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There is much debate in the literature about how the performance of Islamic banks (IBs) should be measured. Basically, IBs’ business models are different from that of conventional banks; thus, the performance of IBs should be measured by using a Sharīʿah-based approach. This paper considers zakat (Islamic tax) as an alternative indicator to measure the performance of IBs. This paper aims to examine whether zakat ratios can be used as Islamic performance (ISPER) indicators for IBs besides the conventional performance (COPER) indicators.

The investigation covered a sample of 214 yearly observations of 37 IBs located in Indonesia, Malaysia, Bahrain, Saudi Arabia and the United Arab Emirates for the period 2007–2015. This study used a single-factor congeneric model and confirmatory factor analysis, performed using the AMOS 23.0 software.

The findings assert that the discriminant validity of multi-bank performance, as measured by ISPER [zakat on assets (ZOA) and zakat on equity (ZOE)] and COPER indicators (return on assets, return on equity and operational efficiency in terms of assets), is very high. Hence, ISPER and COPER measurements are valid, either together to measure the multi-performance of IBs from both the Islamic and conventional perspectives, or independently as each measurement is valid to measure the Islamic and conventional performance if it is used separately.

This paper does not investigate whether the findings are constant across time. This represents one of the limitations of this study.

It is strongly recommended that IBs calculate and disclose zakat ratios, particularly ZOA and ZOE, in their annual reports. Researchers and academicians should use these ratios for measuring the ISPER of IBs, either along with COPER or separately.

Empirical evidence is provided in this paper on the development and validity of zakat ratios as ISPER indicators in the Islamic banking industry. Zakat ratios are suitable indicators that can measure IBs’ performance and achieve the goals of IBs as well as those of Islamic economics. Technically, zakat has a dynamic ability to reflect the profitability of IBs. The more the IBs generate profit, the more they pay zakat. Furthermore, the greater the total assets of IBs, the higher the amount of zakat that they should pay. Thus, zakat ratios can be used as profitability measurements as in the case of tax ratios.

The impact of volatility crush can be devastating to an option buyer and results in a substantial capital loss, even with a directionally correct strategy. As a result, most volatility plays are for option sellers, but the profit they can achieve is limited and the sellers carry unlimited risk. This paper aims to demonstrate the dynamics of implied volatility (IV) as being influenced by effects of persistence, leverage, market sentiment and liquidity. From the exploratory factor analysis (EFA), they extract four constructs and the results from the confirmatory factor analysis (CFA) indicated a good model fit for the constructs.

This section describes the methodology used for conducting the study. This includes the study area, study approach, sources of data, sampling technique and the method of data analysis.

Although there is extensive literature on methods for estimating IV dynamics during earnings announcement, few researchers have looked at the impact of expected market maker move, IV differential and IV Rank on the IV path after the earnings announcement. One reason for this research gap is because of the recent introduction of weekly options for equities by the Chicago Board of Options Exchange (CBOE) back in late 2010. Even then, the CBOE only released weekly options four individual equities – Bank of America (BAC.N), Apple (AAPL.O), Citigroup (C.N) and US-listed shares of BP (BP.L) (BP.N). The introduction of weekly options provided more trading flexibility and precision timing from shorter durations. This automatically expanded expiration choices, which in turned offered greater access and flexibility from the perspective of trading volatility during earnings announcement. This study has demonstrated the impact of including market sentiment and liquidity into the forecasting model for IV during earnings. This understanding in turn helps traders to formulate strategies that can circumvent the undefined risk associated with trading options strategies such as writing strangles.

The first limitation of the study is that the firms included in the study are relatively large, and the results of the study can therefore not be generalized to medium sized and small firms. The second limitation lies in the current sample size, which in many cases was not enough to be able to draw reliable conclusions on. Scaling the sample size up is only a function of time and effort. This is easily overcome and should not be a limitation in the future. The third limitation concerns the measurement of the variables. Under the assumption of a normal distribution of returns (i.e. stock prices follow a random walk process), which means that the distribution of returns is symmetrical, one can estimate the probabilities of potential gains or losses associated with each amount. This means the standard deviation of securities returns, which is called historical volatility and is usually calculated as a moving average, can be used as a risk indicator. The prices used for the calculations are usually the closing prices, but Parkinson (1980) suggests that the day’s high and low prices would provide a better estimate of real volatility. One can also refine the analysis with high-frequency data. Such data enable the avoidance of the bias stemming from the use of closing (or opening) prices, but they have only been available for a relatively short time. The length of the observation period is another topic that is still under debate. There are no criteria that enable one to conclude that volatility calculated in relation to mean returns over 20 trading days (or one month) and then annualized is any more or less representative than volatility calculated over 130 trading days (or six months) and then annualized, or even than volatility measured directly over 260 trading days (one year). Nonetheless, the guidelines adopted in this study represent the best practices of researchers thus far.

This study has indicated that an earnings announcement can provide a volatility mispricing opportunity to allow an investor to profit from a sudden, sharp drop in IV. More specifically, the methodology developed by Tan and Bing is now well supported both empirically and theoretically in terms of qualifying opportunities that can be profitable because of the volatility crush. Conventionally, the option strategy of shorting strangles carries unlimited theoretical risk; however, the methodology has demonstrated that this risk can be substantially reduced if followed judiciously. This profitable strategy relies on a set of qualifying parameters including liquidity, premium collection, volatility differential, expected market move and market sentiment. Building upon this framework, the understanding of the effects of persistence and leverage resulted in further reducing the risk associated with trading options during earnings announcements. As a guideline, the sentiment and liquidity variables help to qualify a trade and the effects of persistence and leverage help to close the qualified trade.

The authors find a positive association between the effects of market sentiment, liquidity, persistence and leverage in the dynamics of IV during earnings announcement. These findings substantiate further the four factors that influence IV dynamics during earnings announcement and conclude that just looking at persistence and leverage alone will not generate profitable trading opportunities.

The impact of volatility crush can be devastating to the option buyer with substantial capital loss, even for a directionally correct strategy. As a result, most volatility plays are for option sellers; however, the profit is limited and the sellers carry unlimited risk. The authors demonstrate the dynamics of IV as being influenced by effects of persistence, leverage, market sentiment and liquidity. From the EFA, they extracted four constructs and the results from the CFA indicated a good model fit for the constructs. Using EFA, CFA and Bayesian analysis, how this model can help investors formulate the right strategy to achieve the best risk/reward mix is demonstrated. Using Bayesian estimation and IV differential to proxy for differences of opinion about term structures in option pricing, the authors find a positive association among the effects of market sentiment, liquidity, persistence and leverage in the dynamics of IV during earnings announcement.

The Student Leadership Competencies Inventory consists of eight scales, each corresponding to its relevant leadership construct within the Student Leadership Competencies framework (Seemiller, 2013). Due to the increasing use of the framework and associated inventory in leadership development programs in higher education, we conducted a thorough analysis of the psychometric properties within each scale. Specifically, using a national dataset of university student responses, we analyzed internal reliability statistics, and conducted exploratory factor analysis with varimax rotation and maximum likelihood confirmatory factor analysis for each of the eight scales. Our results suggested that all scales, overall, possess sufficient strength to be considered valid measures of the leadership constructs within the Inventory, with some notably high co-variances between certain sub-scale factors in several scales.

The Purpose of the study was to investigate the construct validity and internal consistency of the LaMI among staff in the context of elderly care in Sweden.

Questionnaire data from a longitudinal study of staff working in elderly care were used. Data were collected using the Leadership and Management Inventory. First data collection was for explorative factor analysis (n = 1,149), and the second collection, one year later, was for confirmatory factor analysis (n = 1,061).

The explorative factor analysis resulted in a two-factor solution that explained 70.2% of the total variance. Different models were tested in the confirmatory factor analysis. The final model, a two-factor solution where three items were omitted, showed acceptable results.

The instrument measures both leadership and management performance and can be used to continually measure managers’ performances as perceived by staff to identify areas for development.

This study aims to develop a model for readiness measurement and to study readiness levels for online testing of undergraduate students in Thailand’s distance education programs.

In total, 870 undergraduate students enrolled in the 2022 academic year of a Thai university were sampled for the study. The samples were divided into two groups: Group 1 comprised 432 students who underwent exploratory factor analysis (EFA) and Group 2 comprised 438 students who underwent second-order confirmatory factor analysis (CFA). Both were multi-stage random samples. Descriptive statistics, item-total correlations (ITCs), coefficient correlations, EFA and second-order CFA were used.

The readiness for the online testing model comprised 5 factors and 33 indicators. These included self-efficacy (SE) in utilizing technology (nine indicators), self-directed learning (SL) for readiness testing (six indicators), adequacy of technology (AT) for testing (five indicators), acceptance of online testing (AC) (seven indicators) and readiness training for testing (six indicators). The model was congruent with empirical data, and the survey results indicated that students were highly prepared at the “high” level.

This study disclosed several factors and indicators involved in the readiness for online testing. The university may use these findings in preparing its students for online testing for better achievement.

These findings may serve as a framework for the analysis of the readiness issues for online testing of undergraduate students and also offer guidance to the universities preparing to offer online testing.

Cyber-physical systems (CPS) offer improved delivery of facilities management (FM) mandates through their advanced computational capabilities. Using second-order multivariate analysis, this study explores the drivers of the espousal of this digital technology for FM.

The study employed a deductive approach underpinned by a post-positivist philosophical stance using a quantitative technique aided by a well-structured questionnaire. Data retrieved from the study’s respondents were analysed with descriptive statistics, Kruskal–Wallis h-test, exploratory factor analysis and confirmatory factor analysis.

The result of the analysis conducted portrayed evidence of convergence and good measures while the estimated model parameters all attained prescribed fit indexes. Also, it was revealed that the most influential drivers for the uptake of CPS for FM mandates are resource allocation for system procurement, top management willingness, system stability and compatibility with the previous system.

The study’s findings unravel the necessitated parameters that would instigate the adoption of CPS for the delivery of FM activities by organisations while also propelling the digital transformation of construction project delivery at the post-occupancy phase.

This is the first study to empirically assess the propelling measures for incorporating CPS for FM using second-order multivariate analysis. Consequently, the study's outcome helps close this knowledge gap.

The impact of Goods and Service Tax (GST) on the motor and pump exports in the Coimbatore region is measured in this study using various parameters and scales. The data collected from exporters were used to identify the pros and cons of GST, stating their opinions on variables considered by the researchers through extensive literature on GST and exports.

The data were collected from 220 motors and pump exporters through a field survey from the month of January to September 2021. The impacts have been measured using principal component analysis (PCA) and confirmatory factor analysis (CFA). The factor analyses and CFA will derive the positive and negative impact of GST determined through critical empirical evidence in this study. Also, the problems faced by the exporters allied to GST, which the authors could not include in the questionnaire due to certain reasons, are concisely apportioned and discussed.

The study depicts the major advantages of GST, such as harmonized system, long-run performance, reduction in logistics cost, check-post operation, bonds and ease of doing business. Also, it highlights the disadvantages of GST, such as biases in the indirect tax system, the reimbursement of duty drawback being late or pending and document filing was still a tedious job under the GST regime.

The unavailability of considerable literature on the impact of GST on Indian exports signifies the novelty of this research. So far, this is the first empirical attempt to measure the impact of GST on exports which is a unique and original attempt to highlight the problem that lies under the GST regime and the necessary reforms the tax structure needs in the context of Indian exports.

Pedagogical leadership (PL) has been regarded as the best leadership style in the education sector. Thus, the aim of this study was to develop and validate a pedagogical leadership scale (PLS).

Two distinct approaches (inductive and deductive) were utilized. First, a review of the literature was conducted, and then qualitative data were collected through interviews, and their responses were categorized into 40 items. These items were thematized using exploratory factor analysis (EFA) by involving 300 participants. To examine the fitness of the scale, the researchers conducted a confirmatory factor analysis (CFA) with 470 participants.

EFA discovered a total variance of 64.766% for four factors. In CFA, RMSEA, NFI, RFI, NNFI, CFI, GFI and AGFI values were accepted. The highest correlation was found among constructs of PL. Path analysis revealed PL affected social, professional, intellectual and academic capitals. The correlations between the PLS and psychological empowerment demonstrated the theoretically predicted relationships with these variables. Thus, with the initial evidence of a valid and reliable PLS, a pool of 32 items under 4 factors (social, academic, professional and intellectual capital) were developed.

Despite the management of childhood education requiring the practice of PL, it is underexplored in childhood schools, particularly to our knowledge, no studies have been conducted to develop and confirm the PLS in Ethiopia.

The present study is intended to assess the risk factors associated with digital buying. Also aims to design and develop an instrument to assess the digital buyers risk factor score (DBRFS) in light of pandemic.

Present investigation uses a quantitative approach to achieve the stated objectives. The survey instrument for the purpose of assessing risk factors associated with digital buying was developed in two phases. The present study adopts theory of planned behaviour (TPB), built based on the theory of reasoned action (TRA). The data were collected and analysed considering 500 valid responses, sampling unit being digital buyers using social media platforms in tyre-II city of India. The data collection was undertaken between June 2021 and August 2021. The instrument is designed and validated using exploratory factor analysis (EFA) followed by confirmatory factor analysis (CFA).

The present research identified six perceived risk factors that are associated with digital buying; contractual risk, social risk, psychological risk, perceived quality risk, financial risk and time risk. The DBRFS of male is 3.7585, while female is 3.7137. Thus, risk taking by the male and female is at par. For the age group 15–30, DBRFS is 3.6761, while age group 31–45 noted as 3.7889 and for the 46–50 age groups it is measured as 3.9649.

The marketers are expected to have the knowledge about how people responds to the pandemic. The outcome of the research helps to understand consumer behaviour but disentangling consumer’s “black box” is challenging especially during global distress. The present study outcome helps the digital shopkeepers to respond positively to meet the needs of digital buying.

The scale development and to quantify the DBRFS. A deeper understanding of about digital consumers during pandemics will help digital shopkeepers to connect issues related digital buying.

The importance of sustainable development has become increasingly significant in today’s fast-paced world. The 17 sustainable development goals (SDGs) aim to solve a range of environmental, economic and social challenges, which requires global collaboration among governments and private organisations. In light of this, social entrepreneurship has garnered significant attention as it combines the social purpose of non-profits with the market-driven approach of for-profits to address SDG goals. Yet the cognitive processes underpinning the career decisions of social entrepreneurs remain underexplored. This study aims to develop and validate a scale to measure social entrepreneurial career decisions based on the appraisal of perceived challenges.

The study followed the steps of tool development and was carried out in three phases: item analysis, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

The final 20-item scale focuses on the appraisal components in pre-entry social entrepreneurial career decision-making and has four factors, which are relevance, coping potential, knowledge and resources and normative significance.

The study contributes to the literature on entrepreneurial cognition, specifically focusing on social entrepreneurship. The scale could guide model testing and quantitative research in social entrepreneurial cognition. The four-dimensional structure identified in the study may also have implications for researchers interested in the antecedents and effects of social entrepreneurial decision-making.

Accurate measurement of cognitive appraisal is necessary to understand the perceived challenges and thought processes of potential social entrepreneurs. The scale could be used to examine the cognitive appraisal patterns among students. Social entrepreneurship educators and policymakers can use the scale to design and assess educational programs.

Distinct from existing studies, this scale offers a multidimensional approach that captures the stages of career decision-making, providing a robust tool to enhance our understanding of the decision-making dynamics in social entrepreneurship.