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The aim of this paper is to discuss the views of black and ethnic minority school leaders about the Investing in Diversity program, a black‐led program developed in 2004 to address the underrepresentation of black leaders in the London schools. Major themes are identified from interviews with black and South Asian women graduates of the program and recommendations made for leadership development strategies to help aspiring and current black and global majority headteachers “bring who they are” to their leadership.

Qualitative case study data about the Investing in Diversity program include document analysis of curriculum modules and participant observation of the weekend residential, survey satisfaction data from several cohorts, and face‐to‐face interviews with a purposive sample of seven headteachers from African Caribbean, African, and South Asian backgrounds who completed the Investing in Diversity program six‐seven years ago. These semi‐structured individual interviews were conducted in the spring of 2012 during an all‐day visit to their schools and focused on barriers and supports in their career path, approach to leadership, and their views on their leadership preparation.

Participants identified black and ethnic minority headteachers as role models, the importance of mentoring and informal networks, and opportunities to lead as supports to their career path to headship. Many of their long‐term informal networks were established with other BME colleagues who attended Investing in Diversity. Barriers included subtle (and not so subtle) discrimination from parents, teachers, and administrators for some of the participants.

Observational studies and interview studies, which included a bigger sample of black and ethnic minority headteachers, would extend this research.

This study provides suggestions for schools and local authorities about leadership preparation strategies that make a difference for aspiring BME leaders.

There is a paucity of research on the views of British BME headteachers. This study adds to the research base on BME leadership development in Britain and contributes to international research on self‐defined black leadership perspectives.

Despite efforts to reduce environmental pollution and wasteful fossil fuel use, electric vehicles (EVs) are still rare on the road. Why is it so challenging to get widespread EV adoption? One significant factor on which it heavily depends is one's awareness and understanding of EVs. However, due to an absolute lack of knowledge on the part of the populace, this factor becomes a huge impediment to the uptake of EVs. A systematic review of the electronic database Scopus for the years 2003–2022 was carried out on ‘EV awareness and adoption of EV’ while considering the ‘Preferred Reporting Items for Systematic Reviews and Meta-analysis’ (PRISMA) standards. A three-step identification process resulted in the ultimate detection of 41 papers, which were then thoroughly examined. A conceptual framework that encompasses the three key awareness aspects that influence EV adoption is developed. To encourage greater uniformity among EV researchers, this study's conclusions serve as a foundation for operationalising upcoming research efforts within a predetermined framework. The authors must therefore be optimistic that lingering technological, legislative, cultural, behavioural and business-model barriers may be overcome over time through widespread dissemination of knowledge and awareness related to EVs, making it possible for everyone to switch to greener, more economical and more efficient transportation solutions.

Inconel 718 (IN718) is a high-performance nickel-based superalloy with high oxidation-corrosion-temperature resistance, high strength (tensile, fatigue, creep and rupture), durability, toughness, hardness and dimensional stability, which is difficult to machine with traditional fabrication methods. To overcome these difficulties, wire electrical discharge machining (WEDM), one of the modern manufacturing methods, is used.

Main performance criteria in WEDM; material removal rate (MRR), cutting speed, surface roughness, cutting width (kerf) and wire wear rate. In this study, the effect of processing parameters on kerf and MRR because of processing IN718 in WEDM was investigated. Machining parameters, voltage, wire feed rate and dielectric fluid pressure were determined. Deionized water was used as a dielectric fluid and 0.3 mm brass wire was used as wire in the experiments. Gray Relational Analysis (GRA), which is one of the multi-criteria decision-making methods, has been applied for the optimization of the machining parameters in the cutting process with the WEDM. Analysis of variance (ANOVA) was used to determine the effect percentages of the cut-off parameters.

The parameter with the highest effect was determined as tension with a rate of 76.95% for kerf and 91.21% for MRR.

The novel approach uses Taguchi-based GRA optimization as a result of cutting IN718 with WEDM, reducing cost and time consumption.

The purpose of this paper is to develop a blockchain-based data capture and transmission system that will collect real-time power consumption data from a household electrical appliance and transfer it securely to a local server for energy analytics such as forecasting.

The data capture system is composed of two current transformer (CT) sensors connected to two different electrical appliances. The CT sensors send the power readings to two Arduino microcontrollers which in turn connect to a Raspberry-Pi for aggregating the data. Blockchain is then enabled onto the Raspberry-Pi through a Java API so that the data are transmitted securely to a server. The server provides real-time visualization of the data as well as prediction using the multi-layer perceptron (MLP) and long short term memory (LSTM) algorithms.

The results for the blockchain analysis demonstrate that when the data readings are transmitted in smaller blocks, the security is much greater as compared with blocks of larger size. To assess the accuracy of the prediction algorithms data were collected for a 20 min interval to train the model and the algorithms were evaluated using the sliding window approach. The mean average percentage error (MAPE) was used to assess the accuracy of the algorithms and a MAPE of 1.62% and 1.99% was obtained for the LSTM and MLP algorithms, respectively.

A detailed performance analysis of the blockchain-based transmission model using time complexity, throughput and latency as well as energy forecasting has been performed.

This paper aims to study the color change kinetics of lac dye in response to pH and food spoilage metabolites (ammonia, lactic acid and tyramine) for its potential application in intelligent food packaging.

UV-Vis spectroscopy was used to study the color change of dye solution. Ratio of absorbance of dye solution at 528 nm (peak of ionized form) to absorbance at 488 nm (peak of unionized form) was used to study the color change. Color change kinetics was studied in terms of change in absorbance ratio (A528/A488) with time using zero- and first-order reaction kinetics. An indicator was prepared by incorporating lac dye in agarose membrane to validate the result of study for monitoring quality of raw milk.

Dye was orange-red in acidic medium (pH: 2 to 5) and exhibited absorbance peak at 488 nm. It turned purple in alkaline medium (pH: 7 to10) and exhibited absorbance peak at 528 nm. The change in absorbance ratio with pH followed zero-order model. Acid dissociation constant (pKa) of dye was found to be 6.3. Color change of dye in response to ammonia and tyramine followed zero-order reaction kinetics, whereas for lactic acid, the first-order model was found best. In the validation part, the color of the indicator label changed from purple to orange-red when the milk gets spoiled.

The study opens a new application area for lac dye. The results suggest that lac dye has potential to be used as an indicator in intelligent food packaging for detection of spoilage in seafood, meat, poultry and milk.

This paper aims to attempt to empirically investigate the impact of privatization on the performance of central public sector enterprises in India. Further attempt is made to explore whether privatization is a necessary or sufficient condition for improvement of performance of central public sector enterprises.

The scope of the study is limited to financial and operating performance analysis of 206 central public sector enterprises in India. Multiple regression analysis has been used to determine the magnitude and direction of relationship between dependent and independent variables and identify variables other than privatization which affects performance.

The study found that financial and operational performance of firms has improved significantly due to privatization. Further, firm-specific factors and other parallel reforms adopted by enterprises have significantly influenced their performance. The established regression model is highly significant with F-ratio of 31.825 at 99% significance level. The degree of explanation of the model is robust with adjusted R² at 0.956 implying that only 4.40% of explanation in the dependent variable cannot be explained by designated independent/explanatory variables.

The study would be useful to public policymakers to reach to a policy view on whether further disinvestment/privatization of central public sector enterprises need to be continued, and if so, then to what extent and direction.

The purpose of this paper is to review several influential empirical studies that examine the performance of state-owned enterprises (SOEs). The paper undertakes a citation analysis of journals, authors and titles in the area of privatization and firm performance in general, and assesses the impact of privatization on the performance of SOEs in particular.

The methodology is based on a systematic and structured review of over 100 papers published in economics, public management, business strategy and related social sciences. The systematic review is based on citation analysis of journals, authors and titles. The journal and author citation counts were tabulated by leveraging the databases of SCImago Journal Rankings and Google Scholar and filtered it to find out the most highly cited journals and authors. The structured review is based on the framing opinion with respect to major findings, variables selected, measurement techniques and statistical tools applied by different researchers. The impact is measured through coding a value “P” in case of positive effects, “N” in case of negative effects and “NT” in case the study found both positive and negative effects.

The citation analysis reveals that American Economic Review, Journal of Financial Economics, Review of Financial Studies and Journal of Finance as the top-cited journals, and Megginson and Netter (3,468), Megginson et al. (1,737), Djankov and Murrell (1,356), Boardman and Vining (1,320), Balsam et al. (1,094) and DeWenter and Malatesta (1,018) as the top-cited authors in this particular research field. While majority research studies have revealed a significant improvement in the performance of SOEs in the post-privatization period, few studies have reserved their impact as neutral or even negative in some respects.

Given that economic transitions, corporate governance, and performance of SOEs have attracted a great attention from public management and business strategy scholars in recent years, this paper aims to summarize a large number of empirical studies that examine the performance of SOEs. The paper would be useful to future researchers especially the beginners and early career researchers in terms of its current trends, selection of variables, measurement techniques and statistical tools applied.