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Supply chain finance (SCF) has become a vital ingredient that fosters growth and provides flexibility to the global supply chain. Thus, it becomes essential to understand the factors that contribute to the success of the supply chain finance ecosystem (SCFE). This study aims to identify the critical success factors (CSFs) for the development of an efficient and effective SCFE. Based on their characteristics, the study intends to classify the factors into constructs and further establish a hierarchical relationship among the CSFs.

The study is based on empirical data collected from 221 respondents based on administered questionnaires. Exploratory factor analysis (EFA) is carried out on 16 selected factors (out of 21 proposed factors) based on the feedback of the experts and the factors were classified into four constructs. The total interpretive structural modeling (TISM) model was developed by identifying and finalizing CSFs of the SCFE. The model developed a hierarchical relationship between the various factors.

The study identified significant CSFs for the efficient and effective SCF ecosystem. Four constructs were developed by analyzing CSFs using the EFA. The finalized 16 CSFs modeled through the TISM and further hierarchical relationship established between the CSFs concludes that governmental policies and sectoral growth are the strongest driving forces and financial attractiveness is the weakest driving force. Based on the CSFs and the constructs identified, it was found that for the success of the SCF ecosystem, the existence of an economic ecosystem provides a facilitating framework for the overall development of the SCFE. Also, the trustworthiness among the partners fosters better relationships and results in financial feasibility and offers business opportunities for all the stakeholders.

This study will help the SCF partners across the globe understand the CSFs that ensure development of mutually beneficial SCF ecosystems and provide flexibility to the supply chain partners. The CSFs would provide insights to the policymakers and the financial intermediaries for providing a conducive environment for the development of a better SCF ecosystem. Also, the buyers and sellers would understand the CSFs that would develop better relationships among them and ultimately help in development of business across the globe.

The study identifies the CSFs for the SCF ecosystem. The study ascertains the significant factors and classifies them into clusters using EFA. Unlike the literature available, the paper develops the hierarchical relationship between the CSFs and develops a model for an efficient and effective SCF ecosystem.

The purpose of this paper is to identify the challenges surrounding the implementation of digital technology (DT) agri-food supply chain (AFSC) and explore how these challenges relate to the various sustainability dimensions. Additionally, it aims to assess how these challenges are interconnected in relation to achieving sustainable development goals (SDGs).

The study employs a mixed-method approach utilizing the EFA-ISM-Fuzzy DEMATEL technique. To support and validate the findings, exploratory factor analysis (EFA) categorized 12 critical challenges in sustainable dimensions from 141 participants' responses. Furthermore, interpretive structural modeling (ISM) and decision-making trial and evaluation (DEMATEL) methods were used to obtain the interrelationship and hierarchical structure of the challenges.

The study identified 12 critical challenges while adopting DT in AFSC. These challenges were categorized into four sustainable dimensions: technological, economic, environmental and social. These challenges hinder the achievement of SDGs as well. Lack of regulatory and policy framework with security and privacy issues were the key challenges faced while adopting DT. These observations emphasize the necessity for government and policymakers to prioritize tackling the identified challenges to successfully endorse and execute DT initiatives in AFSC while also fulfilling the SDGs.

The implication underscores the need for collaboration among various stakeholders, such as governments, policymakers, businesses and researchers. By collectively addressing these challenges, DT can be leveraged optimally, fostering sustainable practices and making progress toward achieving the SDGs within the AFSC.

The study uses a combination technique of EFA and ISM-DEMATEL to identify the challenges faced in Indian AFSC while adopting DT and categorizes the interrelation between the challenges along with fulfilling the SDGs.

The purpose of this study is twofold. First, this research explores the level of Islamic financial literacy of customers in the context of Islamic banking. Second, this study examines the determinants of customer adoption of Islamic banking in Turkey.

This study gathered sample data from 409 participants determined using the purposive sampling method. In the study, first, the reflective measurement model is used to examine the reliability, validity and multicollinearity problems of the variables. Then, AMOS structural equation model (SEM) is used to reveal the relationship between Islamic financial literacy and Islamic banking services. Additionally, this study performed both descriptive and inferential analysis to understand customer literacy about Islamic banking and their adoption behavior of Islamic banking.

The results obtained from descriptive assessment indicate that Turkish customers of Islamic banking possess sufficient literacy about Islamic banking. Moreover, the results from SEM indicate that the adoption of Islamic banking by customers is significantly predicted by the role of Sharia Board management, Islamic banking and purpose of financial institution, religious factor and legitimacy of Islamic financial system.

This study focuses only on the level of knowledge and perceptions of customers who have accounts in Islamic banks or financial institutions in Turkey. It does not focus on the level of knowledge and perception of Muslims who do not have accounts in Islamic banks and financial institutions.

Previous studies on Islamic banking are mostly studies that investigate customers’ perceptions of the Islamic banking system and why individuals prefer Islamic banks. In particular, studies examining the relationship between individuals’ Islamic financial literacy level and Islamic banking preferences are limited. This study is considered to be an original study as it investigates the relationship between the Islamic financial literacy level of individuals and their adoption of Islamic banking services in Turkey.

The purpose of this study is to frame the dimensions of the external institutional environment, namely, cultural-cognitive, normative and regulative dimensions as the main actors in the organisational field. More precisely, Libyan commercial banks have been identified as empirical evidence, to identify constraints of the institutional environment governing the behaviour and decision-making of commercial banks, when adopting Islamic financial transactions.

A questionnaire has been designed for 14 Libyan commercial banks which is distributed to the Board of Directors, managers, directors of departments, and personnel. The exploratory factor analysis (EFA) and the measurement model by using the first-order and second-order confirmatory factor analysis (CFA) have been applied as essential steps to embody the conceptual framework and test the research hypotheses.

The results of the EFA indicated sufficient correlation among the dimensions of the external environment. The CFA supported this study’s hypotheses. The modelling showed that the cultural-cognitive, normative and regulative dimensions are institutional constraints impeding Libyan commercial banks’ adoption of Islamic financial transactions. Interestingly, the findings of the CFA align with the EFA findings in supporting the conceptual framework of the research. They portrayed that the cultural-cognitive dimension has been identified by explicit and implicit cognition.

This study systematically embodies the dimensions of the external institutional environment, namely, cultural-cognitive, normative and regulative dimensions, as the main factors in the organisational field to be conceptually rich lenses to investigate social considerations to reinforce institutional thought broadly. The results of this study were consistent with extant Islamic financial literature, reflecting symmetry and similarity across commercial banks, particularly at the first stage of adopting Islamic financial transactions.

This chapter focusses on the identification of sustainability factors. Out of the 77 variables used in the questionnaire for collection of the information, on sustainability of financial innovation in e-payment system (EPS), the important factors are identified and derived using exploratory factor analysis (EFA). This chapter further presents validation of the identified factors through confirmatory factor analysis (CFA). Based on the identified factors, a model for EPS is proposed. The chapter also presents a scale developed based on identified factors.

Physical environments, especially the sound environments of ILSs on a university campus, have become increasingly important in satisfying the diverse needs of students. Poor sound environments are widely acknowledged to lead to inefficient and underutilised spaces and to negatively influence students' learning outcomes. This study proposes two hypotheses to explore whether students' sound environment perceptions are related to their individual characteristics and whether students' preferences for the type of ILS are related to their sound environment sensitivities.

An investigation through a questionnaire survey has been conducted on both students' individual characteristics affecting their sound environment perceptions in informal learning spaces (ILSs) of a university campus and their sensitivities to the sound environments in ILSs affecting their preferences for the type of ILSs.

The research findings indicate that students' sound environment perceptions are associated with some of their individual characteristics. In addition, the results show that students' sound environment sensitivities affect their preferences for the type of ILS they occupy.

This study could help architects and managers of university learning spaces to provide better sound environments for students, thereby improving their learning outcomes. The article contributes valuable insights into the correlation between students' individual characteristics, sound environment perceptions and preferences for ILSs. The research findings add to the existing knowledge in this field and offer practical implications for enhancing design and management of university learning environments.

In 2019, Generation Z (Gen Z) accounted for 32% of the world population, as per the report by Bloomberg, Gen Z in India is world's largest with 472 million people, still there is very limited research conducted to explain their intention to visit heritage sites. This paper aims to report the findings of an empirical research focussing on Gen Z Indians' intention to visit heritage sites by applying theory of planned behaviour (TPB) with two additional constructs, i.e. environmental concern (EC) and environmental friendly activities (EFA).

As a fundamental theoretical framework, the TPB model is used. Data consists of responses of 434 Gen Z Indians which were collected through online questionnaires. Using structural equation modelling (SEM) technique, the measurement and structural model were tested with the help of AMOS 22 and SPSS 25 software.

The results of SEM indicate that the hypothesized relationships between attitude (AT), subjective norms (SN), EC, EFA and intention to visit heritage sites were all supported. However, perceived behavioural control (PBC) did not influence intention.

The study's findings have substantial practical implications for organizations/travel companies that primarily deal in heritage sites. The findings of this study contribute to the body of knowledge about intention to visit heritage sites. As the study focuses mostly on Gene Z Indians, it is difficult to extrapolate the findings to other countries.

This paper will help the researchers and practitioners to understand the Gen Z Indians' intention of visiting heritage sites. To the best of the authors' knowledge, this is the first study that predicts intention of Gen Z Indians to visit heritage sites.

Previous studies highlighted a shortage of scale to measure digital citizenship among Indians. Accordingly, this study examined the psychometric properties of Jones and Mitchell’s (2016) digital citizenship scale in the Indian context with the help of two independent studies.

In the first study, the factorial validity of the scale was determined using the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). In the second study, Cronbach’s alpha (CA) and composite reliability (CR) values checked the internal consistency reliability of the scale. Also, convergent, discriminant and criterion validity were examined.

EFA recommended a two-factor structure explaining 58.219% of the total variance. The item loadings varied from 0.540 to 0.793. The Indian version of the scale showed one variation. In the original digital citizenship scale, the seventh statement (“I like to present myself online as someone was making positive choices”) was part of factor 1 (online respect); however, this study suggested that the seventh statement should be included in factor 2 (online civic engagement). In the second study, the acceptable (>0.70) values of CA and CR concluded the internal consistency reliability of the scale. The convergent validity was suggested by average variance explained values (>0.50). In addition, as expected, the Indian version of the digital citizenship scale reported a statistically significant positive correlation with Internet self-efficacy and a considerable negative relationship with cyberbullying. These findings concluded the criterion validity of the scale.

The Indian version of the digital citizenship scale showed appreciable psychometric properties among Indian students.

The use of three-dimensional virtual worlds (3DVWs) is increasingly becoming a common practice in language education to provide digital learning environments for second-language (L2) communicative classes. This study aimed to identify the key factors underlying communication in 3DVWs that can improve the communication skills of L2 learners.

To achieve this, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to validate the identified factors affecting communication in 3DVWs. A self-reported questionnaire with 47 items on a five-point Likert scale was administered to 513 pre-service teachers, teachers and lecturers in the field of language education.

The results of the EFA revealed four factors that contribute to communication in 3DVWs, namely learner motivation, interaction pattern, language development and learner autonomy. CFA results provided support for the updated model, with statistically significant Chi-square results (χ² (df = 83) = 181.049, p < 0.001) indicating a good fit between the model and the data.

The findings suggest that the four EFA-derived parameters are valid and can assist instructional designers and L2 instructors in creating 3DVWs that enhance L2 learners' communication abilities. This study provides valuable insights for educators, instructional designers and researchers in the field of language education and technology-enhanced learning.

This study aims to establish an assessment model to measure big data readiness in the public sector, specifically targeting local governments at the provincial and city/regency levels. Additionally, the study aims to gain valuable insights into the readiness of selected local governments in Indonesia by using the established assessment model.

This study uses a mixed-method approach, using focus group discussions (FGDs), surveys and exploratory factor analysis (EFA) to establish the assessment model. The FGDs involve gathering perspectives on readiness variables from experts in academia, government and practice, whereas the survey collects data from a sample of selected local governments using a questionnaire developed based on the variables obtained in FGDs. The EFA is used on survey data to condense the variables into a smaller set of dimensions or factors. Ultimately, the assessment model is applied to evaluate the level of big data readiness among the selected Indonesian local governments.

FGDs identify 32 essential variables for evaluating the readiness of local governments to adopt big data. Subsequently, EFA reduces this number by five and organizes the remaining variables into four factors: big data strategy, policy and collaboration, infrastructure and human resources and data collection and utilization. The application of the assessment model reveals that the overall readiness for big data in the selected local governments is primarily moderate, with those in the Java cluster displaying higher readiness. In addition, the data collection and utilization factor achieves the highest score among the four factors.

This study offers an assessment model for evaluating big data readiness within local governments by combining perspectives from big data experts in academia, government and practice.