(screenshots) An official statement from Google says the site was designed to "provide content owners an easy way to give us access to their content". (more screenshots)

In a long New York Times piece, top Googlers speculate about the future of advertising, including Google selling TV ads, using more personalized information, and links to store inventory information.

James Yu has a screenshot of a new design Google has been testing lately.

England's review of their last-gasp defeat by Australia was "brutal" but exactly what the squad needed, says wing Ollie Sleightholme.

Home Secretary Amber Rudd tells MPs David Anderson QC will oversee a review of the way recent attacks were handled. in a statement on the terror attacks in Manchester and London.

A DUP MP said flight cancellations between Belfast and London were "fast becoming a norm".

Policy and Resources will review infrastructure projects after deputies rejected income tax plans.

Despite raising £70,000, a group against second home planning permission cannot launch appeal.

The General Medical Council says there are interim conditions on the doctor's registration.

The plans will be re-examined after public support for keeping the school at its current site.

The move by Transport for Greater Manchester follows Saturday's crash, which injured 17 people.

However, a coroner says she was unable to conclude Amir Safi had intended to end his life.

Today our comment and review media lurch from Hot Takes to History without pausing for a moment to get a sense of what actually happened. The concept of the One Year Later Review was that we might be able to get a better understanding of what mattered and what effects it had with a little […]

I’ve ditched the usual blurb about “not being a movies person, but anyway…” because since I started going to the cinema regularly in 2022 I’ve turned into the kind of guy who downloads the London Film Festival brochure and meticulously...

This monthly series is probably more for my benefit than yours, but maybe your interest will be piqued by one of the reviews. Maybe you’ll scroll straight past. Maybe you’ll unsubscribe thinking what did I see in this blog in...

Have you ever reviewed a large file in SDL Trados Studio with numerous repetitions and struggled with confirmed segments not being propagated to the rest of the file? Here is what to do. Imagine you have a big file to … Continue reading →

The confluence of the internet of things (IoT) with smart grids has ushered in a paradigm shift in energy management, promising unparalleled efficiency, economic robustness and unwavering reliability. However, this integrative evolution has concurrently amplified the grid's susceptibility to cyber intrusions, casting shadows on its foundational security and structural integrity. Machine learning (ML) and deep learning (DL) emerge as beacons in this landscape, offering robust methodologies to navigate the intricate cybersecurity labyrinth of IoT-infused smart grids. While ML excels at sifting through voluminous data to identify and classify looming threats, DL delves deeper, crafting sophisticated models equipped to counteract avant-garde cyber offensives. Both of these techniques are united in their objective of leveraging intricate data patterns to provide real-time, actionable security intelligence. Yet, despite the revolutionary potential of ML and DL, the battle against the ceaselessly morphing cyber threat landscape is relentless. The pursuit of an impervious smart grid continues to be a collective odyssey. In this review, we embark on a scholarly exploration of ML and DL's indispensable contributions to enhancing cybersecurity in IoT-centric smart grids. We meticulously dissect predominant cyber threats, critically assess extant security paradigms, and spotlight research frontiers yearning for deeper inquiry and innovation.

The video game industry (VGI) has evolved considerably, transitioning from a niche market to a substantial sector. The VGI's magnitude and the societal implications tied to video game consumption have naturally piqued the interest of scholars in marketing and consumer behaviour. This research serves a dual purpose: firstly, it consolidates existing VG literature by evaluating articles, concepts, and methodologies, systematically tracing their evolution; secondly, it outlines potential directions and implications for forthcoming research. Within this literature, a predominant focus lies on articles investigating purchase decisions concerning VGs, followed by those exploring the integration of video game consumption into broader social contexts. Notably, a limited number of articles delve into player-game interactions and experiences within gaming worlds. This imbalance can be attributed to the fact that such inquiries are often suited to psychology and multidisciplinary journals, while the marketing discipline has predominantly addressed the VGI from a marketing management standpoint.

Although artificial intelligence provides a new method to gather, process, analyse data, generate insights, and offer customised solutions, such methods could change how marketers deal with customers, and there is a lack of literature to portray the application of artificial intelligence in marketing. This study aims to recognise and portray the use of artificial intelligence from a marketing standpoint, as well as to provide a conceptual framework for the application of artificial intelligence in marketing. This study uses a systematic literature review analysis as a research method to achieve the aims. Data from 142 articles were extracted from the Scopus database using relevant search terms for artificial intelligence and marketing. The systematic review identified significant usage of artificial intelligence in conversational artificial intelligence, content creation, audience segmentation, predictive analytics, personalisation, paid ads, sales forecasting, dynamic pricing, and recommendation engines and the bibliometric analysis produced the trend in co-authorship, citation, bibliographic coupling, and co-citation analysis. Practitioners and academics may use this study to decide on the marketing area in which artificial intelligence can be invested and used.

The aim of the study is to examine the determinants of digitalisation in public sector. This research is particularly relevant as digital transformation has become a crucial factor in modernising public sector and enhancing service delivery to citizens. The method of the systematic literature review (SLR) was implemented by searching documents on the Scopus database. The initial research reached the 7902 documents and after specifying the keywords the authors found 207 relevant documents. Finally; after the careful read of their abstracts and the use of inclusion and exclusion criteria; the most cited and relevant 32 papers constituted the final sample. Findings highlighted the focus of the literature on technological factors such as the sense of trust and safety as well as the ease of use in the adoption of digital governance; emphasising the need for effective; trustworthy and user-friendly digital services. The most discussed internal factors were leadership and organisational culture. The study offers a deeper understanding of the factors that shape the successful implementation of digital governance initiatives.

Aim/Purpose: To encourage students’ engagement in peer assessments and provide students with better-quality feedback, this paper describes a technique for author-reviewer matching in peer assessment systems – a Balanced Allocation algorithm. Background: Peer assessment concerns evaluating the work of colleagues and providing feedback on their work. This process is widely applied as a learning method to involve students in the progress of their learning. However, as students have different ability levels, the efficacy of the peer feedback differs from case to case. Thus, peer assessment may not provide satisfactory results for students. In order to mitigate this issue, this paper explains and evaluates an algorithm that matches the author to a set of reviewers. The technique matches authors and reviewers based on how difficult the authors perceived the assignment to be, and the algorithm then matches the selected author to a group of reviewers who may meet the author’s needs in regard to the selected assignment. Methodology: This study used the Multiple Criteria Decision-Making methodology (MCDM) to determine a set of reviewers from among the many available options. The weighted sum method was used because the data that have been collected in user profiles are expressed in the same unit. This study produced an experimental result, examining the algorithm with a real collected dataset and mock-up dataset. In total, there were 240 students in the real dataset, and it contained self-assessment scores, peer scores, and instructor scores for the same assignment. The mock-up dataset created 1000 records for self-assessment scores. The algorithm was evaluated using focus group discussions with 29 programming students and interviews with seven programming instructors. Contribution: This paper contributes to the field in the following two ways. First, an algorithm using a MCDM methodology was proposed to match authors and reviewers in order to facilitate the peer assessment process. In addition, the algorithm used self-assessment as an initial data source to match users, rather than randomly creating reviewer – author pairs. Findings: The findings show the accurate results of the algorithm in matching three reviewers for each author. Furthermore, the algorithm was evaluated based on students’ and instructors’ perspectives. The results are very promising, as they depict a high level of satisfaction for the Balanced Allocation algorithm. Recommendations for Practitioners: We recommend instructors to consider using the Balanced Allocation algorithm to match students in peer assessments, and consequently to benefit from personalizing peer assessment based on students' needs. Recommendation for Researchers: Several MCDM methods could be expanded upon, such as the analytic hierarchy process (AHP) if different attributes are collected, or the artificial neural network (ANN) if fuzzy data is available in the user profile. Each method is suitable for special cases depending on the data available for decision-making. Impact on Society: Suitable pairing in peer assessment would increase the credibility of the peer assessment process and encourage students’ engagement in peer assessments. Future Research: The Balanced Allocation algorithm could be applied using a single group, and a peer assessment with random matching with another group may also be conducted, followed by performing a t-test to determine the impact of matching on students’ performances in the peer assessment activity.

Aim/Purpose: The teaching of appropriate problem-solving techniques to novice learners in undergraduate software development education is often poorly defined when compared to the delivery of programming techniques. Given the global need for qualified designers of information technology, the purpose of this research is to produce a foundational template for an educational software development methodology grounded in the established literature. This template can be used by third-level educators and researchers to develop robust educational methodologies to cultivate structured problem solving and software development habits in their students while systematically teaching the intricacies of software creation. Background: While software development methodologies are a standard approach to structured and traceable problem solving in commercial software development, educational methodologies for inexperienced learners remain a neglected area of research due to their assumption of prior programming knowledge. This research aims to address this deficit by conducting an integrative review to produce a template for such a methodology. Methodology: An integrative review was conducted on the key components of Teaching Software Development Education, Problem Solving, Threshold Concepts, and Computational Thinking. Systematic reviews were conducted on Computational Thinking and Software Development Education by employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) process. Narrative reviews were conducted on Problem Solving and Threshold Concepts. Contribution: This research provides a comprehensive analysis of problem solving, software development education, computational thinking, and threshold concepts in computing in the context of undergraduate software development education. It also synthesizes review findings from these four areas and combines them to form a research-based foundational template methodology for use by educators and researchers interested in software development undergraduate education. Findings: This review identifies seven skills and four concepts required by novice learners. The skills include the ability to perform abstraction, data representation, decomposition, evaluation, mental modeling, pattern recognition, and writing algorithms. The concepts include state and sequential flow, non-sequential flow control, modularity, and object interaction. The teaching of these skills and concepts is combined into a spiral learning framework and is joined by four development stages to guide software problem solving: understanding the problem, breaking into tasks, designing, coding, testing, and integrating, and final evaluation and reflection. This produces the principal finding, which is a research-based foundational template for educational software development methodologies. Recommendations for Practitioners: Focusing introductory undergraduate computing courses on a programming syllabus without giving adequate support to problem solving may hinder students in their attainment of development skills. Therefore, providing a structured methodology is necessary as it equips students with essential problem-solving skills and ensures they develop good development practices from the start, which is crucial to ensuring undergraduate success in their studies and beyond. Recommendation for Researchers: The creation of educational software development methodologies with tool support is an under-researched area in undergraduate education. The template produced by this research can serve as a foundational conceptual model for researchers to create concrete tools to better support computing undergraduates. Impact on Society: Improving the educational value and experience of software development undergraduates is crucial for society once they graduate. They drive innovation and economic growth by creating new technologies, improving efficiency in various industries, and solving complex problems. Future Research: Future research should concentrate on using the template produced by this research to create a concrete educational methodology adapted to suit a specific programming paradigm, with an associated learning tool that can be used with first-year computing undergraduates.

Aim/Purpose: This review’s main objective was to examine the existing literature on the use of 3D printers in primary education, covering students aged six to twelve across general, special, and inclusive educational environments. Background: A review of the literature indicated a significant oversight – prior reviews insufficiently distinguish the application of 3D printing in primary education from its utilization at higher educational tiers or focused on particular subject areas and learning domains. Considering the distinct nature and critical role of primary education in developing young students’ cognitive abilities and skills, it is essential to concentrate on this specific educational stage. Methodology: The scoping review was selected as the preferred research method. The methodological robustness was augmented through the utilization of the backward snowballing technique. Consequently, a total of 50 papers were identified and subjected to thorough analysis. Contribution: This review has methodically compiled and analyzed the literature on 3D printing use among elementary students, offering a substantial addition to academic conversations. It consolidated and organized research on 3D printers’ educational uses, applying robust and credible criteria. Findings: Many studies featured small sample sizes and limited research on inclusive and special education. The analysis revealed 82 distinct research goals and 13 educational fields, with STEM being the predominant focus. Scholars showed considerable interest in how 3D printers influence skills like creativity and problem-solving, as well as emotions such as engagement and motivation. The majority of studies indicated positive outcomes, enhancing academic achievement, engagement, collaboration, creativity, interest, and motivation. Nonetheless, challenges were noted, highlighting the necessity for teacher training, the expense of equipment, technical difficulties, and the complexities of blending new methods with traditional curricula. Recommendations for Practitioners: To capitalize on the benefits that 3D printers bring, curriculum planners are urged to weave them into their programs, ensuring alignment with educational standards and skill development. The critical role educators play in the effective implementation of this technology necessitates targeted professional development programs to equip them with the expertise for successful integration. Moreover, 3D printing presents a unique opportunity to advance inclusive education for students with disabilities, offering tailored learning experiences and aiding in creating assistive technologies. In recognizing the disparities in access to 3D printing, educational leaders must address the financial and logistical barriers highlighted in the literature. Strategic initiatives are essential to democratize 3D printing access, ensuring all students benefit from this educational tool. Recommendation for Researchers: Comparative studies are critical to elucidate the specific advantages and limitations of 3D printing technology due to the scarcity of research contrasting it with other tools. The variability in reporting durations of interventions and research environments underscores the necessity for uniform methodologies and benchmarks. Because research has predominantly focused on STEM/STEAM education, expanding into different educational areas could provide a comprehensive understanding of 3D printing’s capabilities. The existence of neutral and negative findings signals an opportunity for further investigation. Exploring the factors that impede the successful integration of 3D printing will inform the creation of superior pedagogical approaches and technological refinements. Future Research: As the review confirmed the significant promise of 3D printing technology in enriching education, especially in the context of primary education, the imperative for continued research to refine its application in primary education settings is highlighted.

Corporate social responsibility (CSR) and sustainability are gaining worldwide recognition. The question of whether CSR and sustainability programs benefit an organisation's financial success is still being debated. This study aims to verify this phenomenon by examining the current literature pattern on this relationship using bibliometric and systematic review analysis. It further provides a taxonomy for understanding this association. VOSviewer is used to obtain comprehensive dataset mapping and clustering in the field. The manuscript offers promising insights regarding academia by assessing the pattern of publication trends, the most influential author in the area, and analysing the methodological and theoretical underpinnings of CSR, sustainability and firm performance linkage. The outcome of this study provides exploratory insights into research gaps and avenues for future research.

This paper presents a review of the literature on the challenges of national information and communication technology (ICT) policies in the context of African countries. National ICT policies have been aligned with socio-development agendas of African countries. However, the policies have not delivered the expected outcomes due to many challenges. Studies have been conducted in isolation to highlight the challenges in the policy process. The study used grounded theory informed literature review to holistically analyse the problems in the context of African countries. The results were categorised in the typology of the policy process to understand the challenges from a broad perspective. The problems were categorised into agenda setting, policy formulation, legal frameworks, implementation and evaluation. In addition, there were constraints related to policy monitoring in the policy phases and imbalance of power among the policy stakeholders. The review suggests areas of further research.

The study aims to review the literature on mobile wallet payment and align research trends using a systematic literature review with bibliometric and network visualisation analysis over two decades. It uses bibliometric analysis of the literature research retrieved from the Web of Science database. The study period was from 2001 to 2021, with 1,134 research papers. It also provides the indicators like citation trends, cited reference patterns, authorship patterns, subject areas published on the mobile wallet, top contributing authors, and highly cited research articles using the database. Furthermore, network visualisation analysis, like the co-occurrence of author keywords and keywords plus terms, has also been examined using VOSviewer software. The bibliometric analysis shows that the Republic of China dominates mobile wallet payment, and India is a significant contributor. Furthermore, the constructions of the network map using a co-citation analysis and bibliographic coupling shows an interesting pattern of mobile wallet payment.

The surge of learner enrolment in massive open online courses (MOOCs) has led to a wealth of learner-generated data, such as online course reviews that document learner experience. To unveil learner experience with MOOCs, this research uses machine learning methods to extract prominent topics from MOOC reviews and assess the sentiments expressed by learners within them. Furthermore, this research investigates the cooccurrence of the topics using association rule mining. The findings reveal six central topics discussed in MOOC reviews, such as "instructor", "design", "material", "assignment", "platform", and "experience". Notably, most learners express positive sentiments in their reviews. The sentiment indicated in reviews of skill-seeking MOOCs is higher than that in reviews of knowledge-seeking MOOCs. Furthermore, the association rule mining identifies four meaningful association rules. The findings offer valuable insights for MOOC instructors to enhance course design and for platform operators to ensure the long-term viability and success of MOOC platforms.

Aim/Purpose: Authentic assessments offer students the opportunity to develop skills that implement the formal learning they receive in the classroom. Although there is a need for accounting graduates to possess a plethora of skills to equip them for success, there is a shortage of literature that focuses on authentic assessment design for accounting courses. This paper aims to address this gap by compiling a toolkit for accounting educators aspiring to design and implement authentic assessments. Background: This paper reviews examples of authentic assessments that are available and have been used by accounting educators and educators in general. It highlights the skills that might be developed with each assessment Methodology: A review of 182 articles on authentic assessment design and examples of authentic assessments like portfolios, reflective journals, presentations, reports, peer and self-assessment was conducted. Contribution: A toolkit with examples of authentic assessment to ease the task of authentic assessment design for those new to authentic assessment and seasoned authentic assessment practitioners alike. Findings: Authentic assessments are a form of learning. They help graduates develop skills and attributes that will make them work-ready and capable of handling a lot of real life practical work situations. Rubrics are an important part of authentic assessment implementation and their use is mandated by business school accrediting bodies like AACSB. Recommendations for Practitioners: Accounting educators may find guidelines in this paper which will help them understand authentic assessments and enlighten them on the challenges they may encounter when implementing the assessments. Recommendation for Researchers: There is a need for future researchers to contribute more to this topic so as to increase the variety and amount of literature available for those wishing to engage with authentic curriculum design in accounting. Future researchers could also focus on the perceptions of authentic assessments of accounting educators, students and employers. Impact on Society: This paper may also be of use to prospective employers wishing to gain a clear understanding of the skills inherent in prospective graduates who may have been exposed to authentic assessments. Accounting students and graduates may find this paper useful as it will help them comprehend the importance of some the assessments with the backing and assurance from the literature. Future Research: Future research may focus on the challenges in implementing authentic assessments. It would also be great to see more research addressing the perceptions of educators towards authentic assessments.

Aim/Purpose. The goal of this publication is to explore methods for advancing student success in technology related disciplines via improved program classification and selection within higher education. Background. Increased demand for information technology (IT) professionals has been cited as a challenge in many fields including cybersecurity and software development. Many highlight the challenge as not just a numbers gap but a skills gap when comparing industry needs to the curricula in traditional disciplines within higher education. Closing the gap by increasing the number of skilled graduates remains a critical challenge we must address. Methodology. This publication leverages a systematic literature review to identify factors that classify existing higher education programs within the discipline of information technology. Contribution. Research in this area can act as a catalyst to increase relevance of IT related programs as well as graduation rates in technology and engineering. Findings. Authors analyzed forty-four primary studies and found that 56.8% of the publications referenced programs that meet the IT framework definition although they were not classified as IT programs. The findings and further analysis highlight direct challenges between program classification and the potential impact on student success. Recommendations for Practitioners. Research in this area is relevant for academic administrators, private sector executives and others working to increase the technology pipeline. Recommendations for Researchers. Researchers may benefit by exploring thematic analysis as a means of generating relevant classifications and taxonomies that highlight opportunities for improvement in a broad set of subject areas. Impact on Society. Research in this area can serve as a catalyst to increase graduation rates in programs related to technology and engineering. Future Research. This area would benefit from further research by comparing program success rates within varied disciplines. Future research may also produce a classification process.

Aim/Purpose. This paper aims to answer the research question, “What are the development phases of the academic discipline of information technology in the United States?” This is important to understand the reason for the growing talent gap in the information technology (IT) industry by reviewing the evolution of information technology across time, how the discipline was formed, evolved, and gained independence from other information and computing disciplines. Background. The COVID-19 pandemic has increased the shortage of IT professionals in the workplace. The root reason for this talent shortage requires understanding from both industry and academic perspectives in order to implement effective initiatives to prepare, recruit, and retain diverse IT professionals at an early stage. Methodology. This paper used a systematic literature review methodology and retrieved 143 primary studies from the ACM and IEEE Xplore digital libraries to review the development phases of the IT discipline as a contributing factor in understanding why, when, and how the population of professionals in IT and other relevant computing disciplines has changed and continues to fluctuate. Thematic analysis was applied to the abstracts of the primary studies, which spanned the period of 1982 to 2021. Contribution. This paper contributes to the understanding of the discipline of IT in the US and contributes foundations to researchers and educators who are working on strategies to fill the talent gap. Findings. Based on the thematic analysis in this paper, the academic discipline of IT has evolved over four phases across a timeline from 1982 to 2021. These phases were: Phase 1 (1982-1991) – Advent of Information Technology; Phase 2 (1992-2001) – Industry IT & DevOps; Phase 3 (2002-2011) – Information Technology and Management in Evolving Industry, Academia, and Research Areas; and Phase 4 (2011-2021) – Information Technology Research & Education. Recommendations for Practitioners. IT occupies an independent disciplinary space from computer science, computer engineering, and information systems. The paper suggests that practitioners seeking to fill the talent gap in IT invest in enabling its academic programs. Recommendations for Researchers. The depth of the IT disciplinary space and its continued evolution over time is ready for exploration. Continued research in this area may yield a better understanding of its role in society, the skills needed to succeed, and how to build programs to empower students with these skills. Impact on Society. Examining the discipline of IT and understanding its independence and interrelated connection with other computing disciplines will help address the shortfalls in academia across the nation by identifying the distinction between each discipline and creating comprehensive programs, degrees, and curricula suitable for various students and professionals across all educational levels. Future Research. Future research will integrate papers’ introductions and conclusions in addition to abstracts, increase the number of databases and reviewers, as well as incorporate papers that focus on other information and computing disciplines such as computer science and information systems to explore the possibility that IT as a discipline was initially practiced in an existing information or computing discipline before it gained independence.

Aim/Purpose. This study addresses the research question: “What are the developmental phases of Information Technology in the industry?” Existing research has explored the impact of Information Technology (IT) on specific industries. However, it is essential to understand the evolution of IT within industries, its influence on the workforce, and technological advancements. Addressing this knowledge gap will enhance future workforce development and IT integration across diverse sectors. Background. IT can significantly transform industries and drive innovation to meet client demands. Understanding IT phases in industry through literature helps governments and businesses worldwide recognize its importance. This knowledge can guide strategies to address the shortage of highly skilled workers by prioritizing education and training programs to meet future demands. Methodology The methodology involved a systematic literature review of 110 IEEE Xplore, ACM Digital Library, and Google Scholar articles. Thematic analysis was used to understand the development of IT in distinct phases since the 1990s. This development has resulted in a continuous demand for new workforce skills and evolving customer expectations. Contribution. This study aims to fill the knowledge gap by enhancing our understanding of how evolving IT influences the industry and shapes IT jobs and skills. It provides a historical perspective, illustrating how IT advancements have led to new applications to meet changing needs. Additionally, the study identifies patterns in the evolving IT skill requirements due to technological advancements and discusses implications for curriculum development and higher education. Findings. The study identified three significant phases through a systematic literature review and thematic analysis. The first phase, “Advent of Industry IT” (1990-2000), established the digital framework and built essential systems and infrastructure. The second phase, “Connectivity & Information Revolution” (2000-2010), saw exponential internet growth, transforming information access and communication. The third phase, “Emerging Industry IT” (2010-present), focuses on artificial intelligence, automation, and data-driven insights, continuing to disrupt and transform industries. Recommendations for Practitioners. The changing phases of IT within the industry should inform the development of innovative programs. These programs should address diverse skill sets across eras, preparing the workforce for evolving job roles in various sectors, such as healthcare in North America, automotive manufacturing in Japan, telecommunications in Africa, and innovations in other parts of the world. Recommendations for Researchers. Researchers can conduct longitudinal studies to explore the ongoing evolution of IT, tracking its trajectory beyond current delineated phases to understand future trends. Comparative studies across various industries can assess how IT evolution varies among sectors and delve deeper into its practical implications. Researchers can also conduct impact assessment studies to determine how various IT phases directly affect organizational strategy, worker dynamics, and organizational structures across industries. Examples include logistics in the Netherlands, retail in the United Kingdom, and agriculture in Brazil. Impact on Society. Policymakers and planners can use knowledge of these phases to predict technological shifts and industry trends. This knowledge helps develop strategies and policies supporting entrepreneurship, education and training alignment, technical innovation, economic growth, and job creation in line with the changing IT landscape. Examples of policies include Singapore’s Smart Nation initiative, Germany’s Industry 4.0 strategy, Ghana’s digitization efforts, and India’s Digital India campaign. Future Research. Future research can provide a thorough understanding of the evolutionary patterns of IT within sectors by validating the study through various datasets and conducting in-depth examinations of individual industries. This will contribute to a deeper understanding of sector-specific IT evolution and their varying impact on societal interactions and industry dynamics. Comparative studies across various sectors, such as logistics in the Netherlands, retail in the United Kingdom, and agriculture in Brazil, can assess how IT evolution varies.

Aim/Purpose: To investigate the impact of the evolution of Information Technology on global workforce skills and explore emerging approaches that address the IT talent shortage faced by diverse companies in finding skilled IT workers. Background: This paper explores diverse approaches to bridge the skilled IT workers shortage gap, especially in the context of the widening gap following the impact of the COVID-19 pandemic. The study emphasizes the need to consistently leverage business and information technology strategies for competitive advantage. Methodology: This study followed the systematic literature review methodology on 809 articles from ACM, IEEE Xplore, and Scopus digital libraries by utilizing an integrative mixed methods approach with topic modeling and manual content analysis. Contribution: This paper aims to understand and describe the impact of the evolution of the IT industry on its workforce. It contributes additional evidence to our understanding of IT workforce development to support researchers and educators working towards developing effective strategies to bridge the IT talent gap. Findings: On the one hand, the study finds that the evolution of the IT industry produces a shift in required skills and knowledge, resulting in workers needing to adapt and embrace lifelong learning. On the other hand, the evolution of IT creates new opportunities for workers and results in a more globalized and interconnected workforce. Recommendations for Practitioners: Practitioners are recommended to adapt to the shifting skills landscape, encourage lifelong learning, explore new opportunities for workers, and embrace a more globalized workforce. Recommendations for Researchers: Researchers are encouraged to further explore the identified themes and delve into the nuances of the evolving impact of information technology on workforce skills. Impact on Society: The findings have implications for industry growth, emphasizing the importance of aligning business and IT strategies to address the shortage of skilled IT workers on a global scale. Future Research: Future research should focus on the continuous evolution of information technology and its impact on workforce skills, considering the identified themes as a foundation for further exploration.

Aim/Purpose. The aim of this study is to recognize the factors that contributed to the development of IT in the healthcare industry. Background. The healthcare Information Technology (IT) solutions market has experienced remarkable growth, with the healthcare sector emerging as a $303 billion industry. However, despite its substantial size, the healthcare industry has faced criticism for its slow adoption of innovative technologies. This study aims to explore factors driving the evolution of IT in the healthcare sector. Methodology. The researchers conducted a systematic literature review, searching the PubMed and Emerald databases for relevant peer-reviewed articles. After filtering based on defined criteria, 433 articles were included for analysis. Thematic analysis was applied to the abstract of articles which spanned the period of 1997 to 2023. Contribution. This study provides a conceptual framework elucidating the key factors driving the evolution of IT in the healthcare industry. By systematically analyzing the existing literature, the research identifies four overarching themes – government policies, technological potentials, healthcare delivery needs, and organizational motivations – that have propelled the development and adoption of healthcare IT solutions. Provide a conceptual model for understanding, and design of the healthcare it solutions. Findings. Based on the analysis in this paper, four themes emerged: government policies promoting IT adoption through initiatives like incentives for electronic health records; technological breakthroughs enabling new healthcare IT capabilities; healthcare delivery needs to drive IT integration for improved quality and safety; and patient experience and organizational motivations to leverage IT for streamlining processes and knowledge management. Recommendations for Practitioners. The conceptual model can guide practitioners in developing IT solutions aligned with policy drivers, technological capabilities, care delivery needs, and organizational imperatives. Recommendations for Researchers. The conceptual framework developed in this study offers a lens for researchers across disciplines to continue investigating the role of information technology in the healthcare industry. Impact on Society. Examining the evolution of IT in the healthcare industry revealed the importance of information technology in enhancing the delivery and affordability of healthcare services and addressing issues of accessibility and inequality. Future Research. Future research will explore global perspectives showcasing the successful impact of IT on healthcare, as emerging technologies impact healthcare delivery and patient outcomes.

Purpose: Innovation capability is a growing and significant area of academic research. However, there is little attempt to provide a cumulative overview of this phenomenon. The purpose of this systematic review is to synthesize peer reviewed articles published in the area to develop a conceptual framework and to aid future research. Design/Methodology/Approach: The paper adopted a systematic review of literature on innovation capability. The final screening generated 51 articles from 30 journals from 2000-2015. Findings: The examination and synthesis of the theoretical and the empirical articles show that (1) the authors applied narrow range of conceptual and theoretical foundations; (2) innovation capability is being investigated mostly at the firm level for about 90% of the articles, and marginally about 5% at network (supply) chain level; (3) the authors define innovation capability in different ways and use diverse set of dimensions to measure innovation capability; (4) there is potential for future research across firms in innovation management disciplines. Practical implications: The review contributes to theory development in organizational capability literature in general. Managers wishing to innovate need to examine critically and integrate some of the innovation capability dimensions proposed in this paper. Originality: The review is unique in the sense that it provides conceptualisation of innovation capability framework.

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.

Background/Aim/Purpose: A commonly implemented software process improvement framework is the capability maturity model integrated (CMMI). Existing literature indicates higher levels of CMMI maturity could result in a loss of agility due to its organizational focus. To maintain agility, research has focussed attention on agile maturity models. The objective of this paper is to find the common research themes and conclusions in agile maturity model research. Methodology: This research adopts a systematic approach to agile maturity model research, using Google Scholar, Science Direct, and IEEE Xplore as sources. In total 531 articles were initially found matching the search criteria, which was filtered to 39 articles by applying specific exclusion criteria. Contribution:: The article highlights the trends in agile maturity model research, specifically bringing to light the lack of research providing validation of such models. Findings: Two major themes emerge, being the coexistence of agile and CMMI and the development of agile principle based maturity models. The research trend indicates an increase in agile maturity model articles, particularly in the latter half of the last decade, with concentrations of research coinciding with version updates of CMMI. While there is general consensus around higher CMMI maturity levels being incompatible with true agility, there is evidence of the two coexisting when agile is introduced into already highly matured environments. Future Research: Future research direction for this topic should include how to attain higher levels of CMMI maturity using only agile methods, how governance is addressed in agile environments, and whether existing agile maturity models relate to improved project success.

Aim/Purpose: This paper reports our implementation of a prototype system, namely PRATO (Proposals Reviewers Automated Taxonomy-based Organization), for automatic assignment of proposals to reviewers based on categorized tracks and partial matching of reviewers’ profiles of research interests against proposal keywords. Background: The process of assigning reviewers to proposals tends to be a complicated task as it involves inspecting the matching between a given proposal and a reviewer based on different criteria. The situation becomes worse if one tries to automate this process, especially if a reviewer partially matches the domain of the paper at hand. Hence, a new controlled approach is required to facilitate the matching process. Methodology: Proposals and reviewers are organized into categorized tracks as defined by a tree of hierarchical research domains which correspond to the university’s colleges and departments. In addition, reviewers create their profiles of research interests (keywords) at the time of registration. Initial assignment is based on the matching of categorized sub-tracks of proposal and reviewer. Where the proposal and a reviewer fall under different categories (sub-tracks), assignment is done based on partial matching of proposal content against re-viewers’ research interests. Jaccard similarity coefficient scores are calculated of proposal keywords and reviewers’ profiles of research interest, and the reviewer with highest score is chosen. The system was used to automate the process of proposal-reviewer assignment at the Umm Al-Qura University during the 2017-2018 funding cycle. The list of proposal-reviewer assignments generated by the system was sent to human experts for voting and subsequently to make final assignments accordingly. With expert votes and final decisions as evaluation criteria, data system-expert agreements (in terms of “accept” or “reject”) were collected and analyzed by tallying frequencies and calculating rejection/acceptance ratios to assess the system’s performance. Contribution: This work helped the Deanship of Scientific Research (DSR), a funding agency at Umm Al-Qura University, in managing the process of reviewing proposals submitted for funding. We believe the work can also benefit any organizations or conferences to automate the assignment of papers to the most appropriate reviewers. Findings: Our developed prototype, PRATO, showed a considerable impact on the entire process of reviewing proposals at DSR. It automated the assignment of proposals to reviewers and resulted in 56.7% correct assignments overall. This indicates that PRATO performed considerably well at this early stage of its development. Recommendations for Practitioners: It is important for funding agencies and publishers to automate reviewing process to obtain better reviewing quality in a timely manner. Recommendation for Researchers: This work highlighted a new methodology to tackle the proposal-reviewer assignment task in an automated manner. More evaluation might be needed with consideration of different categories, especially for partially matched candidates. Impact on Society: The new methodology and knowledge about factors influencing the implementation of automated proposal-reviewing systems will help funding agencies and publishers to improve the quality of their internal processes. Future Research: In the future, we plan to examine PRATO’s performance on different classification schemes where specialty areas can be represented in graphs rather than trees. With graph representation, the scope for reviewer selection can be widened to include more general fields of specialty. Moreover, we will try to record the reasons for rejection to identify accurately whether the rejection was due to improper assignment or other reasons.

Aim/Purpose: The aim of this paper is to analyze various text classification techniques employed in practice, their strengths and weaknesses, to provide an improved awareness regarding various knowledge extraction possibilities in the field of data mining. Background: Artificial Intelligence is reshaping text classification techniques to better acquire knowledge. However, in spite of the growth and spread of AI in all fields of research, its role with respect to text mining is not well understood yet. Methodology: For this study, various articles written between 2010 and 2017 on “text classification techniques in AI”, selected from leading journals of computer science, were analyzed. Each article was completely read. The research problems related to text classification techniques in the field of AI were identified and techniques were grouped according to the algorithms involved. These algorithms were divided based on the learning procedure used. Finally, the findings were plotted as a tree structure for visualizing the relationship between learning procedures and algorithms. Contribution: This paper identifies the strengths, limitations, and current research trends in text classification in an advanced field like AI. This knowledge is crucial for data scientists. They could utilize the findings of this study to devise customized data models. It also helps the industry to understand the operational efficiency of text mining techniques. It further contributes to reducing the cost of the projects and supports effective decision making. Findings: It has been found more important to study and understand the nature of data before proceeding into mining. The automation of text classification process is required, with the increasing amount of data and need for accuracy. Another interesting research opportunity lies in building intricate text data models with deep learning systems. It has the ability to execute complex Natural Language Processing (NLP) tasks with semantic requirements. Recommendations for Practitioners: Frame analysis, deception detection, narrative science where data expresses a story, healthcare applications to diagnose illnesses and conversation analysis are some of the recommendations suggested for practitioners. Recommendation for Researchers: Developing simpler algorithms in terms of coding and implementation, better approaches for knowledge distillation, multilingual text refining, domain knowledge integration, subjectivity detection, and contrastive viewpoint summarization are some of the areas that could be explored by researchers. Impact on Society: Text classification forms the base of data analytics and acts as the engine behind knowledge discovery. It supports state-of-the-art decision making, for example, predicting an event before it actually occurs, classifying a transaction as ‘Fraudulent’ etc. The results of this study could be used for developing applications dedicated to assisting decision making processes. These informed decisions will help to optimize resources and maximize benefits to the mankind. Future Research: In the future, better methods for parameter optimization will be identified by selecting better parameters that reflects effective knowledge discovery. The role of streaming data processing is still rarely explored when it comes to text classification.

Aim/Purpose: The aim of this study is to develop a research model derived from relevant literature to guide empirical efforts. Background: Companies struggle to innovate, which is essential for improving their performance, surviving in competition, and growing. A number of studies have discussed company innovation capability, stating that innovation capability is influenced by several variables such as cooperation and knowledge management. Therefore, further research is necessary to identify factors playing a role in enhancing innovation capability. Methodology: This study is based on systematic literature review. The stages are: (1) research scope review, (2) comprehensive online research, (3) journal quality assessment, (4) data extraction from journals, (5) journal synthesis, and (6) comprehensive report. The online research used Google Scholar database, by browsing titles, abstracts, and keywords to locate empirical research studies in peer-reviewed journals published in 2010-2020. Furthermore, 62 related articles were found, of which 38 articles were excluded from further analysis and 24 articles were selected because they were more related to the topic. Contribution: The results of this study enrich the research in the field of knowledge management, cooperation, and innovation capability by developing a conceptual framework of innovation capability. The proposed theoretical model may be fundamental in addressing the need of a research model to guide further empirical efforts. Findings: This study provides a research model derived from systematically reviewing relevant literature. The proposed theoretical model was done by incorporating the aspects of knowledge management, cooperation, and innovation capability. The model shows that knowledge management and cooperation are essential aspects of innovation capability. Furthermore, this study also provides the dimensions and sub dimensions of each variable that was established after synthesizing the literature review. Recommendations for Practitioners: Business practitioners can use the identified predictors of innovation capability and the dimensions of each variable to explore their company’s innovation capability. They can also take the relevant variables into consideration when making policies regarding innovation. Recommendation for Researchers: The theoretical model proposed in this study needs validation with further empirical investigation. Impact on Society: Readers of this paper can obtain an understanding that knowledge management and cooperation are essential aspects to consider in enhancing innovation capability. Future Research: Future studies should explore other dimensions of knowledge management and cooperation through alternative approaches and perspectives.

Aim/Purpose: The main goal of this systematic literature review was to look for studies that provide information relevant to business intelligence’s (BI) framework development and implementation in the tourism sector. This paper tries to classify the tourism sectors where BI is implemented, group various BI functionalities, and identify common problems encountered by previous research. Background: There has been an increased need for BI implementation to support decision-making in the tourism sector. Tourism stakeholders such as management of destination, accommodation, transportation, and public administration need a guideline to understand functional requirements before implementation. This paper addresses the problem by comprehensively reviewing the functionalities and issues that need to be considered based on previous business intelligence framework development and implementation in tourism sectors. Methodology: We have conducted a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Guidelines for Meta-Analysis (PRISMA) method. The search is conducted using online academic database platforms, resulting in 543 initial articles published from 2002 to 2022. Contribution: The paper could be of interest to relevant stakeholders in the tourism industry because it provides an overview of the capabilities and limitations of business intelligence for tourism. To our knowledge, this is the first study to identify and classify the BI functionalities needed for tourism sectors and implementation issues related to organizations, people, and technologies that need to be considered. Findings: BI functionalities identified in this study include basic functions such as data analysis, reports, dashboards, data visualization, performance metrics, and key performance indicator, and advanced functions such as predictive analytics, trend indicators, strategic planning tools, profitability analysis, benchmarking, budgeting, and forecasting. When implementing BI, the issues that need to be considered include organizational, people and process, and technological issues. Recommendations for Practitioners: As data is a major issue in BI implementation, tourism stakeholders, especially in developing countries, may need to build a tourism data center or centralized coordination regulated by the government. They can implement basic functions first before implementing more advanced features later. Recommendation for Researchers: We recommend further studying the BI implementation barriers by employing a perspective of an adoption framework such as the technology, organization, and environment (TOE) framework. Impact on Society: This research has a potential impact on improving the tourism industry’s performance by providing insight to stakeholders about what is needed to help them make more accurate decisions using business intelligence. Future Research: Future research may involve collaboration between practitioners and academics in developing various BI architectures specific to each tourism industry, such as destination management, hospitality, or transportation.

Aim/Purpose: Systematic literature reviews seek to locate all studies that contain material of relevance to a research question and to synthesize the relevant outcomes of those studies. The primary aim of this paper was to synthesize both research and practice reports on micro-credentials (MCRs). Background: There has been an increase in reports and research on the plausibility of MCRs to support dynamic human skills development for an increasingly impatient and rapidly changing digital world. The integration of fast-paced emerging technologies and digitalization necessitate alternative learning paradigms. MCRs offer time, financial, and space flexibility and can be stacked into a larger qualification, thereby allowing for a broader range of transdisciplinary competencies within a qualification. However, MCRs often lack the academic rigor required for accreditation within existing disciplines. Methodology: The study followed the PRISMA framework (Preferred Reporting Items for Systematic Reviews and Meta Analyses), which offers a rigorous method to enhance reporting quality. The study used both academic research and practice reports. Contribution: The paper makes a theoretical contribution to the discourse about the need for innovation within existing educational paradigms for continued relevance in a changing world. It also contributes to the debate on the role of MCRs in bridging the gap between practice and academia despite the growing difference between their interests, and the role that MCRs play in the social-economic plans of countries. Findings: The key findings are that investments in MCRs are mainly in the Science, Technology, Engineering and Mathematics (STEM) and Education sectors, and have taken place mainly in high-income countries and regions – contexts that particularly value practice-accredited MCRs. Low-income countries, by contrast, remain traditional and insist on MCRs that are formally accredited by a recognized academic institution. This contributes to a widening skills gap between low- and high-income countries or regions, which results in greater global disparities. There is also a growing divide between academia and practice concerning their interest in MCRs (a reflection of the rigor versus relevance debate), which partially explains why many global and larger organizations have gone on to create their own learning institutions. Recommendations for Practitioners: We recommend that educational mechanisms consider the critical importance of MCRs as part of innovative efforts for life-wide (different sectors) and life-long (same sector) learning, especially in low-income countries. MCRs provide dynamic mechanisms to fill skills gaps in an increasing ruthless international battle for talent. Recommendation for Researchers: We recommend focused research into skills and career pathways using MCRs while at the same time remaining responsive to transdisciplinary efforts and sensitive to global and local changes within any sector. Impact on Society: Work and society have transformed over time, and more so in the new digital age, yet academia has been slow in adapting to the changes, forcing organizations to create their own learning institutions or to use MCRs to fill the skills gap. The purpose of education goes beyond preparing individuals for work, extending further to creating an environment where individuals and governments seek their own social and economic outcomes. MCRs provide a flexible means for co-creation between individuals, education, organizations, and government that could stem global rising unemployment, social exclusion, and redundancy. Future Research: Future research should focus on the co-creation of MCRs between practitioners and academia.

Aim/Purpose: In this study, we aim to investigate the impact of an important characteristic of textual reviews – the diversity of the review content on review helpfulness. Background: Consumer-generated reviews are an essential format of online Word-of-Month that help customers reduce uncertainty and information asymmetry. However, not all reviews are equally helpful as reflected by the varying number of helpfulness votes received by reviews. From consumers’ perspective, what kind of content is more effective and useful for making purchase decisions is unclear. Methodology: We use a data set consisting of consumer reviews for laptop products on Amazon from 2014 to 2018. A topic modeling technique is implemented to unveil the hidden topics embedded in the reviews. Based on the extracted topics, we compute the text diversity score of each review. The diversity score measures how diverse the content in a review is compared to other reviews. Contribution: In the literature, studies have examined various factors that can influence review helpfulness. However, studies that emphasized the information value of textual reviews are limited. Our study contributes to the extant literature of online word-of-mouth by establishing the connection between the diversity of the review content and consumer perceived helpfulness. Findings: Empirical results show that text diversity plays an important role in consumers’ evaluation of whether the review is helpful. Reviews that contain more diverse content tend to be more helpful to consumers. Moreover, we find a negative interaction effect between text diversity and the text depth. This result suggests that text depth and text diversity have a substitution effect. When a review contains more in-depth content, the impact of text diversity is weakened. Recommendations for Practitioners: For consumers to quickly find the informative reviews, platforms should incorporate measures such as text diversity in the ranking algorithms to rank consumer reviews. Future Research: Future study can extend the current research by examine the impact of text diversity for experienced goods and compare the results with search goods.

Aim/Purpose: The purpose of this study is to identify the key determinants hindering Knowledge Transfer (KT) practices for Information Technology Project Managers (ITPMs) Background: The failure rate of IT projects remains unacceptably high worldwide, and KT between project managers and team members has been recognized as a significant issue affecting project success. Therefore, this study tries to identify the determinants of KT within the context of IT projects for ITPMs. Methodology: A systematic review of the literature (SLR) was employed in the investigation. The SLR found 28 primary studies on KT for ITPMs that were published in Scopus and Web of Science databases between 2010 and 2023. Contribution: Social Cognitive Theory (SCT) was used to build a theoretical framework where the determinants were categorized into Personal factors, Environmental (Project organizational) factors, and other factors, such as Technological factors influencing ITPMs (Behavioral factors), to implement in KT practices. Findings: The review identified 11 key determinants categorized into three broad categories: Personal factors (i.e., motivation, absorptive capability, trust, time urgency), Project Organizational factors (i.e., team structure, leadership style, reward system, organizational culture, communication), and Technological factors (i.e., project task collaboration tool and IT infrastructure and support) that influence implementing KT for ITPMs Recommendations for Practitioners: The proposed framework in this paper can be used by project managers as a guide to adopt KT practices within their project organization. Recommendation for Researchers: The review showed that some determinants, such as Technological factors, have not been adequately explored in the existing KT model in the IT projects context and can be integrated with other relevant theories to understand how a project manager’s knowledge can be transferred and retained in the organization using technology in future research. Impact on Society: This study emphasizes the role of individual actions and project organizational and technological matters in shaping the efficacy of KT within project organizations. It offers insight that could steer business owners or executives within project organizations to closely observe the behavior of project managers, thereby securing successful project outcomes. Future Research: The determinant list provided in this paper is acquired from extensive SLR and, therefore, further research should aim to expand and deepen the investigation by validating these determinants from experts in the field of IT and project management. Future studies can also add other external technological determinants to provide a more comprehensive KT implementation framework. Similarly, this research does not include determinants identified directly from the industry, as it relies solely on determinants found in the existing literature. Although a comprehensive attempt has been made to encompass all relevant papers, there remains a potential for overlooking some research in this process.