying the proposed solutions obtained from the case study, a significant reduction in energy consumption and LCC were achieved. Besides, greenhouse gases were remarkably decreased.

Providing the proper lighting systems for each museum is the issue that is given special attention during the facilities management. The quality of the lighting, energy consumption and costs are analyzed by the simulation software. It is recommended that the validity considerations of the practice are examined.

The present study tried to present an optimal method to choose the best lighting system by the simultaneous utilization of theoretical and practical aspects. The functional model is also introduced for performing the most effective method to enhance the lighting techniques in the art museums.

Arguments for the design of sustainable university buildings have emerged in South Africa. Energy being a major determinant of the sustainability of buildings, the purpose of this study was to examine the influence of various building and indoor environmental parameters on the energy performance of university buildings in South Africa.

A quantitative survey research method, administered within the context of university buildings in South Africa, was used. Data about 16 buildings from three universities were collected. Relevant, inferential statistical analyses were conducted to examine the relative influence of the building parameters on the energy consumed in the buildings. Also, regression models within building parameters were developed independently and in a combination that could be used to estimate energy consumption in the university buildings.

Findings suggested that building and indoor environmental parameters of humidity, indoor temperature, volume, illumination, and window width ratio (WWR), in that order, influenced energy consumption significantly, and also, had direct empirical relationships.

Optimising the building and indoor environmental parameters in design will enhance energy-efficiency in university buildings in South Africa.

This study contributes to the literature in terms of understanding the order of influence of building parameters on energy consumption in university buildings in the temperate climatic zone of South Africa. It also established empirical models between building and indoor environmental parameters and energy consumption, both independently and in combination, that could assist in designing energy-efficient and sustainable university buildings.