An empirical assessment of enterprise information systems success in a developing country: the Jordanian experience

Trusting information systems in everyday work events - effects on cognitive resources, performance, and well-being

In today's data-intensive work environments, information systems are crucial for supporting workers. However, workers often do not rely on these systems but resort to workarounds. We argue that trust is essential for workers' reliance on information systems, positively affecting workers' cognitive resources, performance, and well-being. Moreover, we argue that the organisational context (accountability, distractions) and user-related factors qualify trust-outcome associations by affecting workers' trust calibration. In a preregistered study, we asked N = 291 employed users of information systems to re-experience prior everyday usage events (event reconstruction method) and assess event-specific trust in the system, work outcomes, and context conditions. Results confirmed the assumed association between trust in the information system and workers' ratings of both performance and well-being. Moreover, workers' technology competence and need for cognition - but not contextual conditions - qualified trust-outcome associations. Our results offer specific suggestions for achieving successful use of information systems at work.

The impact of management practices and industry 4.0 technologies on supply chain sustainability: A systematic review

This systematic review addresses a significant gap in the existing literature by examining the intricate relationship between management practices and Industry 4.0 technologies in shaping supply chain sustainability. While prior studies have explored their individual impacts, this review synthesizes and categorizes findings to identify nuanced trends that contribute to supply chain efficiency, waste reduction, and environmental footprints. To achieve the goal of the study, a rigorous search strategy was employed to select peer-reviewed journal articles focusing on total quality management, just-in-time, vendor-managed inventory, lean, manufacturer-led decentralized systems, blockchain, the internet of things, and big data in the context of supply chain sustainability. The selected studies underwent a thorough evaluation to ensure quality and relevance. The findings highlight key insights: the adoption of management practices, particularly total quality management and just-in-time, significantly contributes to reducing waste, enhancing efficiency, and minimizing environmental footprints across supply chains. Simultaneously, the integration of industry 4.0 technologies like blockchain, the Internet of things, and big data empowers data-driven decision-making, transparency, and traceability, amplifying sustainability efforts. In conclusion, this review contributes a novel perspective by synthesizing, categorizing, and analyzing the impact of management practices and Industry 4.0 technologies on supply chain sustainability. Its findings offer valuable insights for addressing contemporary challenges and advancing sustainable practices amid dynamic global scenarios.

Developing a success model of a social student relationship management system

Social media's significance in higher education has increased due to its capacity to enhance participation, communication, teamwork, and information sharing. Important notifications, updates, and reminders can be promptly received by all members of the university community, assuring that information is shared with everyone. The objective of this study is to develop a model for a Customer Relationship Management (CRM) system in higher education that is based on social media and intends to increase student satisfaction, loyalty, and profitability. It blends the idea of trust with Delone Mclean success model. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to evaluate the data that was gathered from 606 Jordanian private university students via an online survey. The findings demonstrated that user satisfaction affects social media usage and that system quality, information quality, service quality, and trust must all be considered to attain user satisfaction. This study examines how to create a CRM system based on social media in Jordanian universities. The study makes significant contribution to the development criteria for evaluating social media-based CRM systems in higher education institutions, and its broad conceptual model cloud be expanded and tested in future studies. This study is the first to investigate the use of social media to develop a CRM system for Jordanian universities. This is a novel study, and the work significantly create a set of criteria for evaluating social media-driven CRM systems in higher education. The study's expansive the model may serve as the base for more research in this field.

Gravitating towards Fintech: A study on Undergraduates using extended UTAUT model

One of the most pressing issues affecting people worldwide is the accessibility of financial services in the wake of the COVID-19 outbreak. While peoples' adoption of technological advancements has spiraled over time, the acceptance of Fintech services edged up for instilling resilience during the pandemic. Hence, the study aims at exhuming the Fintech adoption for sustainable financial inclusion among young undergraduate users through the Unified Theory of Acceptance and Use of Technology (UTAUT) model. To test the model, the researchers obtained data from 375 undergrads. The study adopted the Structural Equation Modelling (SEM) approach in AMOS software to examine the determinants that affect the users to embrace Fintech services. The findings revealed that performance expectancy, effort expectancy, and facilitating conditions significantly influence the students' intention to use Fintech, whereas, the users' facilitating condition and behavioral purposes positively influence them to use the financial technology. Interestingly, the social influence and personal innovativeness did not affect their intention to accept and adopt Fintech. Therefore, the study results will help explore the expectations, preferences, and actual level of use of Fintech among undergraduates and contribute to the escalation of Fintech use, leading to sustainable financial inclusion.

The effect of Arabic language type on banking chatbots adoption

Recently many banks around the world are adopting chatbots to communicate with their customers. However, the success of banking chatbots relay on customer adoption of this new technology. Although chatbots use in the banking sector is expanding globally, the Arabic world is still behind in using the technology, and chatbot applications in the Arab world are still immature. One reason behind this lag is the complexity of the Arabic language. This study comes to bridge the gap in the literature regarding what technology aspects affect customer adoption of bank chatbots in the Arabic world, and which type of Arabic language is the most effective in communicating with Arabic language speakers. UTAUT2 was used to figure what factors afect customer adoption. The data for this study was collected from two separate groups, with a total of 429 participants. Results showed that there is a significant difference between the model testing Arabic Fusha and Dialect Fusha. Results showed that Effort expectancy influences adoption only when dialect Arabic is used. Performance expectancy was also found to have no effect on the adoption of bank chatbot in both groups.

Profit prediction optimization using financial accounting information system by optimized DLSTM

Financial accounting information systems (FAISs) are one of the scientific fields where deep learning (DL) and swarm-based algorithms have recently seen increased use. Nevertheless, the application of these hybrid networks has become more challenging as a result of the heightened complexity imposed by extensive datasets. In order to tackle this issue, we present a new methodology that integrates the twin adjustable reinforced chimp optimization algorithm (TAR-CHOA) with deep long short-term memory (DLSTM) to forecast profits using FAISs. The main contribution of this research is the development of the TAR-CHOA algorithm, which improves the efficacy of profit prediction models. Moreover, due to the unavailability of an appropriate dataset for this particular problem, a newly formed dataset has been constructed by employing fifteen inputs based on the prior Chinese stock market Kaggle dataset. In this study, we have designed and assessed five DLSTM-based optimization algorithms, for forecasting financial accounting profit. The performance of various models has been evaluated and ranked for financial accounting profit prediction. According to our research, the best-performing DL-based model is DLSTM-TAR-CHOA. One constraint of our methodology is its dependence on historical financial accounting data, operating under the assumption that past patterns and relationships will persist in the future. Furthermore, it is important to note that the efficacy of our models may differ based on the distinct attributes and fluctuations observed in various financial markets. These identified limitations present potential avenues for future research to investigate alternative methodologies and broaden the extent of our findings.

An empirical investigation on actual usage of educational app: Based on quality dimensions and mobile self-efficacy

The intention of this research is to analyze the actual use of educational app by Chinese students for learning purpose. Based on DeLone & McLean (D&M) this study proposes and tests a research model which analyzes the actual use of educational apps using data collected from the 357 Chinese students. Structural equation modeling (SEM) was applied to examine the hypothesis. Findings specify that information quality, system quality, service quality, mobile self-efficacy, and personal innovativeness is considerably associated to intentions to use educational app which eventually influences actual usage of educational apps. Additionally, trust in educational apps strengthens the connection between intentions to use educational apps and actual use of educational apps by students for learning purposes. However, the perceived risk indicated an insignificant association between intention to use educational apps and actual use of educational apps. This study contributes to DeLone & McLean (D&M) model by examing the moderating role of perceived risk, trust in an educational app.

Healthcare knowledge graph construction: A systematic review of the state-of-the-art, open issues, and opportunities

The incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions. Knowledge graphs (KGs) have proven utility in this arena and are rooted in a number of healthcare applications to furnish better data representation and knowledge inference. However, in conjunction with a lack of a representative KG construction taxonomy, several existing approaches in this designated domain are inadequate and inferior. This paper is the first to provide a comprehensive taxonomy and a bird's eye view of healthcare KG construction. Additionally, a thorough examination of the current state-of-the-art techniques drawn from academic works relevant to various healthcare contexts is carried out. These techniques are critically evaluated in terms of methods used for knowledge extraction, types of the knowledge base and sources, and the incorporated evaluation protocols. Finally, several research findings and existing issues in the literature are reported and discussed, opening horizons for future research in this vibrant area.

Emotion detection of social data: APIs comparative study

The development of emotion detection technology has emerged as an efficient possibility in the corporate sector due to the nearly limitless uses of this new discipline, particularly with the unceasing propagation of social data. In recent years, the electronic marketplace has witnessed the establishment of various start-up businesses with an almost sole focus on building new commercial and open-source tools and APIs for emotion detection and recognition. Yet, these tools and APIs must be continuously reviewed and evaluated, and their performances should be reported and discussed. There is a lack of research to empirically compare current emotion detection technologies in terms of the results obtained from each model using the same textual dataset. Also, there is a lack of comparative studies that apply benchmark comparisons to social data. This study compares eight technologies: IBM Watson Natural Language Understanding, ParallelDots, Symanto - Ekman, Crystalfeel, Text to Emotion, Senpy, Textprobe, and Natural Language Processing Cloud. The comparison was undertaken using two different datasets. The emotions from the chosen datasets were then derived using the incorporated APIs. The performance of these APIs was assessed using the aggregated scores they delivered and the theoretically proven evaluation metrics such as the micro-average of accuracy, classification error, precision, recall, and f1-score. Lastly, the assessment of these APIs incorporating the evaluation measures is reported and discussed.

Investigating the antecedents of HRIS adoption in public sector organizations: integration of UTAUT and TTF

Purpose

This paper aims to propose a user adoption model of human resource information system (HRIS) in the Jordanian public sector by integrating the task technology fit (TTF) model and the unified theory of acceptance and usage of technology (UTAUT).

Design/methodology/approach

Using a quantitative approach, survey data were collected using an online survey from employees working in four different public organizations in Jordan, and structural equation modelling has been used to validate the research model.

Findings

The study found that among the constructs of the UTAUT model performance expectancy, social influence and facilitating condition have a significant effect on users’ behavioural intention to adopt HRIS. Furthermore, the results also reveal that effort expectancy has an insignificant effect on adoption behaviour. The findings also show that all TTF hypotheses were supported by the data collected. Both task characteristics and technology characteristics have a significant effect on the TTF construct, which further determines users’ adoption behaviour.

Originality/value

These findings contribute to the extant academic literature and have practical implications, improving the understanding of the HRIS adoption and use in public sector organizations.

Mobile payment adoption in the time of the COVID-19 pandemic

Current situation in COVID-19 pandemic as well as the significant digital transformation, where the whole world is being forced to participate, are lead for a wide acceptance to use the mobile payments. The main objective for the current study is to focus on analysing the primary variable “intention to use” through the Apple Wallet mobile payment system “apple wallet app” in United Arab Emirates (UAE), in addition to defining a context and evaluating the various antecedents of its use. The main variables that addressed by the current study are ability to use (skilfulness), perceived usefulness, convenience of the system, perceived risk and the primary variable that mentioned before was intention to use. To conduct the study, we invited 422 respondents to an online survey, and we have used a structural equation modelling analysis. The results indicate that mobile user skilfulness is the variable that most influences the intention to use the proposed payment system, followed by perceived usefulness and convenience of the system, while the perceived risk has a weak negative relationship with intention to use mobile payment via apple wallet app in the light of high Cybersecurity Index in the UAE.

Students’ Perceptions of the Sustainability of Distance Learning Systems in the Post-COVID-19: A Qualitative Perspective

The new Sustainable Learning and Education (SLE) concept was formulated in line with the Sustainable Development Goals (SDGs) announced by the United Nations. In order to achieve SLE, educational bodies need to utilize new technologies. Notably, the outbreak of the coronavirus (COVID-19) has forced educational institutions to utilize more innovative technological approaches to meet the objectives while still being in compliance with the doctrines of SLE. This research was conducted to explore the role of e-learning in transforming the academic industry in the post-COVID-19 time. The qualitative technique for interpretive phenomenological analysis (IPA) was applied to closely examine the participants’ lived experiences. The respondents were chosen from a private university in Jordan, and data were acquired through semi-structured interviews. Quality education, ease of technology, instructor accessibility and the use of online learning resources were the dimensions used for e-learning adoption. The findings highlighted that the students were truly overwhelmed by joining online platforms, but a lack of immediate feedback discouraged them. Besides this, the study will be useful to educational institutions in Jordan and other developing nations in gaining a better understanding of students’ attitudes about e-learning adoption.

Investigating antecedents of mobile payment systems’ decision-making: a mediated model

Purpose

The increase in mobile telephone penetration has offered new opportunities for technology to improve payment operations all over the world. Little research has examined the issues related to the decision-making (DM) of mobile payment systems usage in the Jordanian context. The purpose of this study is to examine the factors that may have an influence on the adoption of mobile payment systems. This study has empirically tested the expanded unified theory of acceptance and use of technology (UTAUT2) together with awareness (AW), trust (TR), security (SE) and privacy (PR) as independent variables to explain the mobile payment system adoption in Jordan.

Design/methodology/approach

In total, 270 employees participated in a field survey questionnaire from the public sector in Amman city, the capital city of Jordan. Data were analyzed through a quantitative approach of partial least squares–structural equation modeling.

Findings

The results mainly showed that the determinants of DM to use mobile payment system are price value, social influence, performance expectancy, AW and TR. All of these determinants explained 60.2% of the variation of DM. In total, 72.2% has been explained as the TR to use m-payment system by SE and PR. Furthermore, the results revealed that TR mediates the association between SE as well as PR and the DM to use mobile payment system.

Originality/value

Interestingly, these new variables were found to be important and contribute to the UTAUT2 model. Consequently, the decision-makers in the Central Bank of Jordan should consider all these factors when re-upgrading a Jordan Mobile Payment system in the near future.

Examining the critical factors of computer-assisted audit tools and techniques adoption in the post-COVID-19 period: internal auditors perspective

Purpose

In light of the repercussions of the COVID-19 pandemic, electronic auditing otherwise known as computer-assisted audit tools and techniques (CAATTs) has become inevitable to automate the auditing process worldwide. Accordingly, the purpose of this study is to examine the influence of technological, organizational and environmental (TOE) factors on public sector adoption of CAATTs in developing countries such as Jordan under the COVID-19 pandemic conditions.

Design/methodology/approach

This study used 136 usable responses from the managers of internal audit (IA) of the Jordanian public sector entities. The data collected were analyzed using partial least squares-structural equation modeling. The TOE framework has been used in this study to consider a wide set of TOE factors. Then, this study suggests a CAATTs adoption model that incorporates the related technology factors of the diffusion of innovation theory to environmental and organizational factors. Further, this study contributes to the TOE framework by addressing government regulations, audit bodies’ support and audit task complexity as environmental factors affecting CAATTs adoption in the context of the public sector.

Findings

The results revealed that for technological factors, only the compatibility affects CAATTs adoption by the IA departments. For organizational factors, organizational readiness, top management support, auditors’ information technology competency and entity size were found to be significant factors. From the environmental factors, both government regulation and audit task complexity influence the CAATTs adoption. Besides, entity size moderates the influence of top management support on the CAATTs adoption in the public sector.

Practical implications

The findings could highlight the significance of the CAATTs adoption in the public sector institutions (by internal auditors) post-COVID-19, taking into consideration the TOE framework’s factors. Also, the findings are significant for the decision-makers and regulators in declaring new legislation for the electronic IA profession in the Jordanian public sector.

Social implications

It turns out that the CAATTs adoption in the public sector can definitely enhance their ability to achieve the role of IA in preserving public funds and restricting corrupt practices within the public sector.

Originality/value

To the best of the authors’ knowledge, this study is one of the first studies that address the professional audit agency support and audit task complexity as environmental factors, as well as the entity size as an organizational factor, that affect CAATTs adoption in the IA department of the public sector.

An Empirical Investigation of Reasons Influencing Student Acceptance and Rejection of Mobile Learning Apps Usage

Sustainable learning and education (SLE) is a relatively new ideology based on sustainability principles and developed in response to the United Nations’ recently proclaimed Sustainable Development Goals (SDGs). As a result, technologies should be adopted to equip educational institutions with the tools necessary to attain SLE. Recently, the coronavirus (COVID-19) pandemic has affected educational systems globally, leading them to embrace more innovative technological methods to meet academic demands while maintaining SLE principles. Mobile learning apps (MLA) refers to using the unique capabilities of mobile apps to engage and collaborate towards establishing robust online learning. However, the effectiveness of MLA depends on learners’ acceptance. Therefore, the purpose of this study is to investigate the factors that could affect MLA acceptance. In order to analyze the collected data from 415 Jordanian students among schools and universities, structural equation modeling (SEM) was used. The empirical findings confirm that perceived usefulness and perceived ease of use are significantly influenced by self-efficacy and perceived compatibility. Furthermore, perceived usefulness is significantly influenced by perceived convenience and perceived ease of use. Additionally, perceived enjoyment significantly influences the behavioral intention to use MLA. On the other hand, perceived compatibility has no significant influence on perceived enjoyment. Finally, perceived ease of use, perceived usefulness, and perceived compatibility have no significant effect on behavioral intention to use MLA. This study addresses a critical research gap in the distance learning acceptance literature by proposing an exhaustive model in the post-COVID-19 era that can help to improve students’ performance and outcomes in Jordanian schools and universities.

Factors Influencing the Decision to Utilize eTax Systems During the COVID-19 Pandemic

This study examines the usage of eTax systems using the unified theory of acceptance and use of technology (UTAUT) as a theoretical base. A quantitative methodology using partial least squares-structural equation modelling (PLS-SEM) was used to test the study model against data collected from 209 taxpayers who completed the research questionnaire. The outcomes of this study manifest necessary theoretical extension of the UTAUT model and practical contributions during the pandemic of COVID-19. The findings of this study reveal that the behavioral intention to use eTax systems is highly influenced by performance expectancy, effort expectancy, social influence, social isolation, and anxiety about technology. Similarly, the behavioral intention of eTax systems and anxiety of COVID-19 infection demonstrate a substantial association with the actual usage of eTax systems. Interestingly, the study's findings also show that the anxiety of COVID-19 infection moderates the association bounded by usage intention and actual use of eTax systems.