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Power converters are an integral part of the energy conversion process in solar photovoltaic (PV) systems which is used to match the solar PV generation with the load requirements. The increased penetration of renewable invokes intermittency in the generated power affecting the reliability and continuous energy supply of such converters. DC-DC converters deployed in solar PV systems impose stringent restrictions on supplied power, continuous operation and fault prediction scenarios by continuously observing state variables to ensure continuous operation of the converter.

A converter deployed for a mission-critical application has to ensure continuous regulated output for which the converter has to ensure fault-free operation. The fault diagnostic algorithm relies on the measurement of a state variable to assess the type of fault. In the same line, a predictive controller depends on the measurement of a state variable to predict the control variable of a converter system to regulate the converter output around a fixed or a variable reference. Consequently, both the fault diagnosis and the predictive control algorithms depend on the measurement of a state variable. Once measured, the available data can be used for both algorithms interchangeably.

The objective of this work is to integrate the fault diagnostic and the predictive control algorithms while sharing the measurement requirements of both these control algorithms. The integrated algorithms thus proposed could be applied to any converter with a single inductor in its energy buffer stage.

laboratory prototype is created to verify the feasibility of the integrated predictive control and fault diagnosis algorithm. As the proposed method combine the fault detection algorithm along with predictive control, a load step variation and manual fault creation methods are used to verify the feasibility of the converter as with the simulation analysis. The value for the capacitors and inductors were chosen based on the charge-second and volt-second balance equations obtained from the steady-state analysis of boost converter.

The purpose of this paper is to highlight the factors that aid e-training adoption in the Nigerian civil service.

This paper is based on a review of past literature from databases, reports, newspapers, magazines, etc. The literature recognised the role of perceived cost, computer self-efficacy, availability of resources and perceived support in e-training adoption. Using technology acceptance model (TAM), this paper explained the importance of these variables in e-training adoption in developing country context.

The authors found that the combined role of perceived cost, computer self-efficacy, technological infrastructure, Internet facilities, power supply, organisational support, technical support and government support is critical for e-training adoption in developing countries, particularly in Nigeria. Thus, the authors proposed the combination of these variables which would encourage future research on the use of TAM in technology adoption.

This paper gives an elaboration of the role of computer self-efficacy, perceived cost, availability of resources and perceived support with TAM as base of the framework. This provides researchers the opportunity to test the proposed framework empirically and further suggest other variables that can aid e-training adoption in the context of developing country.

The result of this paper can serve as a guide to managers and policymakers to have a better understanding of the requirements for e-training adoption, especially in developing countries. This will go a long way towards designing good policies that could maximise e-training results.

This paper adds to the existing literature on e-training and TAM with the suggestion of proposed variables.

The purpose of this study is to investigate the relationship between CO₂ emission and its core determinants, namely, economic growth, energy consumption and trade openness in the pre- and post-Kyoto Protocol era in the Indian economy.

The study uses the ARDL bounds test to analyze the long-run and short-run empirical relationship between the interested variables for the time period 1971-2013. A dummy variable representing the Kyoto Protocol regime has been included to examine the likely impact of international climate policies (Kyoto Protocol) in controlling and reducing CO₂ emission in India.

The empirical results indicate the possibility of increase in CO₂ emission from India even after the Kyoto Protocol regime. Evidence of inverted U-shaped relationship between CO₂ emission and economic growth (EKC hypothesis) has been confirmed. However, compared to increase in CO₂ emission, the magnitude of decrease due to improvement in economic growth is relatively lesser. Energy consumption and trade openness are also found to increase CO₂ emission.

The results indicate that there is a lack of commitment on the part of India to curtail CO₂ emission, which can be disastrous for future prosperity. Financing the renewable electricity generation, R&D subsidy and tax-free renewable energy seems to be imperative to address this catastrophic problem.

This study is the first attempt to analyze the impact of international climate policy (Kyoto Protocol) on CO₂ emission by incorporating a fixed dummy in the ARDL specifications.

The continuous increase in the discharges of carbon emissions (CO₂) in the global atmosphere and the likely negative consequences of this practice on the atmosphere draw the attention of researchers and policymakers to argue on the causes and perpetrators of CO₂ emissions. This paper aims to examine the impacts of hydropower consumption, FDI and manufacturing performance on CO₂ emissions in the Association of southeast Asian nations (ASEAN)-4 countries.

The study uses the data on variables, such as hydro-power consumption, FDI, manufacturing value added and CO₂ emissions spanning the period 1980–2015. Autoregressive Distributive Lag Bound test approach was used to assess the relationships among the variables.

The long run estimation of elasticities for all the countries indicates that the coefficient of hydro power consumption was found to be significantly related to CO₂ emissions only in Malaysia. Additionally, the coefficients manufacturing performance were found to be significant in influence the amount of CO₂ emission in all the ASEAN-4 countries. Furthermore, the coefficients of FDI inflows were found to be significant in explaining CO₂ emissions in Malaysia and the Philippines, respectively. In the short run, the estimated results show that all the variables were found to be significant in explaining CO₂ emissions in the countries under study.

Singapore is excluded from the ASEAN-4 due to insufficient data on hydro energy consumption.

The study recommends that as Hydro power energy is a clean source of renewable electricity. Its consumption indicates a negative relationship with CO₂ emissions. The countries should emphasize more on the use of hydro source of energy than the other sources which increase the rate of CO₂ emissions in the atmosphere.

As most of the relevant previous studies did not consider the simultaneous impact of hydro energy consumption, FDI and manufacturing value added on CO₂ emissions in the ASEAN-4, this study is an important contribution to the existing relevant literature.

This paper aims to propose a new MLI topology with reduced number of switches for photovoltaic applications. Multilevel inverters (MLIs) have been found to be prospective for renewable energy applications like photovoltaic cell, as they produce output voltage from numerous separate DC sources or capacitor banks with reduced total harmonic distortion (THD) because of a staircase like waveform. However, they endure from serious setbacks including larger number of capacitors, isolated DC sources, associated gate drivers and increased control difficulty for higher number of voltage levels.

This paper proposes a new three-phase multilevel DC-link inverter topology overpowering the previously mentioned problems. The proposed topology is designed for five and seven levels in Matlab/Simulink with gating pulse using multicarrier pulse width modulation. The hardware results are shown for a five-level MLI to witness the viability of the proposed MLI for medium voltage applications.

The comparison of the proposed topology with other conventional and other topologies in terms of switch count, DC sources and power loss has been made in this paper. The reduction of switches in proposed topology results in reduced power loss. The simulation and hardware show that the output voltage yields a very close sinusoidal voltage and lesser THD.

The proposed topology can be extended for any level of output voltage which is helpful for sustainable source application.

In this paper, we depart from extant conceptualisations of knowledge translation mechanisms to examine projects as a way to achieve effective knowledge transfer. Our empirical analysis focused on a university–industry research project in the automotive industry.

The empirical analysis was based on a qualitative investigation. We analysed material collected within a research project involving a partnership between two universities and Fiat-Chrysler Automotive (FCA), a multi-brand auto manufacturer with a product range covering several different market segments. We used three data collection techniques: internal document analysis, participant observation and semi-structured interviews.

Our findings show that, in a U-I research project, goals represent a key dimension to support knowledge translation. Defining the goal implies an ongoing negotiation process, where researchers and company employees work together, in order to converge towards a shared meaning of the goal. In this sense, goal orientation and goal-based interaction have significant implications for knowledge translation processes.

Studies to date have focussed on the concept of knowledge translation as a way to contextualise the transfer from the source of knowledge to the receiver and to interpret the knowledge to be exchanged. This study expands the understanding of knowledge translation mechanisms in university–industry research settings. It investigates the concept of projects as powerful knowledge translation mechanism in a dynamic and longitudinal perspective. Our contribution provides insight, reflecting on how the use of projects may represent a way to facilitate knowledge transfer and build up new ideas and solutions.

The present study aims to investigate the dynamic relationship between international tourist receipts, economic growth, energy use and carbon dioxide (CO₂) emissions in Pakistan over the period 1980-2016. Many researchers have investigated the link between tourism and CO₂ emissions, but there is no clear picture as the results are contradictory. This study is an attempt to compliment the literature related to tourism and environmental quality.

The study adopted the autoregressive distributed lagged (ARDL) model to investigate the short- and long-run estimates simultaneously. The study further applied Granger causality to find out the direction of causalities. To arrive at long-run robust estimates, the study used dynamic ordinary least squares (DOLS) model.

The results found that tourist receipts have no significant impact on environmental quality, while growth and energy consumption are the main determinants of CO₂ emissions in Pakistan. The Granger causality test confirmed unidirectional causalities from GDP and energy consumption toward CO₂ emissions, while tourist receipts do not affect environmental quality. DOLS technique confirmed the long-run estimates of ARDL model.

The result of the study complements the literature by adding new evidence regarding the nexus of tourism and environment. Findings of the study are important for policymakers and regulatory bodies to place their focus on the development of tourism sector (services sector) rather than energy-intensive manufacturing activities to sustain the growth of the country in higher quartiles, as tourism receipts have no significant negative externalities toward environment, while energy use is one of the key determinants of environmental degradation.

This study used time series data over the period 1980-2016 for Pakistan to inspect the dynamic relationship between tourist receipts, economic growth, energy consumption and CO₂ emissions.

The research is geared towards studying the impact of “GDP per capita (GDP)”, “energy consumption (EC)”, “human capital (HC)” and “trade openness (TO)” on India's ecological footprint (EF) from 1997–1998 to 2019–2020.

The autoregressive distributed lag model (ARDL) bound test was used to look at the short-run and long-term coefficients and the cointegration of the variables.

The results depicted a long-run connection between the variables. The long-run results found a favourable relationship between GDP, EC and EF, indicating that economic growth through heavy reliance on fossil fuels contributes to environmental unsustainability. An inverse relationship between HC, TO and EF was also observed, indicating that education fosters pro-environmental behaviour and leads to adopting cleaner technology that contributes to environmental sustainability.

The research substantiates India's pressing requirement for sustainable development, ensuring a harmonious balance between economic performance and environmental preservation. A carefully designed policy needs to be formulated to mitigate emissions stemming from growth in India. Policymakers are urged to implement measures that promote ecologically friendly tools, utilities and transportation to curb long-term environmental degradation.

The study is novel, incorporating an exhaustive review using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). This study further examines how India's EF is affected by its HC; the preceding literature has yet to discuss much about the connection between HC and the environment. Finally, the study employed advanced econometric techniques, namely the cointegration technique and ARDL model, to find the relationship between EF, GDP, HC, EC and TO.

The efficiency of each of an organization’s individual workers determines its effectiveness. The study aims to explore the relationship between human resource management (HRM) practices and organizational effectiveness with employee performance as a mediating variable.

Data were collected from 800 police officers in the Greater Accra and Tema regions. The data were supported by the hypothesized relationship. Construct reliability and validity was established through confirmatory factor analysis. The proposed model and hypotheses were evaluated using structural equation modeling.

The results show that career planning and employee performance were significantly related. Self-managed teams and employee performance were shown to be nonsignificantly related. Similarly, performance management and employee performance were shown to be nonsignificantly related. Employee performance significantly influenced organizational effectiveness. The results further indicate that employee performance mediates the relationship between HRM practices and organizational effectiveness.

The generalizability of the findings will be constrained due to the research’s police service focus and cross-sectional data.

The study’s findings will serve as valuable pointers for the police administration in the adoption, design and implementation of well-articulated and proactive HRM practices to improve the abilities, skills, knowledge and motivation of officer’s to inordinately enhance the effectiveness of the service.

By evidencing empirically that employee performance mediates the relationship between HRM practice and organizational effectiveness, the study extends the literature.

The increasing global competition, worldwide economic and political uncertainities, and continuously changing dynamics in business environment require companies act differently and differentiate via smart strategies in order to have sustainable operations, growth, and profitability. Therefore, firms should be more agile, creative, and adaptive in planning and strategizing their mid- to long-term business objectives.

In that regard, for the last decade globally many firms across all industries seek opportunities to utilize benefits of digitalization. Lately, COVID-19 has also accelerated companies' efforts and investments in digital platforms.

Today, supply chain and procurement functions are expected to have a strategic role for organizations contributing to management decisions. The digital transformation in procurement is promising to enhance and lean the total workflow of operations. Data analytics, artificial intelligence, robotics, and other emerging digital technologies are all highly powerful tools supporting strategic supply and supplier management, providing predictability for demand planning as well as value-based negotiation power to buyers.

On the other hand, there are still challenges and conflicts throughout this transformation process. Level of technological maturity, infrastructure and investment decisions, expertise and competency of procurement professionals, cultural adaptation, and compliance of related stakeholders are some of the key barriers that are addressed with a unique model in this chapter.

Digital era offers a lot of advantages to firms to improve their procurement facilities and practices while it may still take time both for the technologies to fully evolve and also for companies to adapt and embrace digitalization on their benefit.