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The purpose of this chapter is to cover banking efficiency using the concept of the Meta frontier function and to study group and subgroup differences in the production technology. This study estimates the technical efficiency (TE) and technology gap ratios (TGRs) for banks in Islamic countries. Using the assumption of the convex hull of the Meta frontier production set using the virtual Meta frontier within the nonparametric approach as presented by Battese and Rao (2002), Battese et al. (2004), and O'Donnell et al. (2007, 2008) and after relaxing this assumption, the study investigates if there is a significant difference between these two methods. To overcome the deterministic criterion addressed to nonparametric approach, the bootstrapping technique has been applied. The first part of this chapter covers the analytical framework necessary for the definition of a Meta frontier function and its estimation using nonparametric data envelopment analysis (DEA) in the case where we impose the assumption of the convex production set and follows in the case of relaxation of this assumption. Then we estimated the TE and the TGR in concave and nonconcave Meta frontier cases by applying the Bootstrap-DEA approach. The empirical part will be reserved for highlighting these methods on data bank to study the technical and technological performance level and prove if there is a difference between the two methods. Three groups of banks namely commercial, investment, and Islamic banks in 17 Islamic countries over a period of 16 years between 1996 and 2011 are used.

This paper aims to investigate sustainability-led innovation, focusing on the interplay between product and process innovation for sustainability goals and the underlying supplier–customer relationships. Thus, the paper delves into sustainability-led innovation and how it affects supplier–customer relationships, and vice versa, thus providing a twofold perspective.

The textile industry is the empirical context of this study, which is exploratory research based on in-depth, semi-structured interviews with entrepreneurs, managers and experts in the textile industry.

In the textile industry, sustainability-led product innovation concerns mainly product durability and performance, product recyclability and the use of waste for new product development. Process innovation deals with circular economy, traceability and water and chemical use minimization. The paper also shows how sustainability-led innovation is implemented in more technical terms and regarding supplier–customer relationships.

The paper adopts an original perspective on how processes take place in the relationships between suppliers and customers, where there is no dominance of one actor, but innovation emerges from interdependence and interaction. Such perspective allows to provide an in-depth analysis of the supplier–customer relationships and underlying dynamics that affect sustainability-led innovation; moreover, the authors study how such innovation impacts supplier–customer relationships and the underlying relational dynamics. The value of the paper also stands in delivering a real representation of the innovation processes grounded in the textile industry.

Digital technologies create myriad innovation opportunities and have inspired the establishment of many new start-ups in recent years. Despite the growing knowledge on digital entrepreneurship, few studies explore how start-ups exploit these opportunities to achieve entrepreneurial success. The purpose of this paper is to explore start-ups’ capabilities for successful delivery of digital artefacts in a cloud computing infrastructure.

Empirical data were collected during a qualitative case study of an established start-up in the Chinese market by interviewing 41 interviewees. Informed by the notion of dynamic capabilities and using the Gioia methodology, the case firm's life cycle was analysed in detail.

The study identifies start-ups’ ordinary and dynamic capabilities for successful development and delivery of digital services. The findings provide insights into a portfolio of start-ups’ capabilities, namely adaptation, networking, reengineering and refinement.

The study suggests that start-ups’ capabilities and underlying entrepreneurial actions determine the degree to which adoption of digital technologies create and transfer value to customers. The study offers specific insights into how start-ups successfully develop and deliver digital artefacts in a cloud infrastructure based on entrepreneurs' prior expertise, vision and accumulated experience.

Stock market has always been lucrative for various investors. But, because of its speculative nature, it is difficult to predict the price movement. Investors have been using both fundamental and technical analysis to predict the prices. Fundamental analysis helps to study structured data of the company. Technical analysis helps to study price trends, and with the increasing and easy availability of unstructured data have made it important to study the market sentiment. Market sentiment has a major impact on the prices in short run. Hence, the purpose is to understand the market sentiment timely and effectively.

The research includes text mining and then creating various models for classification. The accuracy of these models is checked using confusion matrix.

Out of the six machine learning techniques used to create the classification model, kernel support vector machine gave the highest accuracy of 68%. This model can be now used to analyse the tweets, news and various other unstructured data to predict the price movement.

This study will help investors classify a news or a tweet into “positive”, “negative” or “neutral” quickly and determine the stock price trends.

Based on the principle of equality, individuals with disabilities have the right to equal job opportunities and career advancements and to actively participate in the economy like other members of society. This study aims to provide an integrated description of discriminatory occupational practices and behaviours that individuals with disabilities face. This study followed the descriptive analytical approach to achieve the objectives. A questionnaire was used for data collection purposes.

The target population for this study was male and female employees with disabilities working in the Jordanian Government sector for the years 2019–2022 in all governorates of Jordan. The sample method used was purposive-convenient random sampling, and the size of the sample valid for statistical analysis was n = 1,043. Using the Statistical Package for Social Sciences (v26), a number of statistical tests were conducted to infer the features of the researched phenomenon.

This study found an overall moderate level (mean = 2.76) of practices and behaviours of job discrimination against individuals with disabilities in the Jordanian public sector. All proposed practices and behaviours were at moderate levels of agreement, with the highest discriminatory behaviours being in the areas of training and learning opportunities (2.88), followed by job performance evaluation (2.84), work leave and vacation (2.75), integration and social participation (2.74), career advancement and promotion (2.73) and, last, the distribution of tasks and responsibilities (2.61). Furthermore, it was found that there are significant differences in the levels of discriminatory practices and behaviours towards people with physical disabilities, individuals with visual impairments and psychological disabilities, new employees at work and those with a low level of education. In addition, employees at higher administrative levels (manager, deputy/assistant manager and head of department/division) and workers in the southern and central governorates are exposed to the highest levels of discrimination.

Lack of data: There is often a lack of reliable and comprehensive data on employees with disabilities, making it difficult for researchers to accurately study and understand the experiences of this population. Stigma and discrimination: People with disabilities often face stigma and discrimination, which can make it challenging for researchers to engage with them and collect accurate information.

Moreover, it was found that the main agencies to which cases of discriminatory practices towards individuals with disabilities working in the Jordanian public sector are reported are the direct managers/supervisors (n = 381), the ministry to which the institution/department belongs (n = 278) and the Higher Council for the Rights of Persons with Disabilities (n = 261).

Supporting social inclusion: Employment can provide a sense of purpose, identity and social inclusion for people with disabilities, which can have a positive impact on their disabilities and overall quality of life. Improving diversity and inclusion: The inclusion of employees with disabilities can contribute to a more diverse and inclusive workplace, where all employees feel valued and respected.

This study found that discriminatory practices against employees with disabilities in the Jordanian public sector were largely because of a lack of awareness of reporting mechanisms and negative attitudes towards individuals with disabilities. This study proposes solutions such as raising awareness among non-disabled employees, implementing penalties for discriminatory behaviour and updating legislation for the rights of individuals with disabilities.

This paper aims to apply several data mining techniques for predicting the daily precision improvement of Jakarta Islamic Index (JKII) prices based on big data of symmetric volatility in Indonesia’s Islamic stock market.

This research uses big data mining techniques to predict daily precision improvement of JKII prices by applying the AdaBoost, K-nearest neighbor, random forest and artificial neural networks. This research uses big data with symmetric volatility as inputs in the predicting model, whereas the closing prices of JKII were used as the target outputs of daily precision improvement. For choosing the optimal prediction performance according to the criteria of the lowest prediction errors, this research uses four metrics of mean absolute error, mean squared error, root mean squared error and R-squared.

The experimental results determine that the optimal technique for predicting the daily precision improvement of the JKII prices in Indonesia’s Islamic stock market is the AdaBoost technique, which generates the optimal predicting performance with the lowest prediction errors, and provides the optimum knowledge from the big data of symmetric volatility in Indonesia’s Islamic stock market. In addition, the random forest technique is also considered another robust technique in predicting the daily precision improvement of the JKII prices as it delivers closer values to the optimal performance of the AdaBoost technique.

This research is filling the literature gap of the absence of using big data mining techniques in the prediction process of Islamic stock markets by delivering new operational techniques for predicting the daily stock precision improvement. Also, it helps investors to manage the optimal portfolios and to decrease the risk of trading in global Islamic stock markets based on using big data mining of symmetric volatility.

This research is a pioneer in using big data mining of symmetric volatility in the prediction of an Islamic stock market index.

This study aims at understanding how higher education institutions (HEIs) can contribute to sustainable development, by designing their programmes for bringing about a transformative impact on communities and students, and also to examine what alternative pedagogical approaches could be used for that. In the past decades, HEIs have increasingly created social innovation (SI) programmes, as a way to achieve United Nations Sustainable Development Goals. These community-oriented and field-based programmes are difficult to ally with conventional classroom education. This study explores how these programmes could integrate the participatory approach and what would be the benefits. It also investigates the effectiveness of the experiential learning approach for teaching sustainability.

A case study method is used to document SI projects initiated by an HEI programme in rural India.

It was found that the participatory approach contributes to empowering communities and also benefits the students in terms of academic, professional and personal growth. Empirical findings show that experiential learning is an efficient method to teach sustainability. Ultimately, both pedagogical approaches are found to be mutually beneficial.

This study fills a gap in the literature, by providing empirical evidence on how HEI can implement innovative educational strategies such as participatory approach and experiential learning in their programmes towards teaching sustainability. A conceptual model for HEI interested in developing similar programmes is also proposed. To the best of the authors’ knowledge, this study is one of the first studies focusing on the context of Indian HEI.

Demand for private investment in infrastructure, notably in the power sector remains high, and this is anticipated to expand with the passage of time. Very little research currently exists on the power sector and specifically the private sector influencing factors (PSIFs) for entering into public–private partnerships (PPPs). The purpose of this study is to explore influencing factors for private sector participation in PPP power projects in Ghana.

Using purposive and snowball sampling techniques, questionnaires were used to gather responses from experts in the PPP power sector domain in a two-round Delphi survey. Reliability analysis was conducted using Cronbach’s alpha coefficient and level of agreement tested using Kendall’s concordance. Mean score ranking, analysis of variance (ANOVA) and Chi-square test were the main analysis conducted on the influencing factors.

The most significant PSIFs were: obtaining of investment support; improvement in private sector’s international image; synergy with public sector; sharing of risks; and gaining of profits. From ANOVA results, all the influencing factors had no significant different perception between the number of years in PPP practice and the motivations for the private sector entering into PPP power projects. Using Chi-square, the association between the variables indicated they were statistically significant.

The findings in this study are significant for multinational power generation firms that seek to enter the Ghanaian energy sector to help fill the generation gap and deficit.

The output of this research contributes to the checklist of influencing factors for private sector participation in PPP power projects and enhances the development of PPP practice.

The purpose of the study is to assess if a policy of female inclusive education should be complemented with a policy of female ownership of bank accounts to fight female unemployment. The study therefore examines how female ownership of bank accounts moderates the incidence of female education on female unemployment.

The focus is on 44 sub-Saharan African (SSA) countries for the period 2004–2018 and the empirical evidence is based on interactive quantile regressions. The interactions are tailored such that female ownership of bank accounts influences the effect of female inclusive education on female unemployment.

From the empirical findings it is evident that female ownership of bank accounts does not effectively moderate female education in order to reduce female unemployment unless complementary policies are considered. The complementary policies should be in view of boosting the interaction between female education and female bank account ownership in increasing employment opportunities for the female gender and by extension, reducing female unemployment. The invalidity of the moderating effect is robust to the inclusion of more elements in the conditioning information set as well as accounting for other dimensions of endogeneity such as simultaneity and the unobserved heterogeneity. Policy implications are discussed.

This study contributes to the extant literature by assessing how female ownership of bank accounts complements female inclusive education to reduce female unemployment.