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The current study aimed to explore the extent of accounting graduates’ abilities (AGAs) in Jordan to use modern information technology systems (MITSs) to make optimal financial decisions (OFDs). To carry out this study, the descriptive analytical approach was used to collect and analyze data. Accordingly, an electronic questionnaire was designed and distributed to 5,000 students in 30 universities in Jordan. However, only 1,067 questionnaires were valid for analysis, which constituted the sample of study. To test the research hypotheses, the descriptive analysis and multivariate regression test were used. The results indicated that the majority of accounting graduates (AGs) in Jordanian universities (JUs) do not realize the importance role of MITSs to make OFDs. In addition, the biggest challenge face AGs in JUs is the weakness of current accounting curricula in JUs in terms of not including materials related to MITSs and the role of these systems in performing accounting tasks. Finally, the study found that the current abilities of AGs in JUs moderate negatively and significantly the positive relationship between the use of MITSs and making OFDs. Accordingly, the study recommended that JUs work on developing accounting curricula through including modern courses related to the use of MITSs in performing accounting tasks.

Natural dyeing has existed in human life from past to present. Although it lost its importance after the industrial revolution, it has started to make again a name for itself today with the increase in environmental awareness. The purpose of this study is to investigate whether the Hibiscus sabdariffa L. can be used in the coloring of woolen fabrics and as a natural antibacterial agent for these fabrics.

Within the scope of the study, it was investigated whether the antibacterial activity of the Hibiscus sabdariffa L. can be transferred to woolen fabrics. In the study, woolen fabric samples were dyed with and without mordant with the help of Hibiscus sabdariffa L. extract. After the dyed fabric samples were washed and dried, their color values were measured, and antibacterial effect tests (against Staphylococcus aureus – Escherichia coli), washing and rubbing fastness tests were carried out. In addition to these, scanning electron microscopy images of dyed fabric samples were taken and Fourier transform infrared microspectroscopy analyzes were also performed.

As a result of the study, it has been determined that the antibacterial activity of the Hibiscus sabdariffa L. can be transferred to woolen fabrics without the use of any chemicals.

Natural antibacterial agent for woolen fabrics was obtained within the scope of the study without the use of chemicals.

This study aims to examine how different uses of performance measurement systems (PMS) enable or hinder organizational ambidexterity (OA), intended as the simultaneous pursuit of exploitation and exploration.

Following a qualitative research design, we gathered data through semi-structured interviews, observations and reviews of documents at four departments of an automotive firm.

We contribute to operations management research and practice by demonstrating how PMS, which are typically associated with exploitation, can also foster exploration and enable organizations to become ambidextrous. Specifically, we show how PMS can be structured and used in more agile ways and, in relation to innovation, we identify which PM practices should be introduced and with what effects and those that should be avoided. We also contribute to organization theory by highlighting how a single management tool can promote the achievement of both exploration and exploitation.

In investigating PMS uses and their effects, we identify several positive practices. For example, we show how managers can use PMS more effectively and how targets could be deployed to stimulate creativity and innovation. We also emphasize the need for managers to opt more often for team incentives rather than individual ones to encourage the collaboration needed for OA.

We provide in-depth insight into how PM tools affect an organization’s ability to pursue exploitation and exploration, thus contributing to research in operations, innovation and organization theory.

The objective of this paper is to develop a condition-based maintenance (CBM) scheme for pneumatic cylinders. The CBM scheme will detect two common types of air leaking failure modes and identify the leaky/faulty cylinder. The successful implementation of the proposed scheme will reduce energy consumption, scrap and rework, and time to repair.

Effective implementation of maintenance is important to reduce operation cost, improve productivity and enhance quality performance at the same time. Condition-based monitoring is an effective maintenance scheme where maintenance is triggered based on the condition of the equipment monitored either real time or at certain intervals. Pneumatic air systems are commonly used in many industries for packaging, sorting and powering air tools among others. A common failure mode of pneumatic cylinders is air leaks which is difficult to detect for complex systems with many connections. The proposed method consists of monitoring the stroke speed profile of the piston inside the pneumatic cylinder using hall effect sensors. Statistical features are extracted from the speed profiles and used to develop a fault detection machine learning model. The proposed method is demonstrated using a real-life case of tea packaging machines.

Based on the limited data collected, the ensemble machine learning algorithm resulted in 88.4% accuracy. The algorithm can detect failures as soon as they occur based on majority vote rule of three machine learning models.

Early air leak detection will improve quality of packaged tea bags and provide annual savings due to time to repair and energy waste reduction. The average annual estimated savings due to the implementation of the new CBM method is $229,200 with a payback period of less than two years.

To the best of the authors’ knowledge, this paper is the first in terms of proposing a CBM for pneumatic systems air leaks using piston speed. Majority, if not all, current detection methods rely on expensive equipment such as infrared or ultrasonic sensors. This paper also contributes to the research gap of economic justification of using CBM.

Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.

We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.

We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.

In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.

This scoping review article aimed to systematically search the literature on the use, purpose and barriers of information and communication technology (ICT) for culturally and linguistically diverse (CALD) older adults in the host country. The review also conducted a search for literature on programs that aim to develop digital literacy skills for CALD older adults.

A scoping review approach was utilized to identify and search the available literature, and to map the key concepts. A total of 23 relevant articles were included following a systematic search across seven databases.

The review suggests that CALD older adults use ICT for various purposes, including social interaction, health management, information gathering, immigration, everyday routines and leisure. The barriers faced by these older adults in using ICT encompass fear and limited knowledge, language issues, lack of interest, limited access to technology and health concerns. The existing training programs focus on enhancing self-efficacy and confidence and promoting attitudinal changes toward ICT.

Despite the presence of empirical studies, few scoping or systematic reviews have focused on CALD older adults and technology. Research developments related to the technology use of CALD older adults and associated training programs have been fragmented and sporadic, resulting in gaps in the evidence base. This review fills such a gap to better understand the research status connected to CALD older people’s technology adoption and use.

This study aims to examine the effect of application architecture and application efficiency on the intention to continue using Islamic bank with data security as a moderator. The investigation was situated within the framework of a hacker attack that compromised the security of customer data at one of Indonesia’s largest Islamic bank.

A survey questionnaire method was used, and the sample population comprised users of Islamic bank in Indonesia. The respondents were then selected purposively with the criteria of individuals who were using mobile banking services. Furthermore, data collection in this study was carried out by distributing questionnaires online. To validate the questionnaire, consultation and validation were conducted by engaging four experts and conducting a pilot study. Hypothesis testing was performed using the structural equation modeling method based on partial least squares.

The results of the partial least square structural model assessment showed that application efficiency and data security positively influenced the intention to continue using Islamic bank, while application architecture had no effect. Furthermore, data security could not moderate the relationship between application architecture and efficiency toward the intention to continue using Islamic bank.

The results of this study suggested that Islamic banking practitioners must prioritize the enhancement of digital banking services, with a specific focus on improving application efficiency and ensuring robust data security. These two dimensions were critical determinants influencing the intention to continue using Islamic bank.

This study addressed the issue of data security as a moderator, particularly in the context of hacker attacks targeting a major Islamic bank in Indonesia. Furthermore, this current report expounded on the study conducted by Mir et al. (2022) by introducing novel dimensions to the e-service quality of internet banking.

This study aims to scrutinize existing end-user comprehension regarding e-wallet technology through an examination of apparent usefulness, ease of use and levels of trust, and how these factors may influence a consumer’s attitudes toward the adoption of this new payment method.

The quota sampling method was used, and residents over the age of 22 years were targeted in online and offline questionnaires, and partial least squares-structural equation modeling was used to analyze the data.

This study indicates that existing consumer mindsets and intentions to adopt new technology, such as the e-wallet, are greatly influenced by their perception of the practicality of the product, its ease of use and their levels of trust in the technology to protect their online safety, privacy and economic affairs. Contrastingly, those participants who were offered deferred reimbursements and those given no information were demonstrably less likely to adopt the new service.

The study sample was from a developing nation – Saudi Arabia. Similar cohorts from developing and developed countries could provide a unique cross-nation comparison.

This study stresses the importance of thoroughly explaining and demonstrating an innovative technology to customers while simultaneously promoting the product. Consumers can be encouraged to use and evaluate the new technology by providing inducements, such as effective reimbursement policies.

This paper contributes to literature by critically reflecting on the question: What are the factors influencing customer intentions to adopt the e-wallet, and how do the guarantee of reimbursement and the time frame following unauthorized use influence consumer adoption intentions when deciding to use the new payment technology?

Artificial intelligence (AI) is a powerful and promising technology that can foster the performance, and competitiveness of micro, small and medium enterprises (MSMEs). However, the adoption of AI among MSMEs is still low and slow, especially in developing countries like Jordan. This study aims to explore the elements that influence the intention to adopt AI among MSMEs in Jordan and examines the roles of firm innovativeness and government support within the context.

The study develops a conceptual framework based on the integration of the technology acceptance model, the resource-based view, the uncertainty reduction theory and the communication privacy management. Using partial least squares structural equation modeling – through AMOS and R studio – and the importance–performance map analysis techniques, the responses of 471 MSME founders were analyzed.

The findings reveal that perceived usefulness, perceived ease of use and facilitating conditions are significant drivers of AI adoption, while perceived risks act as a barrier. AI autonomy positively influences both firm innovativeness and AI adoption intention. Firm innovativeness mediates the relationship between AI autonomy and AI adoption intention, and government support moderates the relationship between facilitating conditions and AI adoption intention.

The findings provide valuable insights for policy formulation and strategy development aimed at promoting AI adoption among MSMEs. They highlight the need to address perceived risks and enhance facilitating conditions and underscore the potential of AI autonomy and firm innovativeness as drivers of AI adoption. The study also emphasizes the role of government support in fostering a conducive environment for AI adoption.

As in many emerging nations, the AI adoption research for MSMEs in Jordan (which constitute 99.5% of businesses), is under-researched. In addition, the study adds value to the entrepreneurship literature and integrates four theories to explore other significant factors such as firm innovativeness and AI autonomy.

Maintaining the safety of the human is a major concern in factories where humans co-exist with robots and other physical tools. Typically, the area around the robots is monitored using lasers. However, lasers cannot distinguish between human and non-human objects in the robot’s path. Stopping or slowing down the robot when non-human objects approach is unproductive. This research contribution addresses that inefficiency by showing how computer-vision techniques can be used instead of lasers which improve up-time of the robot.

A computer-vision safety system is presented. Image segmentation, 3D point clouds, face recognition, hand gesture recognition, speed and trajectory tracking and a digital twin are used. Using speed and separation, the robot’s speed is controlled based on the nearest location of humans accurate to their body shape. The computer-vision safety system is compared to a traditional laser measure. The system is evaluated in a controlled test, and in the field.

Computer-vision and lasers are shown to be equivalent by a measure of relationship and measure of agreement. R² is given as 0.999983. The two methods are systematically producing similar results, as the bias is close to zero, at 0.060 mm. Using Bland–Altman analysis, 95% of the differences lie within the limits of maximum acceptable differences.

In this paper an original model for future computer-vision safety systems is described which is equivalent to existing laser systems, identifies and adapts to particular humans and reduces the need to slow and stop systems thereby improving efficiency. The implication is that computer-vision can be used to substitute lasers and permit adaptive robotic control in human–robot collaboration systems.