Purpose: This study aims to develop cause-and-effect relationships among the critical success factors (CSFs) of fintech adoption and rank these CSFs based on their importance in the model. Design/methodology/approach: To achieve the objectives of the study, the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) approach was used. The data was collected from 16 experts using a questionnaire. Findings: The findings demonstrated the interrelationships among the CSFs. In total, 16 critical factors were recognized as causal factors, and the remaining eight were considered effect factors. The CSFs were ranked based on their importance in fintech adoption. Originality/value: This study is novel as it investigates CSFs of fintech adoption using FDEMATEL, and it contributes to understanding the nature of these factors and how they affect fintech adoption. The findings propose a significant basis to deepen fintech adoption and deliver a clue to design a practical framework for fintech adoption.

Purpose: This paper aims to shed light on the consequences of customer accounting (CA) information usage for strategic purposes on organizational performance.Design/methodology/approach: This is an empirical study with data from 106 Jordanian services organizations. Quantitative data were obtained to investigate the relationship between CA information items and organizational performance in the context of Jordan.Findings: The results show that the level of CA information usage (customer profitability, lifetime customer profitability analysis and valuation of customers as assets) impacts on organizational performance. CA information usage leads to better organizational performance. Also, the findings demonstrate a different effect of CA information items on diverse dimensions of organizational performance.Originality/value: The findings will help academics and managers to achieve higher organizational performance.

Purpose: This research attempts to profoundly understand the factors influencing the usage of e-tax declarations. Design/methodology/approach: In a cross-sectional survey, partial least square-structural equation modeling (PLS-SEM) is used to examine the hypotheses on 182 academic taxpayers working in Public Universities in Jordan. Findings: The findings indicate that knowledge, subjective norms, and attitude play a vital role in taxpayers’ usage of e-tax declarations. Moreover, knowledge confirms the power of the Theory of Planned Behavior (TPB), which helps predict people’s behavior. However, the results reveal that awareness does not moderate the previously mentioned relationship. Research limitations/implications: The sample size is limited, and the participants were academics who work at public universities. Therefore, it is advisable to study larger sample size to confirm the study’s results. Moreover, further research could diversify the sample in terms of occupation, digital divide, and e-literacy, as these factors may significantly impact e-tax declaration usage. A comparison across various groups would be beneficial in gaining a better understanding of the demographics and variables that impact the use of e-tax declarations. The second limitation is the collection of mainly quantitative data; collecting qualitative data to further understand the main factors that could affect the usage of e-services would play a role in supporting the study’s findings. Practical implications: This study provides strategic guidance for Jordanian policymakers in improving citizens’ acceptance of mandatory e-services usage by affecting their knowledge, attitude, and subjective norms. As a result, these practical suggestions positively influence taxpayers’ usage of e-services, which contributes to their usage of optional ones. E-service adoption rates may rise by emphasizing their benefits, such as improving equity, efficiency, life quality, and limiting adverse environmental effects. Originality/value: This study expands the scope of mandatory public e-services research.

Purpose: The purpose of this study is to examine the critical factors influencing blockchain implementation in supply chain networks. Although blockchain facilitates increased transparency, traceability and trust, adoption is still ambiguous and context dependent. This research differentiates between antecedents and outcomes to identify the necessary conditions for digital transformation success. Design/methodology/approach: Twelve technological, organisational and environmental factors were identified through a systematic review of leading research. A panel of 15 experts from the academic, consultancy and industrial fields assessed the relationships existing between these factors. The Decision-Making Trial and Evaluation Laboratory was used to map the direct and indirect influences and reveal the causal structure relevant to the adoption of blockchain. Findings: The four primary causal drivers – regulatory clarity, organisational readiness, relative advantage and competitive pressure – were viewed as facilitating blockchain adoption through investing and collaboration, at various levels of the supply chain. Technological elements such as scalability, interoperability and security were considered consequences of the drivers. Practical implications: It is crucial for managers to develop the capability and regulatory alignment of the organisation before focusing on technology optimisation. As it is with building any type of capability, an assessment of governance is necessary so perform cross-industry collaboration across the supply-chain ecosystem, to foster transparency and resiliency. Originality/value: By integrating the Technology–Organisation–Environment and Institutional Theory perspectives, the study proposes a combined framework that describes the ordered influences on blockchain adoption. The framework suggests benchmarking insights for strategic adoption and policy implementation in digital supply chains.