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With the outbreak of the COVID-19 pandemic, online assessment has become the dominant mode of examination in higher education institutions. However, there are contradictory findings on how students perceive online assessment and its impact on their academic performance. Thus, the purpose of this study is to evaluate the potential impact of online assessment on students' academic performance.

This study proposes a research model based on the task–technology fit theory and empirically validates the model using a survey from students in the UK. In addition, the study conducted four experiments based on paper-based and online assessments and analysed the data using paired sample t test and structural equation modelling.

The findings show that the use of online assessment has a positive impact on students' academic performance. Similarly, the results from the experiment also indicate that students perform better using online assessments than paper-based assessments.

The findings provide crucial evidence needed to shape policy towards institutionalising online assessment. In addition, the findings provide assurance to students, academics, administrators and policymakers that carefully designed online assessments can improve students' academic performance. Moreover, the study also provides important insights for curriculum redesign towards transitioning to online assessment in higher education institutions.

This study advances research by offering a more nuanced understanding of online assessment on students' academic performance since the majority of previous studies have offered contradictory findings. In addition, the study moves beyond existing research by complementing assessment results with the views of students in evaluating the impact of online assessment on their academic performance. Second, the study develops and validates a research model that explains how the fits between technology and assessment tasks influence students' academic performance. Lastly, the study provides evidence to support the wide use of online assessment in higher education.

The purpose of this paper is to present a practical data-based framework for the prioritization of investment in manufacturing technologies, methods and tools, and to demonstrate its applicability and practical relevance through two case studies of manufacturing firms of different industrial segments.

The proposed framework is based on network theory applied on technology adoption. For this, the database of Industry 4.0 maturity assessments of SENAI was used to develop data visualization tools named “Technology Networks”. Thus, this study is descriptive research with correlational design. Besides, the framework was applied in two companies and semi-structured interviews were carried out with domain experts.

The technology networks highlight the technological adoption patterns of six industrial segments, by considering the answers of 863 Brazilian companies. In general, less sophisticated technologies were positioned in the center of the networks, which facilitates the visualization of adoption paths. Moreover, the networks presented a well-balanced adoption scenario of Industry 4.0 related technologies and lean manufacturing methods and tools.

Since the database was not built under an experimental design, it is not expected to make statistical inferences about the variables. Furthermore, the decision to use an available database prevented the editing or inclusion of technologies. Besides, it is estimated that the technology networks given have few years for obsolescence due to the fast pace of technological development.

The framework is a tool that may be used by practicing manufacturing managers and entrepreneurs for taking assertive decisions regarding the adoption of manufacturing technologies, methods and tools. The proposition of using network theory to support decision making on this topic may lead to further studies, developments and adaptations of the framework.

This paper addresses the topics of lean manufacturing and Industry 4.0 in an unprecedented way, by quantifying the adoption of its technologies, methods and tools and presenting it in network visualizations. The main value of this paper is the comprehensive framework that applies the technology networks for supporting decision making regarding technology adoption.

This paper aims to propose an innovative method for deploying a personalized instructor-created software-aided assessment system, that will disrupt traditional learning environments by allowing students to confidentially and with indirect supervision from the instructor, assess their knowledge and ability to achieve the course outcomes.

Through empirical evaluation in real-world educational settings, the authors examine the impact of augmenting human activity in the classroom with an innovative software platform to transform the learning process.

Findings indicate that this software-aided assessment system effectively augments human interactivity by providing timely instructor-designed feedback to increase knowledge retention and skillsets.

This study has shown that incorporating disruptive innovation through the use of software-aided assessment systems increases the effectiveness of the faculty in the classroom and enhances student learning and retention. Thus, a transformative software-aided assessment system design that incorporates artificial intelligence into the learning pathway should be pursued. These software-aided assessments are disruptive innovation as they are formative, frequent and require little direct involvement from the instructor.

To the best of the authors’ knowledge, this study is the first of its kind to incorporate artificial intelligence into the assessment process by analyzing results of pilot programs at several universities. The results demonstrate how using software-aided transformative assessments in various courses have helped instructors assess students’ preparedness and track their learning progress. These software-aided systems are the first step in bringing disruptive innovation to the classroom as these software-aided assessment instruments rapidly assess learners’ knowledge and skills based on short, easily created, multiple-choice tests, with little direct engagement from the faculty.

To improve the academic integrity of online examinations, digital proctoring systems have recently been implemented in higher education institutions (HEIs). The paper aims to understand how digital proctoring has been practised in higher education (HE) and proposes future research directions for studying digital proctoring in HE.

A systematic literature review was conducted. The PRISMA procedure was adapted for the literature search. The topics were identified by topic modelling techniques from 154 relevant publications in seven databases.

Seven widely discussed topics in literature were identified, including solutions for detecting cheating and student authentication, challenges/issues of uptakes and students' performance in different proctoring environments.

This paper provides insights for academics, policymakers, practitioners and students to understand the implementation of digital proctoring in academia, its adoption by HEIs, impacts on students' and educators' performance and the rapid increase in its use for digital exams in HEIs, with particular emphasis on the impacts of the systems on digitalising examinations in HE.

This review paper has systematically and critically described the state-of-the-art literature on digital proctoring in HE and provides useful insights and implications for future research on digital proctoring, and how academic integrity in online examinations can be enhanced, along with digitalising HE.

This study aimed to identify research trends and topics in sustainability assessment in the food sector within the scope of economics, business and management research.

The authors conducted a bibliometric analysis by applying a rigid and systematic research protocol, employing bibliometric techniques and a keyword co-occurrence network. Further, the Visualization of Similarities viewer software was used to analyse publications between 1994 and 2021.

The knowledge trends regarding “sustainability assessment” in the research area of business economics demonstrated a notable evolution of the topics analysed, ranging from indicators and policy analyses in agriculture and fishery sectors, to the topic of sustainability life cycle assessment (LCA) and management systems. In business and management research areas, the main theoretical frameworks used for sustainability assessment in the food sector included the triple-bottom line (TBL) and the LCA, and the main research topics were food chain logistics, bio-based products, retailers, consumption patterns and crop-based biodiesel options.

This study employed only the WoS database and future studies could incorporate other scientific databases. Regarding future research, more emphasis could be laid on food retailers given their prevalence as demonstrated by the study and past research.

The findings can help all participants in the food global value chain to make better decisions to guide their sustainability efforts and assessment. Moreover, this research reveals that companies need to be actively engaged with their stakeholders and pay special attention to consumer patterns and perceptions.

The bibliometric research focus on business and management research areas using the Web of Sciences categories, starting from the research area of business economics to the analysis of the food sector's sustainability assessment.

Construction professionals are the major contributors to developing a sustainable construction industry, whereas architects, engineers and quantity surveyors are the key construction professionals who must play extraordinary roles in achieving better sustainable construction. Therefore, this study aims to identify the job attributes of key Sri Lankan construction professionals in addressing challenges associated with climate change.

The study adopted a mixed research approach. A literature review and preliminary semi-structured interviews were used to appraise the job roles of architects, engineers and quantity surveyors in addressing challenges associated with climate change. The data collected through the qualitative approach were used in an online questionnaire survey, and the findings were analysed using the relative index method.

The findings highlight that regardless of the knowledge of the professional category on green rating tools, carbon footprint, adaptation of renewable energies for the reduction of energy consumption, building information modelling-related applications and waste management concepts/practices are the foremost job attributes required for the key Sri Lankan construction professionals in addressing challenges associated with climate change.

The results from this study provide a handful of guidance to construction industry professionals, national and international professional institutions, non-governmental organisations and other relevant authorities to address climate change within the built environment by identifying ways for improving the relevant key job attributes of construction industry professionals.

To the best of the authors’ knowledge, this is the first study that explores the job attributes of key Sri Lankan construction professionals in addressing the challenges associated with climate change.

Modern technologies are seen as an essential component of the fourth industrial revolution (industry 4.0) and their adoption is vital to transform the existing manufacturing system into industry 4.0-based manufacturing system. Therefore, the primary objective of this research explores the barriers of modern technology adoption and their mitigating solutions in order to align with Industry 4.0 objectives.

Barriers to adopting modern technologies and respective mitigating solutions are identified from the available literature. Further, these barriers are ranked with the help of expert opinions by using the BWM method appropriately. The identified solutions are ranked using the combined compromise solution (CoCoSo) method.

Several modern technologies and their capabilities are recognised to support the industry 4.0-based manufacturing systems. This study identifies 22 barriers to the effective adoption of modern technologies in manufacturing and 14 solutions to overcome these barriers. Change management, the high initial cost of technology and appropriate support infrastructure are the most significant barriers. The most prominent solutions to overcome the most considerable barriers are ‘supportive research, development and commercialisation environment’, ‘updated policy and effective implementation’ and ‘capacity building through training’ that are the top three solutions that need to be addressed.

The barriers and solutions of modern technology adoption are obtained through a comprehensive literature review, so there is a chance to ignore some significant barriers and their solutions. Furthermore, ranking barriers and solutions is done with expert opinion, which is not free from biases.

This identification and prioritisation of barriers will help managers to understand the barriers so they can better prepare themselves. Furthermore, the suggested solutions to overcome these barriers are helpful for the managers and could be strategically adopted through optimal resource utilisation.

This study proposes a framework to identify and analyse the significant barriers and solutions to adopting modern technologies in the manufacturing system. It might be helpful for manufacturing organisations that are willing to transform their manufacturing system into industry 4.0.

This paper aims to investigate the intersection between crowdfunding (CF), open innovation (OI) and responsible innovation (RI) and identify the emerging trends and gaps in research and new paths for CF research in the future. In addition, this paper proposes a conceptual framework and propositions.

This paper is structured in line with the systematic literature review protocol. After reading all the titles, keywords and abstracts, 172 papers focused on OI and RI were selected for this research. Finally, 27 papers that are based on dimensions related to responsible OI were selected for the study.

Due to CF's multidisciplinary nature, the scientific literature on the role of CF in endorsing responsible OI for shared value co-creation appears fragmented and redundant. Several emerging trends and gaps of research and new paths for CF research in the future arise regarding research methodology and theoretical perspective.

To the best of the authors' knowledge, this is the first study investigating the intersection between CF OI and RI.

The objectives of this study are twofold: identify the main challenges in performing training on Industry 4.0 concepts to managers operating in the manufacturing sector who are not familiar with them but aspire for an Industry 4.0 broad view and validate training practices that can be adopted to reduce managerial knowledge differences.

A Delphi method was carried out in two rounds to identify the Industry 4.0 training challenges and a Fuzzy Delphi method was applied in one round to validate the training practices. Both methods used the same set of participants composed of experts in training for Industry 4.0. Results were discussed considering literature statements.

In total, 11 challenges in Industry 4.0 training were identified and grouped into: challenges associated with the necessary knowledge, challenges of breaking paradigm, challenges associated with training characteristics and challenges associated with expected results. In total, 11 training practices were directly validated, including actions to be adopted before, during, and after the training process.

The findings are relevant for professionals, academics, or consultants as the findings enable better training planning and execution. No similar papers were found in scientific databases, reinforcing this present study's originality and contribution.

Wireless sensor networks (WSN), as a solution for buried water pipe monitoring, face a new set of challenges compared to traditional application for above-ground infrastructure monitoring. One of the main challenges for underground WSN deployment is the limited range (less than 3 m) at which reliable wireless underground communication can be achieved using radio signal propagation through the soil. To overcome this challenge, the purpose of this paper is to investigate a new approach for wireless underground communication using acoustic signal propagation along a buried water pipe.

An acoustic communication system was developed based on the requirements of low cost (tens of pounds at most), low power supply capacity (in the order of 1 W-h) and miniature (centimetre scale) size for a wireless communication node. The developed system was further tested along a buried steel pipe in poorly graded SAND and a buried medium density polyethylene (MDPE) pipe in well graded SAND.

With predicted acoustic attenuation of 1.3 dB/m and 2.1 dB/m along the buried steel and MDPE pipes, respectively, reliable acoustic communication is possible up to 17 m for the buried steel pipe and 11 m for the buried MDPE pipe.

Although an important first step, more research is needed to validate the acoustic communication system along a wider water distribution pipe network.

This paper shows the possibility of achieving reliable wireless underground communication along a buried water pipe (especially non-metallic material ones) using low-frequency acoustic propagation along the pipe wall.