Search

The advent of Blockchain technology (BT) revolutionised the way remittance transactions are recorded. Banks and remittance organisations have shown a growing interest in exploring blockchain's potential advantages over traditional practices. This paper presents a data-driven predictive decision support approach as an innovative artefact designed for the blockchain-oriented remittance industry. Employing a theory-generating Design Science Research (DSR) approach, we have uncovered the emergence of predictive capabilities driven by transactional big data. The artefact integrates predictive analytics and Machine Learning (ML) to enable real-time remittance monitoring, empowering management decision-makers to address challenges in the uncertain digitised landscape of blockchain-oriented remittance companies. Bridging the gap between theory and practice, this research not only enhances the security of the remittance ecosystem but also lays the foundation for future predictive decision support solutions, extending the potential of predictive analytics to other domains. Additionally, the generated theory from the artifact's implementation enriches the DSR approach and fosters grounded and stakeholder theory development in the information systems domain., Comment: Ppaper has been accepted for presenting in the Australasian Conference on Information Systems 2023, Dec 6 to 8, Wellington, NZ

With the advancement in the marketing channel, the use of e-commerce has increased tremendously therefore the basic objective of this study is to analyze the impact of business analytics and decision support systems on e-commerce in small and medium enterprises. Small and medium enterprises are becoming a priority for economies as by implementing some policies and regulations these businesses could encourage gain development on an international level. The objective of this study is to analyze the impact of business analytics and decision support systems on e-commerce in small and medium enterprises that investigate the relationship between business analytics and decision support systems in e-commerce businesses. To evaluate the impact of both on e-commerce the, descriptive analysis approach is adopted that reviews the research of different scholars who adopted different plans and strategies to predict the relationship between e-commerce and business analytics. The study contributes to the literature by examining the impact of business analytics in SMEs and provides a comprehensive understanding of its relationship with the decision support system. After analyzing the impact of business analytics and decision support system in SMEs, the research also highlights some limitations and provide future recommendations that are helpful to overcome these limitations., Comment: DataCom Conf

AI has the potential to improve approaches to talent management enabling dynamic provisions through implementing advanced automation. This study aims to identify the new requirements for developing AI-oriented artifacts to address talent management issues. Focusing on enhancing interactions between professional assessment and planning attributes, the design artifact is an intelligent employment automation solution for career guidance that is largely dependent on a talent intelligent module and an individuals growth needs. A design science method is adopted for conducting the experimental study with structured machine learning techniques which is the primary element of a comprehensive AI solution framework informed through a proposed moderation of the technology-organization-environment theory., Comment: Working paper

Adopting a good health information system (HIS) is essential for providing high-quality healthcare. With rapid advances in technology in the healthcare industry in recent years, healthcare providers seek effective options to deal with numerous diseases and a growing number of patients, adopting advanced HIS such as for clinical decision support. While the clinical decision support systems (CDSS) can help medical personnel make better decisions, they may bring negative results due to a lack of understanding of the elements that influence GP's adoption of CDSS. This paper focuses on discovering obstacles that may contribute to the problems surrounding CDSS adoption. Thirty general practitioners were interviewed from different primary health centers in Saudi Arabia in order to determine the challenges and obstacles in the sector. While the outcome confirms that there are obstacles that affect the aspects, such as time risk, quality of the system used, slow Internet speed, user interface, lack of training, high costs, patient satisfaction, multiple systems used, technical support, computer skills, lack of flexibility, system update, professional skills and knowledge, computer efficiency and quality and accuracy of data.

The aged care sector in Australia faces significant challenges. While many of these issues have been clearly identified, their urgency has been further highlighted during the COVID-19 pandemic. Technology such as in-home monitoring is one way to address some of these challenges. However, the efficacy of technology must be considered together with its implementation and running costs to ensure that there is a return on investment, and it is economically viable as a solution. A pilot program was run in-home monitoring system to test the efficacy of this system. This paper focuses on an economic analysis to better understand the financial viability of such systems. Using a secondary analysis approach, the findings identified that revenue could be generated by providing carers with additional services such as real-time monitoring of the client, which can foster deeper relationships with the customer, along with savings of healthcare costs to carers, service providers and Government. Savings are related to the earlier intervention of critical events that are identified by the system, as delays in treatment of some critical events can create much more severe and costly health outcomes. Further health costs savings can be made via trend analysis which can show more nuanced health deterioration that is often missed. The implementation of preventative measures via this identification can reduce the chances of critical events occurring which have much higher costs. Overall, monitoring systems lead to a transition from a reactive to a preventative services offering, delivering more targeted and personalised care., Comment: The Paper is accepted to publish in a journal

Electronic commerce (e-Commerce) technologies have been increased over the past two decades in different business sectors. In particular, the technologies of B2C operations have significantly improved the productivity of online small businesses such as SMEs. Systematic literature review in this domain categorized different benefits but a limited number of studies on SME success from a view of an information systems (IS) research exists, which needs to be taken for further attention. Informing through a comprehensive analysis this study introduces a conceptual framework of the application of e-Commerce technologies in accelerating the SME operation. Content analysis methodology was adopted for generating the outcome associated with the success of the technologies in SMEs., Comment: Submitted to ICICT Conf 2022

Internet of things (IoT) has significantly altered the traditional lifestyle to a highly technologically advanced society. Some of the significant transformations that have been achieved through IoT are smart homes, smart transportation, smart city, and control of pollution. A considerable number of studies have been conducted and continue to be done to increase the use of technology through IoT. Furthermore, the research about IoT has not been done fully in improving the application of technology through IoT. Besides, IoT experiences several problems that need to be considered in order to get the full capability of IoT in changing society. This research paper addresses the key applications of IoT, the architecture of IoT, and the key issues affecting IoT. In addition, the paper highlights how big data analytics is essential in improving the effectiveness of IoT in various applications within society., Comment: Paper is presented to ICICT 2022 Conference

The phenomenon of innovation has been shifting away from focusing on tangible to intangible modernization with its vitalizing context. This shift appears vitally in innovation developed by individual end-users in organizations and societies, including the exploration of the intangible end-user innovation existence and impact in the household sector on a national scale. Some examples of intangible end-user innovation include technique, service, and user behavior. Although, there is a variety of intangible end-user innovation discussed in the literature, limited understanding is existed for constructing an efficient and comprehensive typology, which encompasses the nature of this innovation phenomenon. This research study explores this original phenomenon for proposing a new concept that will act as an overarching descriptor of innovation types: idea, object, and behavior. This proposed concept, relating to intangible innovation, will explain the sequence within one or many connected intangible activities that provide novelty to its end-user relative to previous activities and practices. Using a design science research approach, the study comprises two goals: a) identifying opportunities and issues to measure intangible inputs to the innovation and b) proposing a framework for extending the existing innovation theories that to better capture intangible end-user innovation and its diffusion insights in their online environment across nations, Comment: Conf paper

With the medical development in recent decades, the multiplicity of different diseases, and an increased number of patients, the use of an advanced healthcare information technology (HIT) such as a clinical decision support system (CDSS) has been of necessary to help general practitioners (GPs). CDSS may fail due to the failure to understand the factors influencing the GP's acceptance of CDSS. Identifying factors that promote acceptance of CDSS can be a vital aspect for its successful implementation. This study seeks to identify factors that influence the acceptance of CDSS in Saudi Arabia by GPs. This study relies mainly on the unified theory of acceptance and use of technology (UTAUT) which has been integrated with a task-technology fit (TTF) model and has applied a qualitative method to collect the data through using semi-structured interviews with 12 GPs. The study's results indicated that performance expectancy, effort expectancy, facilitating conditions, technology fit for the task, technology characteristics and task characteristics have all influenced the acceptance of CDSS. The results also indicated the need to extend the UTAUT model to investigate and explore other factors in GPs' acceptance of CDSS.

This paper is to create a basis of theoretical contribution for a new PhD thesis in the area of Clinical Decision Support Systems (CDSS) acceptance. Over the past three years, we conducted qualitative research into three distinctive phases to develop an extended Task-Technology Fit (TTF) Framework. These phases are for initiating requirement generation of the framework, discovering the factors of the framework through perspectives, and evaluating the new proposed framework. The new condition is related to developing country in which various sectors such as healthcare is mostly under attention. We conduct a new inspective for assisting decisions to support technology and its usefulness in this sector to integrate with other frameworks for assisting the value, use, and how can be better accepted in the context of healthcare professionals.

This paper provides a novel framework for maximizing the effectiveness of the Diabetes Group Education Program, which could be generalized in any similar problem context., Comment: The paper has been accepted for publishing and presenting at the Australasian Conference on Information Systems, Dec 2020, Wellington, NZ

Inspired by the unique properties of graphene, the focus in the literature is now on investigations of various two-dimensional (2D) materials with the aim to explore their properties for future applications. The group IV analogues of graphene, i.e., silicene, germanene and stanene have been intensively studied in recent years. However, their semi-metallic band structures hamper their use in electronic applications. Hence, the synthesis of 2D materials with band gaps of various sizes has attracted a large interest. Here, we report a successful preparation of a 2D Te-Ag binary alloy with a honeycomb structure. Angle-resolved photoelectron spectroscopy (ARPES) in combination with first-principles calculations using density functional theory (DFT) confirmed the formation of this binary alloy. The semiconducting property is verified by the ARPES data and a direct gap of ~0.7 eV is predicted by the DFT calculations., Comment: 7 pages, 3 figures and 2 figures in supplementary

Group V element analogues of graphene have attracted a lot attention recently due to their semiconducting band structures, which make them promising for next generation electronic and optoelectronic devices based on two-dimensional materials. Theoretical investigations predict high electron mobility, large band gaps, band gap tuning by strain, formation of topological phases, quantum spin Hall effect at room temperature, and superconductivity amongst others. Here, we report a successful formation of freestanding like monolayer arsenene on Ag(111). This was concluded from our experimental atomic and electronic structure data by comparing to results of our theoretical calculations. Arsenene forms a buckled honeycomb layer on Ag(111) with a lattice constant of 3.6 {\AA} showing an indirect band gap of about 1.4 eV as deduced from the position of the Fermi level pinning.

We study the "higher algebra" of spectral Mackey functors, which the first named author introduced in Part I of this paper. In particular, armed with our new theory of symmetric promonoidal $\infty$-categories and a suitable generalization of the second named author's Day convolution, we endow the $\infty$-category of Mackey functors with a well-behaved symmetric monoidal structure. This makes it possible to speak of spectral Green functors for any operad $O$. We also answer a question of A. Mathew, proving that the algebraic $K$-theory of group actions is lax symmetric monoidal. We also show that the algebraic $K$-theory of derived stacks provides an example. Finally, we give a very short, new proof of the equivariant Barratt-Priddy-Quillen theorem, which states that the algebraic $K$-theory of the category of finite $G$-sets is simply the $G$-equivariant sphere spectrum., Comment: 40 pages. v2: New authors added; somewhat awkward case-based system for the operad structures on effective Burnside infinity-categories from the previous version now streamlined, thanks to the (new) notion of symmetric promonoidal infinity-category

A molecular theory of liquid water is identified and studied on the basis of computer simulation of the TIP3P model of liquid water. This theory would be exact for models of liquid water in which the intermolecular interactions vanish outside a finite spatial range, and therefore provides a precise analysis tool for investigating the effects of longer-ranged intermolecular interactions. We show how local order can be introduced through quasi-chemical theory. Long-ranged interactions are characterized generally by a conditional distribution of binding energies, and this formulation is interpreted as a regularization of the primitive statistical thermodynamic problem. These binding-energy distributions for liquid water are observed to be unimodal. The gaussian approximation proposed is remarkably successful in predicting the Gibbs free energy and the molar entropy of liquid water, as judged by comparison with numerically exact results. The remaining discrepancies are subtle quantitative problems that do have significant consequences for the thermodynamic properties that distinguish water from many other liquids. The basic subtlety of liquid water is found then in the competition of several effects which must be quantitatively balanced for realistic results., Comment: 8 pages, 6 figures

A gaussian distribution of binding energies, but conditioned to exploit generally available information on packing in liquids, provides a statistical-thermodynamic theory of liquid water that is structurally non-committal, molecularly realistic, and surprisingly accurate. Neglect of fluctuation contributions to this gaussian model yields a mean-field theory that produces useless results. A refinement that accounts for sharper-than-gaussian behavior at high binding energies recognizes contributions from a discrete number of water molecules and permits a natural matching of numerically exact results. These gaussian models, which can be understood as vigorous simplifications of quasi-chemical theories, are applicable to aqueous environments where the utility of structural models based on geometrical considerations of water hydrogen bonding have not been established., Comment: 4 pages, 3 figures