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Prisons offer a public health opportunity to access a group with multiple and complex needs and return them to the community with improved health. However, prisons are not conducive to optimal health and there are few frameworks to guide efforts. This study aims to generate insights into health literacy across a young adult prison population, specifically examining the level of limitations, barriers and characteristics associated with these limitations.

The study took place in a single prison in England for young adult men aged 18–21 years old. A mixed-methods design was adopted with 104 young men completing a quantitative survey and qualitative semi-structured interviews with 37 young men.

72% (n = 75) of young men scored as limited in their health literacy. Barriers included structural restrictions, limited access to formal support and social and natural disruptions. No demographic characteristics or smoking intentions/behaviours predicted limited health literacy, but characteristics of the prison were predictive. Physical problems (sleep, nausea, tiredness and headaches), mental health and well-being (anxiety, depression and affect) and somatisation problems were also predictive of limitations.

Prison healthcare services and commissioners should undertake regular health literacy needs assessments to support developments in reducing barriers to healthcare and increasing health improvement efforts. Action also requires greater political will and investment to consider broader action on the wider determinants of (prison) health.

The study provides a framework to understand and guide prison health efforts and highlights attention needed at the level of governments, prison leaders and their health systems.

The purpose of this paper is to understand current Shari'ah governance practices with the purpose of promoting greater understanding of some of the crucial issues and to provide relevant information in guiding the future development of Shari'ah governance system. The paper illustrates the state of Shari'ah governance practices in Malaysia, GCC countries (Kuwait, Bahrain, United Arab Emirates, Qatar and Saudi Arabia) and the UK by highlighting five main elements of good corporate governance that consist of independence, competency, transparency, disclosure and consistency.

Since the availability of secondary data on Shari'ah governance practices is very limited, a detailed survey questionnaire is generated for sourcing primary data from Islamic Financial Institutions (IFIs). The study utilizes descriptive analysis approach in extracting and analyzing the data and factual input derived from the questionnaire feedback.

The survey findings affirm that there are significant differences and diverse Shari'ah governance practices in the case countries. This position acknowledges that there are shortcomings and weaknesses to the existing governance framework which needs further enhancement and improvement.

The paper is a very useful source of information that may provide relevant guidelines in guiding the future development of Shari'ah governance practices in IFIs.

This paper provides fresh data and recent information on the actual Shari'ah governance practices of IFIs in three jurisdictions.

The purpose of this paper is to determine if a blended learning component can aid professional development, improve student ability and be approved at the foreign language level using the lesson study (LS) method at a university in Japan.

This paper introduces the three main theoretical concepts of blended learning, learner autonomy and technology in education before explaining the LS in full. Two groups of students were taught using almost identical syllabus. One group, the A group were taught using computer rooms for two semesters, while the other (B) group were taught in regular classrooms without computers for one semester then with computers for the following semester. The impact on the student and teacher will be discussed.

The findings of this study indicate that technology, in the form of a blended learning component added to a test-based curriculum, can enhance student test-scores, raise teacher and student awareness of technology and improve ability over a relatively short period.

This study emphasizes the power of technology in modern day education. Through blended learning methodology this study proposes that teachers in the modern age should adopt some form of technology into their teaching technique.

This paper is directed at teachers who are interested in integrating technology into their teaching techniques, through either computer aided or mobile assisted learning, but are slightly apprehensive in doing so. This study focuses on the introduction of an online and mobile digital flashcard tool called Quizlet. Very little literature exists in this field as the mobile application was only released in 2013.

This paper examines and forecasts correlations between cryptocurrencies and major fiat currencies using Generalized Autoregressive Score (GAS) time-varying copulas. The authors examine to which extent the multivariate GAS method captures the volatility persistence and the nonlinear interaction effects between cryptocurrencies and major fiat currencies.

The authors model tail dependence between conventional currencies and Bitcoin utilizing a Glosten-Jagannathan-Runkle Generalized Autoregressive Conditional Heteroscedastic model (GJR-GARCH)-GAS copula specification, which allows detecting the leptokurtic feature and clustering effects of currency returns distribution.

The authors' results show evidence of multiple tail dependence regimes, implying the unsuitability of applying static models to entirely describe the extreme dependence between Bitcoin and fiat currencies. Compared to the most common constant copulas, the authors find that the multivariate GAS copulas better forecast the volatility and dependency between cryptocurrencies and foreign exchange markets. Furthermore, based on the value-at-risk (VaR) and expected shortfall (ES) analyses, the authors show that the multivariate GAS models produce accurate risk measures by adding cryptocurrencies to a portfolio of fiat currencies.

This paper has two main contributions to the existing literature on cryptocurrencies. First, the authors empirically examine the tail dependence structure between common conventional currencies and bitcoin using GJR-GARCH GAS copulas which consider the leptokurtic feature and clustering effects of currency returns distribution. Second, by modeling VaR and ES, the authors test the implication of using time-varying models on the performance of currency portfolios, including cryptocurrencies.

This study aims to assess future prospects for Russian energy exports until 2040, as global energy markets are undergoing major changes, with possible impacts on Russia.

Qualitative and quantitative approaches are integrated under a proposed foresight framework. The qualitative method involves an expert survey aimed at identifying major energy trends and their influence on Russia. As the trends are validated, an algorithm is proposed to assess the contribution of separate trends to Russian energy exports.

Experimental quantitative scenarios are conducted to assess the prospects for Russian energy exports until 2040 under the given exogenous scenario calculations of the IEA. Factor analysis allows for an assessment of the contribution of separate factors in dynamics of net energy imports into the regional economies. The future prospects for fossil fuels’ exports on regional markets are considered. Priority markets for Russian energy exporters are identified.

The results of the paper may be used by decision-makers for adjustments in the system of government policy or corporate strategy.

The paper provides an algorithm to assess energy export flows to macroregions based upon the synthesis of quantitative and qualitative information. Experimental scenario calculations of the Russian fossil fuels’ exports are provided. Strategic decision-making map is elaborated.

The purpose of this paper is to evaluate the implementation of the service profit chain as an entrepreneurial marketing initiative within a defined franchise system. An objective is also to evaluate these initiatives against service quality dimensions. Despite recognition of the merits and advantages of service profit chain initiatives of retention, related sales and referrals, little research has empirically addressed the perceptions of franchisees regarding these initiatives.

Methodology includes the empirical analysis of evaluating the effectiveness of service profit chain implementation, primarily based on initiatives of retention, related sales and referrals. Research methodology comprises the survey approach, using electronic media and Surveypro analysis. This is facilitated by descriptive and inferential statistical techniques using SPSS version 11.0 data analysis. Inferential significance tests include the ANOVA Kruskal‐Wallis hypothesis test; and the Cronbach's coefficient alpha.

Hypothesis tests highlight the significance of a positive association between service profit chain initiatives and service quality. All service profit chain initiatives were deemed appropriate. Item analysis highlights specific dominant service profit chain initiatives, linking key relationship marketing and service quality themes.

Findings are indicative of implementation opportunities, including measurement of loyalty within the system, developing customer feedback and complaint systems, and communicating the value of service profit chain enhancement within the franchise system.

Originality includes cognizance of entrepreneurial orientation, relationships and service quality when implementing service profit chain initiatives. Concurrent research opportunities include the implementation of other entrepreneurial marketing initiatives, including relationship marketing and benchmarking for best practice.

The purpose of this paper is to shed fresh light into whether an energy commodity price index (ENFX) and energy blockchain-based crypto price index (ENCX) can be used to predict movements in the energy commodity and energy crypto market.

Using principal component analysis over daily data of crude oil, heating oil, natural gas and energy based cryptos, the ENFX and ENCX indices are constructed, where ENFX (ENCX) represents 94% (88%) of variability in energy commodity (energy crypto) prices.

Natural gas price movements were better explained by ENCX, and shared positive (negative) correlations with cryptos (crude oil and heating oil). Using a vector autoregressive model (VAR), while the 1-day lagged ENCX (ENFX) was significant in estimating current ENCX (ENFX) values, only lagged ENCX was significant in estimating current ENFX. Granger causality tests confirmed the two markets do not granger cause each other. One standard deviation shock in ENFX had a negative effect on ENCX. Weak forecasting results of the VAR model, support the two markets are not robust forecasters of each other. Robustness wise, the VAR model ranked lower than an autoregressive model, but higher than a random walk model.

Significant structural breaks at distinct dates in the two markets reinforce that the two markets do not help to predict each other. The findings are limited by the existence of bubbles (December 2017-January 2018) which were witnessed in energy blockchain-based crypto markets and natural gas, but not in crude oil and heating oil.

As per the authors’ knowledge, this is the first paper to analyze the relationship between leading energy commodities and energy blockchain-based crypto markets.

The purpose of this paper is investigate the dynamic linkages among industrial energy use, industrial value added, financial development (FD) and trade openness, in case of India. The study covers the annual frequency data on both aggregate and disaggregate variables for the period 1971–2016.

The autoregressive distributed lag bounds testing approach is applied to examine the long-run relation among variables under consideration. Also, Johansen and Juselius (1990) and vector error-correction mechanism results confirm the result of cointegration. Furthermore, non-linear relationship in the model is also tested.

It has been found that there exists long-run relationship among variables. Long-run estimates show that increasing FD leads to more energy uses. Hence, FD should be directed in such a way that it incentivises firms to invest in energy-efficient technology. Furthermore, it is also found that study supports the evidence of conservative hypothesis, which supports that the energy conservation policy should be adopted in the industrial sector. Energy efficiency programme needs to be designed very carefully to achieve a higher level of energy efficiency. This leads to a sustainable growth and low carbon emission.

This paper examines the recent trend in Indian industrial energy consumption and does a comprehensive analysis using a robust econometric method. We have developed a lucid model to examine the deriving factors of industrial energy consumption.

The purpose of this study is to investigate the predictability of crude oil price and shale oil production, in a bid to examine the possibility of bi-directional causality.

The study adopts a recently developed predictability model by Westerlund and Narayan (2015), which accounts for persistence, endogeneity and heteroscedasticity. It also accounts for structural breaks in the predictive models.

The empirical results show that only a unidirectional causal relationship from crude oil price to shale oil production exists. This happens as crude oil price appears to be a good predictor of shale oil production; however, shale oil production does not serve as a good predictor for crude oil price. Accounting for structural break was found to improve the predictability and forecast accuracy of the predictive model. Our result is robust to choice of crude oil price benchmarks (West Texas Intermediate, Brent, Dubai Fateh and Refiners’ Acquisition Cost) and their denominations (real or nominal).

The result implies that crude oil price must be considered when predicting shale oil production. Meanwhile, the non-significance of shale of production in crude oil price predictive model provides information to potential analyst, researchers and countries predicting crude oil price that failure to account for the effect of shale oil production would not have significant impact on the forecast accuracy of their models.

The study contributes originally to the literature on crude oil price–shale oil production in four major ways. First, it applies a recently developed predictability method by Westerlund and Narayan (2015), which is more suitable for dealing with persistence, conditional heteroscedasticity and endogeneity in the predictors. Second, it investigates existence of reverse causality between crude oil price and shale oil production. Third, it examines the variation in the response and effect of four major crude oil price benchmarks. Fourth, it considers crude oil price in both real and nominal terms.

The purpose of this paper is to shed light on how the relational capital of the information technology (IT) department creates value in organizations. In addition, the paper presents a multi-dimensional scale to measure and manage relational capital in the IT department.

In the first, explorative phase of the study, interviews and focus groups were conducted in order to develop a new measurement scale, which was subsequently tested through a survey questionnaire (212 respondents).

This research suggests that the relational capital of the IT department is a very important resource for the creation of strategic value. The statistical analysis conducted for this study confirmed the validity and reliability of the novel scale developed to measure this resource. Finally, thanks to factor analysis, five dimensions for the scale were identified.

Data were collected in northern Italy only. Further studies are advisable to confirm the validity of the constructs and scale.

The questionnaire presented in this study can be used to monitor the effectiveness of the interactions between the IT department and the other key actors involved in IT-enabled innovation. The adoption of this scale and its possible adaptation to specific, evolving business contexts may enhance the practitioner’s understanding of the role of relational capital in the value creation process.

The paper contributes to the “third stage” of intellectual capital research by concentrating on an intra-organizational level of analysis, which has been overlooked in the literature to date.