IT graduates need a suite of technical competencies and soft skills married with an understanding of the social and business contexts of the systems that they build. To instill in students an awareness of current IT industry practice coupled with the broader impact of their discipline in society, academics from Victoria University and Federation University initiated an across-institutional collaboration. The initiative resulted in a common formative assessment task undertaken by teams of students enrolled in each institution’s professional development units. An initial survey of students was undertaken prior to the assessment task. The survey queried students’ perceptions of a broad range of professional attitudes and skill sets needed by IT professionals when compared to non-skilled workers. Upon the completion of the assessment task, students were surveyed again as to their perceptions of the importance of personal skills, technical competencies, professional and team working skills, workplace knowledge, and cultural awareness for their future professional lives. Comparisons of both surveys’ results revealed that the cohort had a greater appreciation of technical abilities and team-working skills post the assessment task.

An algorithm learning tool was developed for an introductory computer science class in a specialized science and technology high school in Japan. The tool presents lessons and simple visualizations that aim to facilitate teaching and learning of fundamental algorithms. Written tests and an evaluation questionnaire were designed and implemented along with the learning tool among the participants. The tool’s effect on the learning performance of the students was examined. The differences of the two types of visualizations offered by the tool, one with more input and control options and the other with fewer options, were analyzed. Based on the evaluation questionnaire, the scales with which the tool can be assessed according to its usability and pedagogical effectiveness were identified. After using the algorithm learning tool there was an increase in the posttest scores of the students, and those who used the visualization with more input and control options had higher scores compared to those who used the one with limited options. The learning objectives used to evaluate the tool correlated with the test performance of the students. Properties comprised of learning objectives, algorithm visualization characteristics, and interface assessment are proposed to be incorporated in evaluating an algorithm learning tool for novice learners.

Internship courses, unlike others, are multi-pronged because they require coordination at different levels. Typically, a faculty member coordinates the communication and implementation at each level to achieve the desired outcomes. We call the position that this faculty holds the “internship coordinator”. For the work of the internship coordinator to be successful, he/she may need to synchronize the work of the internship with all parties involved. Failure to coordinate at one level or another may affect the work of other parties involved in completing the internship for the students. This paper explains the experience of an internship program at the computer science department (COSC) at Indiana University Indiana University of Pennsylvania (IUP). We focus on the work of the internship coordinator for this program and his work to communicate and coordinate to successfully implement the internship experience for the students. We first discuss the theoretical foundation that led to the development of internship programs in academia and then elaborate on the multiple levels of the role of the internship coordinator in completing the internship experience for the students.

The number of online resources available for teaching and learning in higher education has been growing enormously during the last decade. A recent development is the emergence of Massive Open Online Courses (MOOCs) and of Open Educational Resources (OER). The result is a huge number of videos that are available on line. Can these videos enrich learning? As a pilot study we added sixteen videos to an existing introductory course in Human-Computer Interaction. This course is mandatory in the Bachelor programs Computer Science and Information Science (second year). Watching the videos was optional for the students. The videos originated for the most part from the MOOC Human-Computer Interaction, produced by Stanford University. We offered this course to a pilot group of eight students. The educational context was problem-based learning in distance education. The videos were welcomed by all of the students and were found to be useful in their learning process. The students watched the videos intensively and appreciated them very well. A main reason for the students to be positive about the videos was that they liked to alternate reading texts and watching videos.

The authors present the results of a study conducted at a comprehensive, urban, coeducational, land-grant university. A quasi-experimental design was chosen for this study to compare student performance in two different classroom environments, traditional versus flipped. The study spanned 3 years, beginning fall 2012 through spring 2015. The participants included 433 declared business majors who self-enrolled in several sections of the Management Information Systems course during the study. The results of the current study mirrored those of previous works as the instructional method impacted students’ final grade. Thus, reporting that the flipped classroom approach offers flexibility with no loss of performance when compared to traditional lecture-based environments.

Aim/Purpose: Bring your own device (BYOD) provides opportunities for both the organization and employees, but the adoption of BYOD also introduces risks. This case study of an organization’s BYOD program identifies key positive and negative influences on the adoption decision. Background: The consumerization of IT introduced the BYOD phenomenon into the enterprise environment. As mobile and Internet technologies improve employees are opting to use their personal devices to access organizational systems to perform their work tasks. Such devices include smartphones, tablets and laptop computers. Methodology: This research uses a case study approach to investigate how business priorities drive the adoption of BYOD and how resulting benefits and risks are realized and managed by the organization. Primary empirical data was collected using semi-structured interviews with 15 senior employees from a large South African financial services organization. Policy documents from the organization were analyzed as secondary data. Contribution: Thematic analysis of the data revealed six major themes: improving employee mobility; improving client service and experience; creating a competitive industry advantage; improving business processes; information security risks; and management best practices. Findings: The themes were analyzed using the Technology-Organization-Environment (TOE) framework, showing the key positive and negative influences on the adoption decision. Recommendations for Practitioners: Organizations need to clearly understand the reasons they want to introduce BYOD in their organizations. The conceptual framework can be applied by practitioners in their organizations to achieve their BYOD business objectives. Recommendations for Researchers: BYOD remains an important innovation for organizations with several aspects worthy of further study. The TOE framework presents a suitable lens for analysis, but other models should also be considered. Impact on Society: The findings show that organizations can use BYOD to improve client service, gain competitive advantage, and improve their processes using their digital devices and backend systems. The BYOD trend is thus not likely to go away anytime soon. Future Research: The applicability of findings should be validated across additional contexts. Additional models should also be used.

Aim/Purpose: Drone technology has been increasingly used in education. This paper reports a study of assessing teachers’ readiness and training needs for using drone technology in their teaching. Background: New technology promotes new ways of practices. With the sophisticated design and the affordance to explore our world from a bird’s eye perspective, a drone has been increasingly used to support science, technology, engineering, and mathematics education. However, it also brings challenges to teachers to integrate drone technology in their teaching. It is therefore important to obtain a better understanding of various aspects of integrating drone technology in education. Methodology: A group of pre-service teachers was engaged in a case study conducted using a designed-based approach. The participants were randomly assigned into three groups. They were required to develop lesson plans with the application of drone technology in teaching. The lesson plans were subsequently analyzed using the TPCK framework to identify teachers’ readiness and training needs. Findings: The participants, to a large extent, have sufficient competence to master the skills and knowledge of drone technology and to integrate it into their teaching. However, they were required to strengthen the pedagogical knowledge, subject content knowledge, and technological content knowledge in order to maximize the potential benefits of drone technology in education. Contribution: This paper reports the level of readiness and training needs of teachers regarding the use of drone technology in their teaching. Recommendations for Practitioners: To conduct teacher training regarding the use of drone technology in education, a particular focus should be put on enhancing teachers’ pedagogical knowledge, subject content knowledge, and technological content knowledge. Recommendations for Researchers: Researcher may further explore the strategies to integrate drone technology in teaching. Impact on Society: This paper suggests the area of teacher training regarding the use of drone technology in education. The teaching and learning effectiveness could be improved. Future Research: Future research may study the safety issue and ethical issue of using a drone in education.

Aim/Purpose: The aim of this project was to explore a method to enable an updated under-standing of digital literacy to be implemented in curricula in an environment of an existing, but outdated, understanding of digital literacy. . Background: The changing healthcare environment increasingly emphasizes the importance of digital literacy skills; therefore academics in the optometry discipline at Deakin University sought to better understand where digital literacy skills were taught in their program, and whether delivery was implicit or explicit. Methodology: This case study describes a systematic review of the optometric curriculum to first identify where and what digital literacy skills are currently being addressed in the curriculum, identify the gaps, and develop a strategy to address the gaps. Contribution: The main outcome of this work is the development of a spiraling curriculum to support the development of digital literacy skills required in later units of the program and for clinical practice post-graduation. Findings: Although the definition of digital literacy may be outdated, the digital literacy capabilities being addressed in the curriculum had grown as digital technology use by staff and students had expanded. This, together with the realization that students were not as digitally capable as expected, indicated that teaching digital literacy skills needed to be made overt throughout the curriculum. Recommendations for Practitioners: The process developed through this case study provides a strong foundation for course teams, curriculum developers and educational designers to efficiently analyze digital literacy expectations in existing, accredited health-related curricula and improve the curricula by more overtly embedding digital literacy teaching into it. Impact on Society: Graduates of the amended program of study are expected to be better prepared to undertake their future careers in a digitally enhanced and disrupted environment. Future Research: The framework will be used to explore digital literacy teaching practices in other disciplines. A systematic evaluation will be undertaken to identify the benefits and short comings of using the framework. The elements that make up the new definition of digital literacy need to be better articulated to allow curriculum developers to be better informed as to how to interpret the framework in their context.

Aim/Purpose: One of the most fascinating developments in computer user interfaces in recent years is the rise of “chatbots”. Yet extent information system (IS) curriculum lacks teaching resources on chatbots programming.. Background: To better prepare students for this new technological development and to enhance the IS curriculum, we introduce a project that teaches students how to program simple chatbots, including a transactional chatbot and a conversational chatbot. Methodology: We demonstrated a project that teaches students how to program two types of simple chatbots: a transactional chatbot and a conversational chatbot. We also conducted a survey to examine students’ perceptions on their learning experience. Findings: Our survey on students’ perception of the project finds that learning chatbots is deemed very useful because chatbot programming projects have enabled the students to understand the subject better. We also found that social influence has positively motivated the students to learn chatbot programming. Though most of the students have no prior experiences programming chatbots, their self-efficacy towards chatbot programming remained high after working through the programming project. Despite the difficult tasks, over 71% of respondents agree to various degrees that chatbot programming is fun. Though most students agree that chatbot programming is not easy to learn, more than 70% of respondents indicated that they will use or learn chatbots in the near future. The overwhelmingly positive responses are impressive given that this is the first time for the students to program and learn chatbots. Recommendations for Practitioners: In this article, we introduced a step by step project on teaching chatbot programming in an information systems class. Following the project instructions, students can get their first intelligent chatbots up and running in a few hours using Slack. This article describes the project in detail as well as students’ perceptions. Recommendations for Researchers: We used UTAUT model to measure students’ perception of the projects. This study could be of value to researchers studying students’ technology learning and adoption behaviors. Impact on Society: To our best knowledge, pedagogical resources that teach IS students how to program chatbots, especially the introductory level materials, are limited. We hope this teaching case could be of value for IS educators when introducing IS students to the wonderful field of chatbot programming. Future Research: For future work, we plan to expand the teaching resources to cover more advanced chatbot programming projects, such as on how to make chatbot more human-like.

Aim/Purpose: This brief paper will provide preliminary insight into an institutions effort to help students understand the application of the scientific method as it applies to the business discipline through the creation of a dedicated, required course added to the curriculum of a mid-Atlantic minority-serving institution. In or-der to determine whether the under-consideration course satisfies designated student learning outcomes, an assessment regime was initiated that included examination of rubric data as well as the administration of a student perception survey. This paper summarizes the results of the early examination of the efficacy of the course under consideration. Background: A small, minority-serving, university located in the United States conducted an assessment and determined that students entering a department of business following completion of their general education science requirements had difficulties transferring their understanding of the scientific method to the business discipline. Accordingly, the department decided to create a unique course offered to sophomore standing students titled Principles of Scientific Methods in Business. The course was created by a group of faculty with input from a twenty person department. Methodology: Rubrics used to assess a course term project were collected and analyzed in Microsoft Excel to measure student satisfaction of learning goals and a student satisfaction survey was developed and administered to students enrolled in the course under consideration to measure perceived course value. Contribution: While the scientific method applies across the business and information disciplines, students often struggle to envision this application. This paper explores the implications of a course specifically purposed to engender the development and usage of logical and scientific reasoning skills in the business discipline by students in the lower level of an bachelors degree program. The information conveyed in this paper hopefully makes a contribution in an area where there is still an insufficient body of research and where additional exploration is needed. Findings: For two semesters rubrics were collected and analyzed representing the inclusion of 53 students. The target mean for the rubric was a 2.8 and the overall achieved mean was a 2.97, indicating that student performance met minimal expectations. Nevertheless, student deficiencies in three crucial areas were identified. According to the survey findings, as a result of the class students had a better understanding of the scientific method as it applies to the business discipline, are now better able to critically assess a problem, feel they can formulate a procedure to solve a problem, can test a problem-solving process, have a better understanding of how to formulate potential business solutions, understand how potential solutions are evaluated, and understand how business decisions are evaluated. Conclusion: Following careful consideration and discussion of the preliminary findings, the course under consideration was significantly enhanced. The changes were implemented in the fall of 2020 and initial data collected in the spring of 2021 is indicating measured improvement in student success as exhibited by higher rubric scores. Recommendations for Practitioners: These initial findings are promising and while considering student success, especially as we increasingly face a greater and greater portion of under-prepared students entering higher education, initiatives to build the higher order thinking skills of students via transdisciplinary courses may play an important role in the future of higher education. Recommendations for Researchers: Additional studies of transdisciplinary efforts to improve student outcomes need to be explored through collection and evaluation of rubrics used to assess student learning as well as by measuring student perception of the efficacy of these efforts. Impact on Society: Society needs more graduates who leave universities ready to solve problems critically, strategically, and with scientific reasoning. Future Research: This study was disrupted by the COVID-19 pandemic; however, it is resuming in late 2021 and it is the hope that a robust and detailed paper, with more expansive findings will eventually be generated.

Aim/Purpose: Designing augmented reality (AR) experiences for education, health or entertainment involves multidisciplinary teams making design decisions across several areas. The goal of this paper is to present a classification schema that describes the design choices when constructing an AR interactive experience. Background: Existing extended reality schema often focuses on single dimensions of an AR experience, with limited attention to design choices. These schemata, combined with an analysis of a diverse range of AR applications, form the basis for the schema synthesized in this paper. Methodology: An extensive literature review and scoring of existing classifications were completed to enable a definition of seven design dimensions. To validate the design dimensions, the literature was mapped to the seven-design choice to represent opportunities when designing AR iterative experiences. Contribution: The classification scheme of seven dimensions can be applied to communicating design considerations and alternative design scenarios where teams of domain specialists need to collaborate to build AR experiences for a defined purpose. Findings: The dimensions of nature of reality, location (setting), feedback, objects, concepts explored, participant presence and interactive agency, and style describe features common to most AR experiences. Classification within each dimension facilitates ideation for novel experiences and proximity to neighbours recommends feasible implementation strategies. Recommendations for Practitioners: To support professionals, this paper presents a comprehensive classification schema and design rationale for AR. When designing an AR experience, the schema serves as a design template and is intended to ensure comprehensive discussion and decision making across the spectrum of design choices. Recommendations for Researchers: The classification schema presents a standardized and complete framework for the review of literature and AR applications that other researchers will benefit from to more readily identify relevant related work. Impact on Society: The potential of AR has not been fully realized. The classification scheme presented in this paper provides opportunities to deliberately design and evaluate novel forms of AR experience. Future Research: The classification schema can be extended to include explicit support for the design of virtual and extended reality applications.

Power differences affect implementation of information and communication technology (ICT) in a way that creates differences in ICT use. Involuntary non-use of new ICT at work occurs when employees want to use the new technology, but are unable to due to factors beyond their control. Findings from an in-depth qualitative study show how involuntary non-use of new ICT can be attributed to power differences between occupational groups in the same organization. The findings suggest that experience is a moderating variable and that closeness to formal power holders as well as closeness to the new technology increases the probability for expert control of the ICT-organization processes. These power differences favor ICT experts over ICT novices and result in a high-quality learning environment for the ICT experts characterized by autonomy, inclusion, and adequate work processes and technological solutions. The ICT novices try to navigate in a learning-hostile work environment characterized by marginalization through expert control, isolation, and inadequate work processes and technological solutions. This led to involuntary non-use by the ICT novices, while the experts became more proficient in ICT use. These findings give managers facing a technological organizational change tools to understand important mechanisms for implementing the change in their own organization, and help them take the right actions to integrate new technology and new organization of work.

The purpose of the study is to identify influential factors in the use of collaborative networks within the context of manufacturing. The study aims to investigate factors that influence employees’ learning, and to bridge the gap between theory and praxis in collaborative networks in manufacturing. The study further extends the boundary of a collaborative network beyond enterprises to include suppliers, customers, and external stakeholders. It provides a holistic perspective of collaborative networks within the complexity of the manufacturing environment, based on empirical evidence from a questionnaire survey of 246 respondents from diverse manufacturing industries. Drawing upon the socio-technical systems (STS) theory, the study presents the theoretical context and interpretations through the lens of manufacturing. The results show significant influences of organizational support, promotive interactions, positive interdependence, internal-external learning, perceived effectiveness, and perceived usefulness on the use of collaborative networks among manufacturing employees. The study offers a basis of empirical validity for measuring collaborative networks in organizational learning and knowledge/information sharing in manufacturing.

Universities have traditionally been leaders in the field of knowledge production, research, and societal development. They are expected to be drivers of innovation, thereby contributing to the development of a learning society. The array of challenges facing universities in Nigeria and other developing countries forces one to question their levels of innovation. While knowledge management has been identified as a strategy for driving innovative processes in business organizations, there is a paucity of literature on its application in Nigerian universities. This paper, therefore, proposes a conceptual model which Nigerian universities could adopt, in order to drive innovation and performance. As the paper is conceptual in nature, a literature survey was conducted to examine the concept of knowledge management and its application in higher education institutions. Findings from the literature informed the development of a conceptual model describing ways in which universities can adopt knowledge management practices and strategies in order to drive innovation and improve performance. The conceptual model proposed in this paper could serve as a basis for empirical investigations on knowledge management processes in universities. The paper concludes that, while knowledge management has the potential for improving performance within universities, the proposed model must be subjected to empirical validation for further amendments and improvements.

Recently ERP implementation has seen increasing significance in different sectors. The research related to the implementation issues of ERP has also increased during the past decade. Particularly the behavioral aspects of ERP implementations have been researched in terms of identifying appropriate frameworks, critical success factors, perception and attitude of users and managers, the role of change agents, leadership, etc. This conceptual review summarizes some of the studies done on the above aspects and suggests further research areas. It is suggested that leadership competencies, learning attitude of the users, and organizational power dynamics can be potential areas of research in the context of ERP implementation.

Helping a company organize and capture the knowledge used by its employees and business processes is a daunting task. In this work we examine several proposed methodologies and synthesize them into a new methodology that we demonstrate through a case study of an electric power distribution company. This is a practical research study. First, the research approach for creating the knowledge map is process-oriented and the processes are considered as the main elements of the model. This research was done in four stages: literature review, model editing, model validation and case study. The Delphi method was used for the research model validation. Some of the important outputs of this research were mapping knowledge flows, determining the level of knowledge assets, expert-area knowledge map, preparing knowledge meta-model, and updating the knowledge map according to the company’s processes. Besides identifying, auditing and visualizing tacit and explicit knowledge, this knowledge mapping enables us to analyze the knowledge areas’ situation and subsequently help us to improve the processes and overall performance. So, a process map does knowledge mapping in a clear and accurate frame. Once the knowledge is used in processes, it creates value.

Aim/Purpose: This work aims to present a knowledge modeling technique that supports the representation of the student learning process and that is capable of providing a means for self-assessment and evaluating newly acquired knowledge. The objective is to propose a means to address the pedagogical challenges in m-learning by aiding students’ metacognition through a model of a student with the target domain and pedagogy. Background: This research proposes a framework for social and meta-cognitive support to tackle the challenges raised. Two algorithms are introduced: the meta-cognition algorithm for representing the student’s learning process, which is capable of providing a means for self-assessment, and the social group mapping algorithm for classifying students according to social groups. Methodology : Based on the characteristics of knowledge in an m-learning system, the cognitive knowledge base is proposed for knowledge elicitation and representation. The proposed technique allows a proper categorization of students to support collaborative learning in a social platform by utilizing the strength of m-learning in a social context. The social group mapping and metacognition algorithms are presented. Contribution: The proposed model is envisaged to serve as a guide for developers in implementing suitable m-learning applications. Furthermore, educationists and instructors can devise new pedagogical practices based on the possibilities provided by the proposed m-learning framework. Findings: The effectiveness of any knowledge management system is grounded in the technique used in representing the knowledge. The CKB proposed manipulates knowledge as a dynamic concept network, similar to human knowledge processing, thus, providing a rich semantic capability, which provides various relationships between concepts. Recommendations for Practitioners: Educationist and instructors need to develop new pedagogical practices in line with m-learning. Recommendation for Researchers: The design and implementation of an effective m-learning application are challenging due to the reliance on both pedagogical and technological elements. To tackle this challenge, frameworks which describe the conceptual interaction between the various components of pedagogy and technology need to be proposed. Impact on Society: The creation of an educational platform that provides instant access to relevant knowledge. Future Research: In the future, the proposed framework will be evaluated against some set of criteria for its effectiveness in acquiring and presenting knowledge in a real-life scenario. By analyzing real student interaction in m-learning, the algorithms will be tested to show their applicability in eliciting student metacognition and support for social interactivity.

Aim/Purpose: This study aims to investigate the relationship between the knowledge management (KM) process and the performance of construction companies. The ultimate goal is to promote better efficiency and competitive advantage in the construction industry by making the best use of knowledge. Background: While attention to KM is currently on the rise, as shown by the number of studies conducted, research on KM in the construction industry of Indonesia is still very rare. However, organizational learning as the implementation of KM provides an opportunity to improve the construction industry, and thus there is an urgency to conduct research on this topic. Methodology: This study lasted for three months and used the survey method, with 100 questionnaires distributed to contractors of grade 6 and 7 on the islands of Java and Borneo in Indonesia. A total of 54 returned questionnaires were deemed complete and eligible for further analysis. Data analysis was performed using the structural equation modeling method with partial least squares (SEM PLS). Contribution: This study helps to measure the relationship value of the KM process and company performance. Findings: The results of this study indicate that the process of KM has a significant and positive influence on company performance, and there is a positive interaction in the process of KM and company performance as well. Recommendations for Practitioners: Construction companies need to perceive that activities undertaken in a construction project should always be assumed to be a KM process in order to make strategic and effective decisions that can result in improvements to customers, finance, internal business, learning, and growth. Recommendation for Researchers: Research on the KM process and information technology needs to be developed more, so that construction companies can apply this knowledge to explore problems and create solutions, resulting in methods to facilitate efficiency and effectiveness. Impact on Society: This paper helps to understand that KM activities provide initial benefits and guidance for companies that want to apply KM. Future Research: Innovative and new ideas to cultivate the KM process in the construction industry need to be explored and developed to improve the implementation.

Aim/Purpose: This study describes a conceptual model, based on the principles of concept algebra that can provide intelligent academic advice using adaptive, knowledge-based feedback. The proposed model advises students based on their traits and academic history. The system aims to deliver adaptive advice to students using historical data from previous and current students. This data-driven approach utilizes a cognitive knowledge-based (CKB) model to update the weights (values that indicate the strength of relationships between concepts) that exist between student’s performances and recommended courses. Background: A research study conducted at the Public Authority for Applied Education and Training (PAAET), a higher education institution in Kuwait, indicates that students’ have positive perceptions of the e-Advising system. Most students believe that PAAET’s e-Advising system is effective because it allows them to check their academic status, provides a clear vision of their academic timeline, and is a convenient, user-friendly, and attractive online service. Student advising can be a tedious element of academic life but is necessary to fill the gap between student performance and degree requirements. Higher education institutions have prioritized assisting undecided students with career decisions for decades. An important feature of e-Advising systems is personalized feedback, where tailored advice is provided based on students' characteristics and other external parameters. Previous e-Advising systems provide students with advice without taking into consideration their different attributes and goals. Methodology: This research describes a model for an e-Advising system that enables students to select courses recommended based on their personalities and academic performance. Three algorithms are used to provide students with adaptive course selection advice: the knowledge elicitation algorithm that represents students' personalities and academic information, the knowledge bonding algorithm that combines related concepts or ideas within the knowledge base, and the adaptive e-Advising model that recommends relevant courses. The knowledge elicitation algorithm acquires student and academic characteristics from data provided, while the knowledge bonding algorithm fuses the newly acquired features with existing information in the database. The adaptive e-Advising algorithm provides recommended courses to students based on existing cognitive knowledge to overcome the issues associated with traditional knowledge representation methods. Contribution: The design and implementation of an adaptive e-Advising system are challenging because it relies on both academic and student traits. A model that incorporates the conceptual interaction between the various academic and student-specific components is needed to manage these challenges. While other e-Advising systems provide students with general advice, these earlier models are too rudimentary to take student characteristics (e.g., knowledge level, learning style, performance, demographics) into consideration. For the online systems that have replaced face-to-face academic advising to be effective, they need to take into consideration the dynamic nature of contemporary students and academic settings. Findings: The proposed algorithms can accommodate a highly diverse student body by providing information tailored to each student. The academic and student elements are represented as an Object-Attribute-Relationship (OAR) model. Recommendations for Practitioners: The model proposed here provides insight into the potential relationships between students’ characteristics and their academic standing. Furthermore, this novel e-Advising system provides large quantities of data and a platform through which to query students, which should enable developing more effective, knowledge-based approaches to academic advising. Recommendation for Researchers: The proposed model provides researches with a framework to incorporate various academic and student characteristics to determine the optimal advisory factors that affect a student’s performance. Impact on Society: The proposed model will benefit e-Advising system developers in implementing updateable algorithms that can be tested and improved to provide adaptive advice to students. The proposed approach can provide new insight to advisors on possible relationships between student’s characteristics and current academic settings. Thus, providing a means to develop new curriculums and approaches to learning. Future Research: In future studies, the proposed algorithms will be implemented, and the adaptive e-Advising model will be tested on real-world data and then further improved to cater to specific academic settings. The proposed model will benefit e-Advising system developers in implementing updateable algorithms that can be tested and improved to provide adaptive advisory to students. The approach proposed can provide new insight to advisors on possible relationships between student’s characteristics and current academic settings. Thus, providing a means to develop new curriculums and approaches to course recommendation.

Aim/Purpose: This paper examines the behavior of financial firm employees with regard to information security procedures instituted within their organization. Furthermore, the effect of information security awareness and its importance within a firm is explored. Background: The study focuses on employees’ attitude toward compliance with information security policies (ISP), combined with various norms and personal abilities. Methodology: A self-reported questionnaire was distributed among 202 employees of a large financial Corporation Contribution: As far as we know, this is the first paper to thoroughly explore employees’ awareness of information system procedures, among financial organizations in Israel, and also the first to develop operative recommendations for these organizations aimed at increasing ISP compliance behavior. The main contribution of this study is that it investigates compliance with information security practices among employees of a defined financial corporation operating under rigid regulatory governance, confidentiality and privacy of data, and stringent requirements for compliance with information security procedures. Findings: Our results indicate that employees’ attitudes, normative beliefs and personal capabilities to comply with firm’s ISP, have positive effects on the firm’s ISP compliance. Also, employees’ general awareness of IS, as well as awareness to ISP within the firm, positively affect employees’ ISP compliance. Recommendations for Practitioners: This study can help information security managers identify the motivating factors for employee behavior to maintain information security procedures, properly channel information security resources, and manage appropriate information security behavior. Recommendation for Researchers: Researchers can see that corporate rewards and sanctions have significant effects on employee security behavior, but other motivational factors also reinforce the ISP’s compliance behavior. Distinguishing between types of corporations and organizations is essential to understanding employee compliance with information security procedures. Impact on Society: This study offers another level of understanding of employee behavior with regard to information security in organizations and comprises a significant contribution to the growing knowledge in this area. The research results form an important basis for IS policymakers, culture designers, managers, and those directly responsible for IS in the organization. Future Research: Future work should sample employees from another type of corporation from other fields and should apply qualitative analysis to explore other aspects of behavioral patterns related to the subject matter.

Aim/Purpose: This paper reports a case study of organizational transition from a non-competitive selection method to a novel bidding method for the selection of consultants in the Architectural and Engineering (A/E) industry. Background: Public procurement agencies are increasingly relying on external consultants for the design of construction projects. Consultant selection can be based on either competitive bidding, or quality-based criteria, or some combination between these two approaches. Methodology: Different sources of information were reviewed: internal documents, and quantitative data from the enterprise software platform (ERP). In addition, informal and unstructured interviews were conducted with relevant officials. Contribution: As there are mixed opinions in the scientific literature regarding the use of competitive bidding for the selection of consultants in the A/E industry, this paper contributes a detailed review of a transition to a competitive selection method and provides a financial and qualitative comparison between the two methods. In addition, the method implemented is novel, as it delegates most of the responsibility of hiring and managing consultants to one main contractor. Findings: While the new selection method was intended to reduce bureaucratic overload, it has unexpectedly also succeeded to reduce costs as well. Recommendations for Practitioners: It may be more efficient and profitable to adopt the selection method described in this study. Recommendation for Researchers: Similar methods can be applied to other industries successfully. Impact on Society: Our method was applied in a public organization and resulted in a better outcome, both financial and managerial. Adopting this approach can benefit public budgets. Future Research: The selection, data storage, and analysis methods are interrelated components. Future analysis of these components can help better shape the consultant selection process.

Aim/Purpose: This research investigates the influence of soft skills on graduates’ employability in the technology industry, using the technology industry sector in Malaysia as a case. Background: Organizations are looking for appropriate mechanisms to hire qualified employees with strong soft skills and hard skills. This requires that job candidates possess a set of qualifications and skills which impact their employability. Methodology: Fuzzy Delphi analysis was conducted as preliminary study to identify the critical soft skills required by technology industry sector. The preliminary study produced ten critical soft skills to form a conceptual model of their influence on employability. Then, an online questionnaire survey was distributed in two industry companies in Malaysia to collect research data, and regression analysis was conducted to validate the conceptual model. Contribution: This research focuses on the influence of soft skills on graduate employability in the technology industry sector, since the selection of the best candidate in the industry will improve employee performance and lead to business success. Findings: The results of regression analysis confirmed that Communication skills, Attitude, Integrity, Learnability, Motivation, and Teamwork are significantly correlated with employability, which means that these soft skills are the critical factors for employability in Malaysian technology companies. Recommendations for Practitioners: The model proposed in this article can be used by employers to give better assessment of candidates’ compatibility with the jobs available. Impact on Society: This research highlights the critical soft skills required by technology industry sector, which will reduce the unemployment percentages among graduates. Future Research: More studies are required to examine the soft skills found in the literature and to define the most important skills from a general perspective of the industry. Future research should assess the moderating role of other variables, such as skills gap, employee performance, and employee knowledge. Furthermore, it is recommended to conduct similar studies of soft skills for employability in other countries.

Aim/Purpose: This research aims to analyze the effect of human resource management on humanitarian operations performance, using humanitarian organizations in Malaysia as a case. Background: Humanitarian organizations need to develop and continue effective on-the-job human resource management, such as training and development and managing employee performance to enhance the performance of their humanitarian operations. Methodology: The sampling technique that was conducted is probability sampling. In particular, the technique is called stratified sampling. This technique is chosen because it is involving the division of a population into a smaller group, called “strata”. The questionnaire survey was distributed to humanitarian organizations in Malaysia to collect research data, and PLS-SEM analysis was conducted to validate the conceptual model. Contribution: This research focuses on the effect of human resource management on humanitarian operations performance in humanitarian organizations with consistent training to ensure successful humanitarian operations. Findings: The results of PLS-SEM analysis confirmed that Training and Employee Development, Recruitment and Employee Selection, and Communicative Management Style are significantly correlated with humanitarian operations performance, giving 75.7% variations which means that these human resource management are critical factors for increasing humanitarian operations performance in Malaysian humanitarian organizations. Recommendations for Practitioners: This research will enhance humanitarian operations performance for humanitarian organizations, in-line policies outlined under the Malaysia National Security Council Directive No. 20, and benefit the field of disaster management. Recommendation for Researchers: This research can be used by the authorized individual involved in humanitarian operations to satisfy the needs of the victims, which ultimately contributes to the performance of these humanitarian organizations. Impact on Society: This research highlighted the human resource management that is vital for humanitarian organizations, which will increase humanitarian operations performance in an organization. Future Research: This study is conducted in the context of humanitarian organizations in Malaysia. It is unclear whether the key findings of this study can be generalized. Therefore, it is suggested that, in future research, the current research model should be extended to include different countries for validation.

Aim/Purpose: The understanding of disease spread dynamics in the context of air travel is crucial for effective disease detection and epidemic intelligence. The Susceptible-Exposed-Infectious-Recovered-Hospitalized-Critical-Deaths (SEIR-HCD) model proposed in this research work is identified as a valuable tool for capturing the complex dynamics of disease transmission, healthcare demands, and mortality rates during epidemics. Background: The spread of viral diseases is a major problem for public health services all over the world. Understanding how diseases spread is important in order to take the right steps to stop them. In epidemiology, the SIS, SIR, and SEIR models have been used to mimic and study how diseases spread in groups of people. Methodology: This research focuses on the integration of air traffic network data into the SEIR-HCD model to enhance the understanding of disease spread in air travel settings. By incorporating air traffic data, the model considers the role of travel patterns and connectivity in disease dissemination, enabling the identification of high-risk routes, airports, and regions. Contribution: This research contributes to the field of epidemiology by enhancing our understanding of disease spread dynamics through the application of the SIS, SIR, and SEIR-HCD models. The findings provide insights into the factors influencing disease transmission, allowing for the development of effective strategies for disease control and prevention. Findings: The interplay between local outbreaks and global disease dissemination through air travel is empirically explored. The model can be further used for the evaluation of the effectiveness of surveillance and early detection measures at airports and transportation hubs. The proposed research contributes to proactive and evidence-based strategies for disease prevention and control, offering insights into the impact of air travel on disease transmission and supporting public health interventions in air traffic networks. Recommendations for Practitioners: Government intervention can be studied during difficult times which plays as a moderating variable that can enhance or hinder the efficacy of epidemic intelligence efforts within air traffic networks. Expert collaboration from various fields, including epidemiology, aviation, data science, and public health with an interdisciplinary approach can provide a more comprehensive understanding of the disease spread dynamics in air traffic networks. Recommendation for Researchers: Researchers can collaborate with international health organizations and authorities to share their research findings and contribute to a global understanding of disease spread in air traffic networks. Impact on Society: This research has significant implications for society. By providing a deeper understanding of disease spread dynamics, it enables policymakers, public health officials, and practitioners to make informed decisions to mitigate disease outbreaks. The recommendations derived from this research can aid in the development of effective strategies to control and prevent the spread of infectious diseases, ultimately leading to improved public health outcomes and reduced societal disruptions. Future Research: Practitioners of the research can contribute more effectively to disease outbreaks within the context of air traffic networks, ultimately helping to protect public health and global travel. By considering air traffic patterns, the SEIR-HCD model contributes to more accurate modeling and prediction of disease outbreaks, aiding in the development of proactive and evidence-based strategies to manage and mitigate the impact of infectious diseases in the context of air travel.

Aim/Purpose: Social commerce is an emergent topic widely used for product and service sourcing. It helps companies to have frequent interaction with their customers and strive to achieve a competitive advantage. Yet there is only little empirical evidence focusing on social commerce and its adoption in SMEs to date. This study investigates the key factors affecting social commerce adoption in SMEs. This research designed a theoretical model using the Technology, Organization, and Environment (TOE) Model Background: Despite its rapid growth and usage, social commerce is still in its evolution phase and its current conception is vague and restricted. Therefore, considering the benefits of social commerce for consumers and businesses, it is important to explore the concept of social commerce. Methodology: The research floated a self-administered questionnaire and surveyed 218 Jordanian SME businesses. The data was analyzed using smart PLS and the results were drawn that covers the detail of the characteristics of respondents, study descriptive, results of regressions assumptions, e.g., data normality, reliability, validity, common method biases, and description of the measurement model, followed by the findings of hypothesis analysis. Contribution: This study has many significant contributions to the existing studies on firms’ adoption of social commerce. It indicates that organizational readiness from the organizational perspective and consumer pressure from the environmental dimension of the TOE model are significant influential elements in the adoption of social commerce in business, followed by high-level management support and trading partner pressure, respectively. This shows that organizational readiness to adopt social commerce and consumer pressure has a vital role in Jordanian SMEs’ adopting social commerce. Findings: The results were drawn from a survey of 218 Jordanian SMEs, indicating that organizational readiness from an organizational dimension and consumer pressure environmental perspective, followed by top management’s support and trading partner pressure, significantly predicts the adoption intentions of social commerce. However, perceived usefulness and security concerns from a technological context do not significantly impact behavioral intentions to utilize social commerce. Recommendations for Practitioners: Lack of awareness about new technology and its potential benefits are not well diffused in the Jordanian context. In short, both organizational and environmental dimensions of the TOE framework significantly influence the behavioral intentions for social commerce adoption in the Jordanian context whereas the third-dimension technological factors do not affect the behavioral intentions of SMEs to adopt social commerce. In the technological context, SMEs need to invest in technology and must spread awareness among Jordanian consumers about the potential benefits of technology and must encourage them to use social commerce platforms to interact because of the high significance of social commerce for businesses as it facilitates the quick completion of tasks, enhances the productivity, and improves the chances of high profitability. Recommendation for Researchers: First, the study is limited in scope as it discusses the direct links between the TOE framework, behavioral intentions to use social commerce, and the actual usage of social commerce in the Jordanian context rather than testing the mediation, and moderation. Future research may examine the mediators and moderators in the conceptual model. Second, the research examined the behavioral intentions of SMEs rather than consumers to adopt social commerce. Further research might consider the consumer perspective on social commerce. Impact on Society: This research aims to identify the key factor that impact the behavioral intentions of SME businesses to practice social commerce. The theoretical underpinning of the study lies in the TOE model, as using its basic assumptions the conceptual grounds and hypothesis of the study are developed. Future Research: The study findings are not generalizable in different contexts as it was specifically conducted by gathering data from the Jordanian population. However future studies may consider different contexts, sectors, cultures, or countries to examine the model. Lastly, the research collected data using convenience sampling from 218 SMEs in Jordan, which may create difficulty in the generalizability of the research, so needs to examine a larger sample in future studies.

Aim/Purpose: In this study, we developed a recommendation system model designed to support decision-makers in identifying consumers eligible for pay-later options via consensus-based decision-making. This approach was chosen due to the high and complex risks involved, such as delayed payments, challenges in reaching consumers, and issues of bad credit. Background: The “pay-later” option, which allows consumers to postpone payment for e-commerce purchases, offers convenience and flexibility but also introduces several challenges: (i) by enabling payment deferral, merchants face financial risks, including potential delays or defaults in payment, adversely affecting their cash flow and profitability; and (ii) this payment delay can also heighten the risk of fraud, including identity theft and unauthorized transactions. Methodology: This study initiated a risk analysis utilizing the ROAD process. Considering contemporary economic developments and advancements in neural networks, integrating these networks into risk assessment has become crucial. Consequently, model development involved the amalgamation of three deep learning methods – CNN (Convolutional Neural Networks), RNN (Recurrent Neural Networks), and LSTM (Long Short-Term Memory) – to address various risk alternatives and facilitate multi-stage decision-making recommendations. Contribution: Our primary contribution is threefold. First, our study identified potential consumers by prioritizing those with the smallest associated problem consequence values. Second, we achieved an optimal recall value using a candidate generator. Last, we categorized consumers to assess their eligibility for pay-later rights. Findings: The findings from this study indicate that our multi-stage recommendation model is effective in minimizing the risk associated with consumer debt repayment. This method of consumer selection empowers policymakers to make informed decisions regarding which consumers should be granted pay-later privileges. Recommendations for Practitioners: This recommendation system is proposed to several key parties involved in the development, implementation, and use of pay-later systems. These parties include E-commerce Executive Management for financial analysis and risk evaluation, the Risk Management Team to assess and manage risks related to users utilizing Pay-Later services, and Sales Managers to integrate Pay-Later services into sales strategies. Recommendation for Researchers: Advanced fraud detection mechanisms were implemented to prevent unauthorized transactions effectively. The goal was to cultivate user confidence in the safety of their financial data by ensuring secure payment processing. Impact on Society: Ensuring consumers understand the terms and conditions of pay-later arrangements, including interest rates, repayment schedules, and potential fees, is crucial. Providing clear and transparent information, along with educating consumers about their financial responsibilities, helps prevent misunderstandings and disputes. Future Research: Our future development plans involve the ongoing assessment of the system’s performance to enhance prediction accuracy. This includes updating models and criteria based on feedback and changes in economic or market conditions. Upholding compliance with security and data privacy regulations necessitates the implementation of protective measures to safeguard consumer information. The implementation of such a system requires careful consideration to ensure fairness and adherence to legal standards. Additionally, it is important to acknowledge that algorithms and models may evolve over time through the incorporation of additional data and continuous evaluations.