Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs

The mechanism analysis on the farmers' motivation of using the quality traceability system based on TAM-ECM model

The quality traceability system for agricultural product plays an important role in tracing the production history or flow of agricultural products in China. At present, the quality traceability system is facing the problem of limited coverage and promotion. Understanding the continuous usage behavior of users can help solve this problem. This study constructed a model integrating TAM-ECM to analyze the mechanisms affecting the continuous usage intention and behavior of users of the quality traceability system, using PLS analysis method and survey data from 197 users of the GanNan navel orange quality traceability system with a usage time of up to two years. The results show that both satisfaction and usage habits directly promote the continuous usage of the quality traceability system. Lowering transaction costs significantly improves perceived value and satisfaction, and has a greater direct impact on satisfaction. Expectation confirmation level has a positive effect on perceived value, and lowering transaction costs also enhances perceived value. Perceived value、transaction cost, and satisfaction are important factors driving the continuous usage of the quality traceability system by users. The research findings provide a reference basis for the government to develop policies to attract users to use the quality traceability system for agricultural product.

Examining the critical factors of internal audit effectiveness from internal auditors' perspective: Moderating role of extrinsic rewards

An effective internal auditor can support an organization in achieving its goals and protect its assets and funds. However, to be effective, the internal auditors need to be empowered with relevant resources. This study aims at probing the influence of the empowerments (management support, external auditors' collaboration, independence, size of internal audit units, and extrinsic rewards) on the internal auditors' effectiveness, and to examin whether extrinsic rewards moderate the association between respective empowerments and the effectiveness of Jordanian public sector internal auditors'. The current work relied on 117 surveys collected from Jordan's internal audit and financial managers in the public sectors. According to the Resource-Based View (RBV), the findings show that management support, external auditors cooperation, independence, and extrinsic rewards all have a significant influence on the effectiveness of internal auditor. The of the Internal Audit Department (IAD) size was discovered to be insignificant. Also, the results have revealed partial support for the influence of the extrinsic reward as a moderator. Because of the prominence of the public sector in the Jordanian market, this current research expands on the idea of enabling internal auditor (IA) to accomplish their assigned objectives. The findings might help authorities develop new norms and legislation for the internal audit profession. These empowering characteristics may also improve internal auditors' capacity to execute their duty in saving public monies and limiting corrupt practices inside public sector organizations.

The influence of accounting information system adoption on business performance amid COVID-19

The previous decade witnessed the dynamic progress that information systems (ISs) brought about in business performances. In this regard, an effective and efficient organization reflects heightened performance through the use of financial systems like the Accounting Information System (AIS) as the system automates the processes and improves efficiencies. In the current times, AIS has been the reason behind the optimum performance of businesses, with past studies evidencing its successful role dependent on critical success factors. Hence, the primary aim of this study is to evaluate AIS through the use of De Lone and Mc Lean's information sys-tem model (DM ISM) among Sudanese banks. The system focuses on critical factors including information quality, system quality, service quality, system usage and user satisfaction and their effects on the performance of banks in Sudan. Accordingly, this study made use of self-administered survey questionnaire to collect data from 103 AIS user, after which PLS-SEM was employed for data validation. The findings supported the significant effects of system and information quality on system usage but not services quality. Also, AIS use was found to significantly affect the performance of business. The study contributed to literature concerning IS in light of AIS benefits determinants, and it validated the proposed model among firms in Sudan. In effect, the study has both theoretical and practical significance, and it provided limitations, implications and future studies recommendations.

The Use of a Technology Acceptance Model (TAM) to Predict Patients' Usage of a Personal Health Record System: The Role of Security, Privacy, and Usability

Personal health records (PHR) systems are designed to ensure that individuals have access and control over their health information and to support them in being active participants rather than passive ones in their healthcare process. Yet, PHR systems have not yet been widely adopted or used by consumers despite their benefits. For these advantages to be realized, adoption of the system is necessary. In this study, we examined how self-determination of health management influences individuals' intention to implement a PHR system, i.e., their ability to actively manage their health. Using an extended technology acceptance model (TAM), the researchers developed and empirically tested a model explaining public adoption of PHRs. In total, 389 Saudi Arabian respondents were surveyed in a quantitative cross-sectional design. The hypotheses were analysed using structural equation modelling-partial least squares (SEM-PLS4). Results indicate that PHR system usage was influenced by three major factors: perceived ease of use (PEOU), perceived usefulness (PU), and security towards intention to use. PHR PEOU and PHR intention to use were also found to be moderated by privacy, whereas usability positively moderated PHR PEOU and PHR intention to use and negatively moderated PHR PU and PHR intention to use. For the first time, this study examined the use of personal health records in Saudi Arabia, including the extension of the TAM model as well as development of a context-driven model that examines the relationship between privacy, security, usability, and the use of PHRs. Furthermore, this study fills a gap in the literature regarding the moderating effects of privacy influence on PEOU and intention to use. Further, the moderating effects of usability on the relationship between PEOU, PU, and intention to use. Study findings are expected to assist government agencies, health policymakers, and health organizations around the world, including Saudi Arabia, in understanding the adoption of personal health records.

Digital transformation of business model innovation

Because of the rising labor costs and the trade impact after joining the World Trade Organization, the textile industry in Taiwan has encountered many operational and production problems and obstacles. In addition, the lack of knowledge and resources for the digital transformation required to improve business performance has led to poor production and decision-making efficiency, and stagnant R&D for textile product innovation. In order to improve business operations, enhance customer satisfaction and experience, increase efficiency and reduce manual error, this study was conducted with senior executives and company managers in Taiwan's textile industry as the target population. The knowledge, technological resources, and competitive pressure of digital transformation are the independent variables. The organizational innovation atmosphere is the moderating variable. The study analyzes the impact of digital transformation on the intention of enterprises. The results of the study show that the knowledge of digital transformation, technological resources, and the competitive pressure of the textile industry positively and significantly affect their perceived benefits of digital transformation. Digital transformation knowledge, technological resources, and competitive pressure will negatively and significantly affect the perceived risk of digital transformation. The perceived benefits and risks of digital transformation are related to the intention of digital transformation of enterprises. The organizational innovation atmosphere of the textile industry positively moderates the influence of perceived benefits on digital transformation intention. Finally, based on the research findings, this study provides practical recommendations to senior executives and company managers in the textile industry. It is also recommended to promote the digital transformation of related software and hardware vendors and government agencies, as well as the subsequent related research reference.

Optimization of Work Environment and Community Labor Health Based on Digital Model-Empirical Evidence from Developing Countries

As far as we know, for large manufacturing enterprises, there is often a community of labor gathered around such enterprises, which is especially used as a place for the enterprise to place the labor force. This paper aimed to update the industry model of Chinese Manufacturing Enterprises (CMEs) to improve workers' health management. This work first discusses the value, mode, and process of Enterprise Digital Transformation (EDT) and Worker Health and Safety Management (WHSM). Then, it proposes the CMEs-oriented EDT model and WHSM system based on Big Data Technology (BDT) and the Internet of Things (IoT). The proposed model and system are verified through a case study on the Shanghai BYD manufacturing enterprise (short for BYD) using the Fuzzy Comprehensive Evaluation Method (CFEM). The EDT model verification considers the adaptation and performance of enterprises after EDT. The WHSM system considers workers' oxygen inhalation status to evaluate their heart and cardiovascular health. The results show that EDT improves the enterprise's revenue and reshuffles the revenue structure. The EDT model has absolute adaptability to BYD. It has greatly improved BYD's indexes, especially financial performance, market capability, and technical capability.

The Role of Personality and Top Management Support in Continuance Intention to Use Electronic Health Record Systems among Nurses

This study examines nurses' Continuance Intention (CI) to use electronic health records (EHRs) through a combination of three conceptual frameworks: the Unified Theory of Acceptance and Use of Technology (UTAUT), the theory of expectation-confirmation (ECT), and the Five-Factor Model (FFM). A model is developed to examine and predict the determinants of nurses' CI to use EHRs, including top management support (TMS) and the FFM's five personality domains. Data were collected from a survey of 497 nurses, which were analyzed using partial least squares. No significant relationship was found between TMS and CI. The study revealed that performance expectancy significantly mediated the influences of two different hypotheses of two predictors: agreeableness and openness to testing CI. A significant moderating impact of conscientiousness was found on the relationship between performance expectancy and CI and the relationship between social influence and CI. The findings of this study indicated that rigorous attention to the personality of individual nurses and substantial TMS could improve nurses' CI to use EHRs. A literature gap was filled concerning the mediating effects of performance expectancy on the FFM-CI relationship, and the moderation effects of Conscientiousness on UTAUT constructs and CI are another addition to the literature. The results are expected to assist government agencies, health policymakers, and health institutions all over the globe in their attempts to understand the post-adoption use of EHRs.

Adoption of big data analytics practices for sustainability development in the e-commercesupply chain: a mixed-method study

Purpose

The study aims to identify the potential drivers of big data analytics (BDA) practices in the supply chain and develop a sustainability evaluation model to evaluate drivers of big data for sustainability development.

Design/methodology/approach

The mixed-method approach was applied to assess sustainability dimensions and calculate the score using two phases. In Phase I, the BDA drivers in the e-commerce industry were finalised using the partial least square based structural equation modelling (PLS-SEM) method. In Phase II, a case study in the Indian fashion e-commerce industry was carried out to evaluate sustainability dimensions with respect to drivers of BDA and the sustainability score was calculated using the fuzzy analytical hierarchical process (AHP) method.

Findings

The index for economic sustainability (0.220), social sustainability (0.142) and environmental sustainability (0.182) were derived. The higher index value of economic sustainability compared to social sustainability and environmental sustainability signified those drivers of big data bring social and environmental uncertainty along with economic sustainability.

Research limitations/implications

The study will help practitioners promote BDA use for developing environmental/social/economic sustainability in supply chains. Policymakers must ensure whether the integration of BDA practices brings down cost and brings strategic value for ensuring big data success. The study will help managers decide a constant trade-off between the requirement for social, environmental and economic performance.

Originality/value

The study corroborates and adds to the BDA literature by emphasising the positive role of BDA in sustainability development in the supply chain area and highlighting the significant role of different drivers of BDA in sustainability development.

Acquiring, Analyzing and Interpreting Knowledge Data for Sustainable Engineering Education: An Experimental Study Using YouTube

With the immersion of a plethora of technological tools in the early post-COVID-19 era in university education, instructors around the world have been at the forefront of implementing hybrid learning spaces for knowledge delivery. The purpose of this experimental study is not only to divert the primary use of a YouTube channel into a tool to support asynchronous teaching; it also aims to provide feedback to instructors and suggest steps and actions to implement in their teaching modules to ensure students’ access to new knowledge while promoting their engagement and satisfaction, regardless of the learning environment, i.e., face-to-face, distance and hybrid. Learners’ viewing habits were analyzed in depth from the channel’s 37 instructional videos, all of which were related to the completion of a computer-aided mechanical design course. By analyzing and interpreting data directly from YouTube channel reports, six variables were identified and tested to quantify the lack of statistically significant changes in learners’ viewing habits. Two time periods were specifically studied: 2020–2021, when instruction was delivered exclusively via distance education, and 2021–2022, in a hybrid learning mode. The results of both parametric and non-parametric statistical tests showed that “Number of views” and “Number of unique viewers” are the two variables that behave the same regardless of the two time periods studied, demonstrating the relevance of the proposed concept for asynchronous instructional support regardless of the learning environment. Finally, a forthcoming instructor’s manual for learning CAD has been developed, integrating the proposed methodology into a sustainable academic educational process.

Broadband Mobile Applications’ Adoption by SMEs in Taiwan—A Multi-Perspective Study of Determinants

The purpose of this study is to explore what determinants affect small and medium enterprises regarding the adoption of broadband mobile applications. Today, broadband mobile applications are changing the business landscape rapidly, which presents a vital issue for enterprises to understand and tackle. Both qualitative and quantitative methods were applied in this study in order to analyze the issues enterprises may face with broadband mobile applications. Qualitatively, a preliminary study was conducted based on a review of literature to explore the factors that impact small and medium enterprises. Quantitatively, Structural Equation Modeling and AMOS were deployed to further examine the potential factors. As broadband mobile applications are mostly installed in the personal mobile device and operated by individuals, this study integrated the perspective of internal users along with the Technology-Organization-Environment framework to develop an ITOE research model to provide a more comprehensive view on the determinants and factors. The practicality and feasibility of the ITOE research model were then verified by the study results through the fifteen determinants identified. Based on the findings, implications and future research directions are proposed.

The Validity of Visual Communication Design of Online Advertisement Based on Interactivity

Today’s society is a society of Internet information, especially the rapid development of new media that is the most distinctive project today. New media has changed the way traditional media are disseminated, and the advertising industry has made new developments with the rapid development of new media, especially with the rise of online advertising, making the dissemination of advertising more influential. In modern advertising information, online advertising has become very influential. This study aims at how to achieve user-matching push and set the right price is the two major problems of Internet advertising push, through the analysis of the emergence and development of network advertising and visual elements in network advertising, starting from the problems appearing in modern online advertisements, and studying the visual communication design in online advertisements. In this paper, a neural network model and a fuzzy comprehensive evaluation decision model are designed; so as to make our online advertisements rich in national characteristics and really cause online users’ active clicks. The experimental results show that the proposed method achieves good results and verifies the effectiveness of the model.

Evaluating the D&M IS Success Model in the Context of Accounting Information System and Sustainable Decision Making

The Accounting Information System (AIS) is generally employed for the automation of operational processes and the enhancement of company efficiencies, but more recently, AIS developments have had a great effect on the process of sustainable decision-making among organizations. However, previous research on the AIS and its capabilities attributed its success to critical success factors. Therefore, in the current work, De Lone and Mc Lean’s Information System (D&M IS) Success Model is evaluated in terms of AIS in Jordanian organizations. The current study primarily aimed to determine the influence of system quality, service quality, information quality, system use and user satisfaction on AIS use, which is argued to eventually enhance the quality and sustainability of decision-making. The study employed a quantitative approach using a self-administered questionnaire for data collection involving 101 decision-makers who are familiar with AIS usage. Following the collection of data, it was validated using Structural Equation Modeling (SEM)—PLS. Based on the obtained results, system quality and information quality significant affected system use, but service quality did not. In turn, AIS was found to have a significant effect on user satisfaction. Furthermore, system use and user satisfaction had positive effects on AIS, which eventually affected the sustainability of decision-making, representing the net AIS benefits. The study contributes to existing IS literature, particularly in the field of determining the factors that influence the AIS net benefits, with the proposed model validated in Jordanian organizations using AIS. The study can be used as a guide to shed light on the importance of AIS and it also provides implications, limitations and opportunities for future studies.

The Role of Quality Measurements in Enhancing the Usability of Mobile Learning Applications during COVID-19

Despite numerous studies offering some evidence about the significance of quality measurements in enhancing the success of m-learning applications, there are still limited studies about the role of quality measurements in promoting the usability of mobile learning systems. Therefore, our study explores the role of quality measurements in promoting the usability of m-learning systems during COVID-19. The results revealed that the service quality, information quality and system quality are the most important factors affecting mobile learning usability among learners during COVID-19. Moreover, these findings are valuable for classifying the significance of these quality elements, which provide guidance on assigning quality aspects to improve this mobile learning usage during COVID-19 in higher education institutions.

Actual Use of Mobile Learning Technologies during Social Distancing Circumstances: Case Study of King Faisal University Students

The most current highly infectious disease, which has become a global health challenge permeating entire sectors of society, is COVID-19. In the education sector, the transmission of COVID-19 has been curbed through the closure of institutions and the facilitation of online learning. The main objective of this study was to propose an integrated model of the unified theory of acceptance and use of technology combined with the DeLone and McLean model, to examine the influence of quality features, namely, performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC), and social influence (SI), on the intentions and satisfaction of users toward mobile learning (m-learning) use in the context of Saudi learning institutions. The study obtained m-learning user data using an online questionnaire, after which the data were exposed to partial least squares structural equation modeling to test the proposed research model. The findings supported the influence of PE, EE, and FC on intention toward m-learning use but did not support the significant influence of SI. Moreover, system, intention, and user satisfaction were found to positively and significantly influence m-learning-system usage, with system, information, and service quality being top drivers of such user intention and satisfaction. The results reflect the required information concerning the strategies of higher institutions to enhance m-learning-system acceptance among students, with general implications for learning acceptance and usage.

An application of data mining algorithms for predicting factors affecting Big Data Analysis adoption readiness in SMEs

The adoption of Big Data Analysis (BDA) has become popular among firms since it creates evidence for decision-making by managers. However, the adoption of BDA continues to be poor among small and medium enterprises (SMEs). Therefore, this study adopted the Technology-Organization-Environment (TOE) framework to identify the drivers of readiness to adopt BDA among SMEs. Chi-square automatic interaction detection (CHAID), Bayesian network, neural network, and C5.0 algorithms of data mining were utilized to analyze data collected from 240 Vietnamese managers of SMEs. The evaluation model identified the C5.0 algorithm as the best model, with accurate results for the prediction of factors influencing the readiness to adopt BDA among SMEs. The findings revealed management support, data quality, firm size, data security and cost to be the fundamental factors influencing BDA adoption readiness. Moreover, the results identified the service sector as having a higher level of readiness toward the adoption of BDA compared to the manufacturing sector. The findings are imperative for the enhancement of the decision-making process and advancement of comprehension of the determinants of BDA adoption among SMEs by researchers, managers, providers and policymakers.

Exposure Detection Applications Acceptance: The Case of COVID-19

The pandemic's context is rife with numerous dangerous threats and high fear levels, influencing human decision-making. Such characteristics are identified by investigating the acceptance of exposure detection apps from the technology acceptance model (TAM) perspective. This study purposed a model to investigate protection technology acceptance, specifically exposure detection apps in the context of COVID-19. Quantitative study approach and a cross-section design targeted 586 participants from Saudi Arabia. As the study model is complex, the study hypotheses were analysed using the structural equation modelling-partial least squares (SEM-PLS3) approach. The findings support the entire model hypothesis except the link between social media awareness and exposure detection apps' intention. Mediation of COVID-19 anxiety and influence was confirmed as well. The current paper contributes to the technologies acceptance domain by developing a context-driven model comprising the major pandemic characteristics that lead to various patterns of technology acceptance. This study also fills the literature gap regarding mediating effects of social influence and COVID-19 anxiety in the relationship between trust in government and exposure detection apps implementation, and between COVID-19 anxiety and exposure detection apps implementation, respectively. The results may assist government agencies, health policymakers, and health organisations in the wide world and specifically Saudi Arabia, in their attempts to contain the COVID-19 pandemic spread.

Business Sustainability of Small and Medium Enterprises during the COVID-19 Pandemic: The Role of AIS Implementation

Small and medium enterprises (SMEs) are the pillars on which most businesses worldwide rest. Thus, without the support of qualified information systems, it can be very challenging for them to improve their performance and difficult for them to reach sustainability goals. Despite the essentiality of economic sustenance for a competitive advantage in the postmodern industrial era, Jordanian SMEs are hampered with multiple challenges, such as accounting information quality, which supports various organizational decisions. The prevalence of information technology (IT) optimizes accounting operations through accounting-based information. A computerized accounting system (accounting information system, or AIS) facilitates accurate reporting, processes large-scale transactions, and generates meaningful reporting for subsequent evaluation. Given the lack of AIS implementation in SMEs, despite its notable advantages, this study aims to investigate the AIS-implementation antecedents and their implications towards sustainable business performance among Jordanian SMEs. An integrated model was recommended based on the technology–organization–environment (TOE) framework and resource-dependency theory (RDT) for the incorporation of AIS-implementation elements and sustainable business performance into one model. A self-administered questionnaire was disseminated among 194 respondents within the context of Jordanian SMEs for data collection and evaluation using structural equation modelling (SEM). Based on the study outcomes, external pressure, compatibility, financial support, top management support (TMS), and external assistance significantly impacted AIS implementation, which subsequently catalyzed sustainable business performance. Such results could offer useful insights into how organizations could optimize AIS implementation for sustainable business performance and expand the current body of literature on IS- or IT-implementation antecedents and impacts. The implications of this study are that SMEs should develop effective AIS implementation in order to reach sustainability goals. Therefore, we recommend and encourage SMEs decision makers to utilize AIS for their businesses.

Grade Prediction Modeling in Hybrid Learning Environments for Sustainable Engineering Education

Since mid-March 2020, due to the COVID-19 pandemic, higher education has been facing a very uncertain situation, despite the hasty implementation of information and communication technologies for distance and online learning. Hybrid learning, i.e., the mixing of distance and face-to-face learning, seems to be the rule in most universities today. In order to build a post-COVID-19 university education, i.e., one that is increasingly digital and sustainable, it is essential to learn from these years of health crisis. In this context, this paper aims to identify and quantify the main factors affecting mechanical engineering student performance in order to build a generalized linear autoregressive (GLAR) model. This model, which is distinguished by its simplicity and ease of implementation, is responsible for predicting student grades in online learning situations in hybrid environments. The thirty or so variables identified by a previously tested model in 2020–2021, in which distance learning was the exclusive mode of learning, were evaluated in blended learning spaces. Given the low predictive power of the original model, about ten new factors, specific to blended learning, were then identified and tested. The refined version of the GLAR model predicts student grades to within ±1 with a success rate of 63.70%, making it 28.08% more accurate than the model originally created in 2020–2021. Special attention was also given to students whose grade predictions were underestimated and who failed. The methodology presented is applicable to all aspects of the academic process, including students, instructors, and decisionmakers.

Smart Mobile Learning Success Model for Higher Educational Institutions in the Context of the COVID-19 Pandemic

Smart mobile learning (M-learning) applications have shown several new benefits for higher educational institutions during the COVID-19 pandemic, during which such applications were used to support distance learning. Therefore, this study aims to examine the most important drivers influencing the adoption of M-learning by using the technology acceptance model (TAM). The structural equation modelling (SEM) method was used to test the hypotheses in the proposed model. Data were collected via online questionnaires from 520 undergraduate and postgraduate students at four universities in Saudi Arabia. Partial least squares (PLS)–SEM was used to analyse the data. The findings indicated that M-learning acceptance is influenced by three main factors, namely, awareness, IT infrastructure (ITI), and top management support. This research contributes to the body of knowledge on M-learning acceptance practices. Likewise, it may help to facilitate and promote the acceptance of M-learning among students in Saudi universities.

Employing the TAM Model to Investigate the Readiness of M-Learning System Usage Using SEM Technique

During COVID-19, universities started to use mobile learning applications as one of the solutions to support distance learning. The readiness of universities to apply new systems, such as mobile learning applications, is considered one of the critical issues to ensure the system’s success. Determining the most important aspects of readiness to use mobile learning is a key step to adopt mobile learning in an effective way. To address this issue, this research aims to determine the most important determinants influencing mobile learning readiness by employing the Technology Acceptance Model (TAM). The Structural Equation Modelling (SEM) method was used to test the hypotheses in the proposed model. The results showed that the relationship between mobile learning readiness and awareness, IT infrastructure and top management support was positively significant. In conclusion, the findings will be of value to decision makers and mobile learning developers in universities to enhance the development of mobile learning applications. In addition, it may help facilitate and promote the usage of mobile learning applications among users.

Deploying Big Data Enablers to Strengthen Supply Chain Resilience to Mitigate Sustainable Risks Based on Integrated HOQ-MCDM Framework

In the face of global competition, competitive enterprises should pursue sustainable development, and strengthen their supply chain resilience to cope with risks at any time. In addition, big data analysis has been successfully applied in a variety of fields. However, the method has not been applied to improve supply chain resilience in order to reduce sustainable supply chain risks. An approach for enhancing the capabilities of big data analytics must be developed to enhance supply chain resilience, and mitigate sustainable supply chain risks. In this study, a decision framework that integrates two-stage House of Quality and multicriteria decision-making was constructed. By applying this framework, enterprise decision-makers can identify big data analytics that improve supply chain resilience, and resilience indicators that reduce sustainable supply chain risks. A case study of one of China’s largest relay manufacturers is presented to demonstrate the practicability of the framework. The results showed that the key sustainable supply chain risks are risks regarding the IT infrastructure and information system efficiency, customer supply disruptions, transport disruptions, natural disasters, and government instability. To reduce risk in sustainable supply chains, enterprises must improve the key resilience indicators ‘financial capability’, ‘flexibility’, ‘corporate culture’, ‘information sharing’, and ‘robustness’. Moreover, to increase supply chain resilience, the following most important big data analysis enablers should be considered: ‘capital investment’, ‘building big data sharing mechanism and visualisation’, and ‘strengthening big data infrastructures to support platforms and systems’. This decision framework helps companies prioritise big data analysis enablers to mitigate sustainable supply chain risks in manufacturing organisations by strengthening supply chain resilience. The identified priorities will benefit companies that are using big data strategies and pursuing supply chain resilience initiatives. In addition, the results of this study show the direction of creating a fruitful combination of big data technologies and supply chain resilience to effectively mitigate sustainable risks. Despite the limited enterprise resources, management decision-makers can determine where big data analysis enablers can be most cost-effectively improved to promote risk resilience of sustainable supply chains; this ensures the efficient implementation of effective big data strategies.

Factors Influencing the Continuance Intention to Use Accounting Information System in Jordanian SMEs from the Perspectives of UTAUT: Top Management Support and Self-Efficacy as Predictor Factors

The primary objective of this study is to explain the factors that influence the continuance intention of accountants to use an accounting information system (AIS) in the context of Jordanian small and medium-sized enterprises (SMEs). Accountants are the main AIS users, and their system acceptance and use are crucial to evaluating the successful implementation of the system. The study conducted a cross-sectional survey on SMEs that have fully implemented an AIS. The proposed framework of the study is based on the extended unified theory of acceptance and use of technology (UTAUT) model and top management support (TMS). The results revealed that the examined variables, namely effort expectancy, performance expectancy and facilitating conditions, have a positive effect on the continuance intention of accountants to use AIS, with TMS having a significant and negative effect on such intention to use. In addition, social influence was found to be significantly related to continuance intention, confirming the need to support technologies such as AIS among SMEs. The study findings contribute to UTAUT theory as they supported the effects of TMS on continuance intention to use and established the study framework measurement accuracy in the context of Jordanian SMEs.

Big Data in Entrepreneurship

Entrepreneurship research is paying increasing attention to big data. However, there is only a fragmented understanding on how big data influences entrepreneurial activities. To review previous research systematically and quantitatively, the authors use bibliometrics method to analyze 164 research articles on big data in entrepreneurship. They visualize the landscape of these studies, such as publication year, country, and research area. They then use VOSviewer to conduct theme clustering analysis, finding four themes, namely the COVID-19 pandemic and small medium enterprise (SME) digitization, application of big data analytics to decision making, application of big data in platform, and the effects of big data on enterprises. In addition, they construct an integrated framework that integrates the antecedents of big data adoption and influence mechanism of big data on entrepreneurial activities.

Explaining the Factors Affecting Students’ Attitudes to Using Online Learning (Madrasati Platform) during COVID-19

This study aims to investigate students’ perceptions about the Madrasati platform as well as to identify the crucial factors that could influence the adoption of the Madrasati platform. Online quantitative survey method was employed to collect the data. SEM modelling method was adopted to analyze the hypotheses in the research model. The findings of the study indicate system quality, service quality and content quality, technology infrastructure, awareness, university management support, security concerns and training have a primary role in increasing the usage of the Madrasati platform in Saudi Arabia. The findings indicate that all factors have a significant influence on Madrasati platform-adoption among students. This research contributes to the body of knowledge and Madrasati platform-adoption practices. Likewise, it may help facilitate and promote the usage of Madrasati platform among students in Saudi universities.

Antecedents and Impacts of Enterprise Resource Planning System Adoption among Jordanian SMEs

Businesses need accounting information to support their decision-making. In this regard, the extensive use of Information Technology (IT) has enhanced the effectiveness and efficiency of accounting functions that support accounting-related information. Specifically, an enterprise resource planning (ERP) system ensures reporting accuracy, large amounts of transaction processing, and the generation of reports for analysis. Regardless of the numerous benefits that an ERP system provides, small and medium-sized enterprises (SMEs) have yet to catch up with their system usage. Hence, this study draws upon the technology-organisation-environment (TOE) framework to propose an integrated model that includes diffusion of innovation (DOI), institutional factors, and TOE to examine ERP adoption antecedents in the context of SMEs in Jordan. A mixed method is applied in this work, and it uses a self-administered questionnaire survey as the main data collection instrument along with interviews. Quantitative data are obtained from 102 respondents through the questionnaire, after which the research model is validated using SMEs in Jordan. The survey results show that relative advantage, top management support, organisational readiness, training, competitive pressure, government support compatibility, and service provider support significantly influence ERP adoption among the SMEs. The findings are expected to shed light on the way SMEs can enhance their ERP adoption for optimum performance, as well as extend the literature dedicated to the antecedents of information system, IT adoption, and their impact.

Perception of Occupational and Environmental Risks and Hazards among Mineworkers: A Psychometric Paradigm Approach

This study aims to assess workers’ perception of occupational and environmental risks and hazards using the psychometric paradigm. For this purpose, data were collected using survey questionnaires from 360 mineworkers recruited from mineral and sand mines. Respondents were asked to evaluate eight occupational and environmental risks and hazards on nine commonly used risk characteristics. The principal component analysis revealed that two components, “Dreaded” and “Unknown”, explained 73% percent of the total variance in workers’ risk perception. The results also showed that the risk of developing an occupational disease was perceived as the most dreaded and unknown type of risk, while landslide, occupational noise, and vibration exposure were the least familiar to the respondents. A practical implication of this research is that the results may offer an insight into the employees’ perceptions of the hazards and risks associated with their working environment. This could help risk management develop and implement effective risk management and communications strategies.

A Conceptual Framework for Determining Quality Requirements for Mobile Learning Applications Using Delphi Method

The development of mobile learning apps might fail due to poor selection of the suitable technical requirements for mobile devices. This will affect the quality of mobile learning applications and, thus, will increase the development cost of mobile learning apps. Due to the above issues, we need to determine the most appropriate technical quality requirements for the development of mobile learning apps that meet user requirements. To achieve that, we propose a comprehensive framework to capture the most suitable technical quality requirements for mobile learning apps. A Delphi method was used to collect, evaluate, and analyze the data for this study. As a result of our Delphi study, we have identified nineteen technical quality requirements, divided into six quality dimensions, for the development of mobile learning applications. The proposed framework is expected to be a guideline for mobile apps designers and developers to successfully develop mobile learning apps.