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1 – 10 of 235Vanessa Honson, Thuy Vu, Tich Phuoc Tran and Walter Tejada Estay
Large class sizes are becoming the norm in higher education against concerns of dropping learning qualities. To maintain the standard of learning and add value, one of the common…
Abstract
Purpose
Large class sizes are becoming the norm in higher education against concerns of dropping learning qualities. To maintain the standard of learning and add value, one of the common strategies is for the course convenor to proactively monitor student engagement with learning activities against their assessment outcomes and intervene timely. Learning analytics has been increasingly adopted to provide these insights into student engagement and their performance. This case study explores how learning analytics can be used to meet the convenor’s requirements and help reduce administrative workload in a large health science class at the University of New South Wales.
Design/methodology/approach
This case-based study adopts an “action learning research approach” in assessing ways of using learning analytics for reducing workload in the educator’s own context and critically reflecting on experiences for improvements. This approach emphasises reflexive methodology, where the educator constantly assesses the context, implements an intervention and reflects on the process for in-time adjustments, improvements and future development.
Findings
The results highlighted ease for the teacher towards the early “flagging” of students who may not be active within the learning management system or who have performed poorly on assessment tasks. Coupled with the ability to send emails to the “flagged” students, this has led to a more personal approach while reducing the number of steps normally required. An unanticipated outcome was the potential for additional time saving through improving the scaffolding mechanisms if the learning analytics were customisable for individual courses.
Originality/value
The results provide further benefits for learning analytics to assist the educator in a growing blended learning environment. They also reveal the potential for learning analytics to be an effective adjunct towards promoting personal learning design.
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Fauziah Eddyono, Dudung Darusman, Ujang Sumarwan and Fauziah Sunarminto
This study aims to find a dynamic model in an effort to optimize tourism performance in ecotourism destinations. The model structure is built based on competitive performance in…
Abstract
Purpose
This study aims to find a dynamic model in an effort to optimize tourism performance in ecotourism destinations. The model structure is built based on competitive performance in geographic areas and the application of ecotourism elements that are integrated with big data innovation through artificial intelligence technology.
Design/methodology/approach
Data analysis is performed through dynamic system modeling. Simulations are carried out in three models: First, existing simulation models. Second, Scenario 1 is carried out by utilizing a causal loop through innovation of big data-based artificial intelligence technology to ecotourism elements. Third, Scenario 2 is carried out by utilizing a causal loop through big data-based artificial intelligence technology on aspects of ecotourism elements and destination competitiveness.
Findings
This study provides empirical insight into the competitiveness performance of destinations and the performance of implementing ecotourism elements if integrated with big data innovations that will be able to massively demonstrate the growth of sustainable tourism performance.
Research limitations/implications
This study does not use a primary database, but uses secondary data from official sources that can be accessed by the public.
Practical implications
The paper includes implications for the development of intelligent technology based on big data and also requires policy innovation.
Social implications
Sustainable tourism development.
Originality/value
This study finds the expansion of new theory competitiveness of ecotourism destinations.
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Verònica Riera, Marta Moragas-Rovira and Xavier Pujadas
The purpose of this paper is to analyze if the sport trajectory could be an impact factor in leadership development.
Abstract
Purpose
The purpose of this paper is to analyze if the sport trajectory could be an impact factor in leadership development.
Design/methodology/approach
A qualitative research method has been adopted by conducting 17 in-depth, semi-structured interviews. The data were analyzed with the program Open Code (4.03).
Findings
The findings of this study revealed that the interviewed managers perceived that their sport trajectory has had an important influence in the development of their leadership. This influence is determined by four factors: (1) sport profile, (2) sport referents, (3) competences, values and abilities and (4) experiences from different sport roles played during their lifespan.
Research limitations/implications
The research is based on interviews with a small sample of managers. In order to develop the research further, a more extensive sample is required.
Originality/value
The paper is unique as it examines the impact of the sport trajectory as an impact factor in leadership development.
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Ummi Ibrahim Atah, Mustafa Omar Mohammed, Abideen Adewale Adeyemi and Engku Rabiah Adawiah
The purpose of this paper is to propose a model that will demonstrate how the integration of Salam (exclusive agricultural commodity trade) with Takaful (micro-Takaful – a…
Abstract
Purpose
The purpose of this paper is to propose a model that will demonstrate how the integration of Salam (exclusive agricultural commodity trade) with Takaful (micro-Takaful – a subdivision of Islamic insurance) and value chain can address major challenges facing the agricultural sector in Kano State, Nigeria.
Design/methodology/approach
The study conducted a thorough and critical analysis of relevant literature and existing models of financing agriculture in Nigeria to come up with the proposed model.
Findings
The findings indicate that measures undertaken to address the major challenges fail. In view of this, this study proposed Bay-Salam with Takaful and value chain model to solve a number of challenges such as poor access to financing, poor marketing and pricing, delay, collateral requirement and risk issues in order to avail farmers with easy access to finance and provide effective security to financial institutions.
Research limitations/implications
The paper is limited to using secondary data. Therefore, empirical investigation can be carried out to strengthen the validation of the model.
Practical implications
The study outcome seeks to improve the productivity of the farmers through enhancing their access to finance. This will increase their level of production and provide more employment opportunities. In addition, it will boost financial inclusion, income generation, poverty alleviation, standard of living, food security and overall economic growth and development.
Originality/value
The novelty of this study lies in the integration of classical Bay-Salam with Takaful and value chain and create a unique model structure which the researchers do not come across in any research that presented it in Nigeria.
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Santosh Kumar Shrivastav and Surajit Bag
The purpose of this study is to examine various data sources to identify trends and themes in humanitarian supply chain management (HSCM) in the digital age.
Abstract
Purpose
The purpose of this study is to examine various data sources to identify trends and themes in humanitarian supply chain management (HSCM) in the digital age.
Design/methodology/approach
In this study, various data sources such as published literature and social media content from Twitter, LinkedIn, blogs and forums are used to identify trending topics and themes on HSCM using topic modelling.
Findings
The study examined 33 published literature and more than 94,000 documents, including tweets and expert opinions, and identified eight themes related to HSCM in the digital age namely “Digital technology enabled global partnerships”, “Digital tech enabled sustainability”, “Digital tech enabled risk reduction for climate changes and uncertainties”, “Digital tech enabled preparedness, response and resilience”, “Digital tech enabled health system enhancement”, “Digital tech enabled food system enhancement”, “Digital tech enabled ethical process and systems” and “Digital tech enabled humanitarian logistics”. The study also proposed a framework of drivers, processes and impacts for each theme and directions for future research.
Originality/value
Previous research has predominantly relied on published literature to identify emerging themes and trends on a particular topic. This study is unique because it examines the ability of social media sources such as blogs, websites, forums and published literature to reveal evolving patterns and trends in HSCM in the digital age.
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Patrícia Becsky-Nagy and Balázs Fazekas
Venture capital (VC) is an essential element in healthy entrepreneurial environments; therefore, many countries in developing entrepreneurial economies support the industry via…
Abstract
Purpose
Venture capital (VC) is an essential element in healthy entrepreneurial environments; therefore, many countries in developing entrepreneurial economies support the industry via direct or indirect government interventions. The purpose of this study is to examine through the example of the Hungarian market, whether direct or hybrid state involvement has contributed more to the growth of the invested enterprises. The findings are relevant in the design of government VC schemes and in the contracts mitigating the moral hazards inherent in government funding.
Design/methodology/approach
The basis of empirical research is a unique hand-collected database covering Hungarian government-backed VC (GVC) investments. Based on the financial data of investee firms, the authors investigate whether firms financed by hybrid VC involving market participants are able to outperform firms that receive pure public financing using panel regression.
Findings
Based on Hungarian evidence, hybrid VC-backed firms generated lower growth and employment than their purely government-backed peers. Both schemes showed meagre innovation activity. The conclusion is that because of the conflict of private and economic policy objectives in hybrid financing, the exposure of hybrid risk capital to moral hazard is higher than that of pure public financing. Private interests in hybrid funds can only improve investment efficiency if they are structured along the lines of market-based independent financial intermediation and the contracts imitate the ones existing amongst limited and general partners in private schemes.
Research limitations/implications
The research covers the data of Hungarian government-backed firms by tracking the full range of 86 investments made in the purely government scheme and 340 firms that received funding in the hybrid scheme. The research focuses on two government initiatives, and the results are influenced by the specific regulation of the programs; therefore, the results cannot be generalized for all government agendas; they are indicative in the designs of the agendas.
Originality/value
There is a limited number of empirical studies investigating the impact of VC in developing markets, especially in the Central and Eastern Europe region. This firm-level research on the impact of public VC can help improve the effectiveness of development policies. By analysing the entirety of investments of a VC program that is near to its completion, the authors provide new insight into the efficiency and prospects of GVC schemes in the region.
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Magda Mostafa, Marlene Sotelo, Toby Honsberger, Christine Honsberger, Erin Brooker Lozott and Nate Shanok
The objective of this paper is to study the efficacy of the ASPECTSS Design Index's concepts as drivers of design intervention for educational environments for students on the…
Abstract
Purpose
The objective of this paper is to study the efficacy of the ASPECTSS Design Index's concepts as drivers of design intervention for educational environments for students on the autism spectrum. Based on the seven principles of acoustics, spatial sequencing, escape spaces, compartmentalization, transitions, sensory zoning and safety, ASPECTSS formed the basis for a preliminary post-occupancy evaluation (POE) and survey of an existing school environment.
Design/methodology/approach
Concepts drawn from the review of other strategies for autism spectrum disorder (ASD) friendly design were integrated with the seven ASPECTSS principles to create a design framework and consequent design retro-fit for a Pre-K-12th grade public school for students on the autism spectrum. The following design interventions were proposed: colour-coding based navigation; acoustical treatments in key circulation spaces; introduction of transition alcoves; classroom reorganisation using compartmentalization principles and the introduction of escape spaces for de-escalation. Specifically, a classroom template of modules of ASPECTSS-compliant layouts was provided to all staff. The efficacy and impact of these interventions were assessed using a whole campus online staff survey with further probing using classroom observations and subsequent interviews.
Findings
The results show alignment between the implementation of the ASPECTSS informed design interventions and responses to nine of the Likert scale items were all significantly lower than the middle response, indicating a high degree of satisfaction from survey respondents. These questions and responses related to the colour scheme facilitating ease of navigation for visitors of the school, the acoustics of the building successfully mitigating sound magnification and subsequently student distractibility, the organisation of the classrooms enhancing learning and the de-escalation zones allowing improved management of disruptive behaviours in the classroom.
Research limitations/implications
This study focuses primarily on the Autism ASPECTSS Design Index as a framework for assessing classroom efficacy. Other tools and frameworks may produce different insights. A single school site was studied. Validation of these findings in other school environments is necessary before generalising these strategies at scale. The use of qualitative tools, primarily teacher and staff surveys, provides one lens into the efficacy of these design strategies. Further research using measurable biometric indicators such as heart-rate and stress levels measured through wearable technology could provide a first step towards the triangulation of these findings.
Practical implications
These findings could help provide more standardised best practices for designing learning environments for autism, potentially providing supportive strategies with real impact on learning quality, skill development and knowledge acquisition in school environments. This could potentially have economic implications by supporting more efficient progress for autistic students through their school curriculum.
Social implications
Similar to economic impact, if validated and generalised, these findings could help with sense of accomplishment, general mental health improvement, alleviation of family stress and potential reduction of stigma in the autism community.
Originality/value
There is a slowly emerging field of design guidance for autism schools, but very little empirical evidence on the measurable efficacy of these strategies. This research provides one type of such evidence, as measured by the perceived impact from the point of view of staff and teachers at the school.
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Shivangi Viral Thakker, Santosh B. Rane and Vaibhav S. Narwane
Digital supply chains require nascent technologies like blockchain and Internet of Things (IoT). There is a need to develop a roadmap for the implementation of these technologies…
Abstract
Purpose
Digital supply chains require nascent technologies like blockchain and Internet of Things (IoT). There is a need to develop a roadmap for the implementation of these technologies, as they require a huge amount of resources and infrastructure. The purpose of this paper is to analyze the challenges of implementing blockchain-IoT integrated architecture in the green supply chain and develop strategies for the same.
Design/methodology/approach
After a thorough literature survey of Scopus-indexed journals and books, 37 barriers were identified, which were then brought down to 15 barriers after confirming with industry and academic experts using the Delphi method. Using the total interpretive structural modeling (TISM) method and cross-impact matrix multiplication applied to classification (MICMAC) analysis, the barriers were modeled, and finally, strategies were formulated using a concept map to handle the barriers in the blockchain-IoT integrated architecture for a green supply chain.
Findings
This paper presents the research on barriers that can be considered for incorporating blockchain and IoT in the green supply chain. It was found from the TISM model that environmental concerns are Level-1 barriers and need to be addressed by developing appropriate technology and allocating funds for the same. An integrated ecosystem with blockchain and IoT is developed.
Research limitations/implications
The focus of this study was on the challenges of blockchain and IoT; hence, it is required to extend the research and find challenges for different industries and also analyze the criteria using other multi-criteria decision-making (MCDM) methods. Further research is required for the integration of blockchain-IoT with supply chain functions.
Practical implications
The transformation of a traditional supply chain into a green supply chain is possible with the integration of technologies. This research work and the strategies developed are useful to managers and practitioners working on technology implementation. Planning resources and addressing key barriers is possible with the concept maps and architecture developed.
Social implications
Green supply chain management (SCM) is gaining importance in industry as well as the academic sector due to government Policies and norms worldwide for reducing emissions and encouraging environment-friendly production systems. Incorporating blockchain and IoT in a green supply chain will further digitize and increase transparency in supply chains.
Originality/value
We have done a categorization of all barriers based on the expert survey by academicians and industry experts from industries in India. The concept map helps in identifying possible solutions for the challenges and initiatives to be taken for the smooth integration of technologies in the green supply chain.
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Juliana Elisa Raffaghelli, Marc Romero Carbonell and Teresa Romeu-Fontanillas
It has been demonstrated that AI-powered, data-driven tools’ usage is not universal, but deeply linked to socio-cultural contexts. The purpose of this paper is to display the need…
Abstract
Purpose
It has been demonstrated that AI-powered, data-driven tools’ usage is not universal, but deeply linked to socio-cultural contexts. The purpose of this paper is to display the need of adopting situated lenses, relating to specific personal and professional learning about data protection and privacy.
Design/methodology/approach
The authors introduce the results of a case study based on a large educational intervention at a fully online university. The views of the participants from degrees representing different knowledge areas and contexts of technology adoption (work, education and leisure) were explored after engaging in the analysis of the terms and conditions of use about privacy and data usage. After consultation, 27 course instructors (CIs) integrated the activity and worked with 823 students (702 of whom were complete and correct for analytical purposes).
Findings
The results of this study indicated that the intervention increased privacy-conscious online behaviour among most participants. Results were more contradictory when looking at the tools’ daily usage, with overall positive considerations around the tools being mostly needed or “indispensable”.
Research limitations/implications
Though appliable only to the authors’ case study and not generalisable, the authors’ results show both the complexity of privacy views and the presence of forms of renunciation in the trade-off between data protection and the need of using a specific software into a personal and professional context.
Practical implications
This study provides an example of teaching and learning activities that supports the development of data literacy, with a focus on data privacy. Therefore, beyond the research findings, any educator can build over the authors’ proposal to produce materials and interventions aimed at developing awareness on data privacy issues.
Social implications
Developing awareness, understanding and skills relating to data privacy is crucial to live in a society where digital technologies are used in any area of our personal and professional life. Well-informed citizens will be able to obscure, resist or claim for their rights whenever a violation of their privacy takes place. Also, they will be able to support (through adoption) better quality apps and platforms, instead of passively accepting what is evident or easy to use.
Originality/value
The authors specifically spot how students and educators, as part of a specific learning and cultural ecosystem, need tailored opportunities to keep on reflecting on their degrees of freedom and their possibilities to act regarding evolving data systems and their alternatives.
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Mahesh Babu Purushothaman and Kasun Moolika Gedara
This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and…
Abstract
Purpose
This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.
Design/methodology/approach
Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).
Findings
Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.
Research limitations/implications
Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.
Practical implications
The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.
Social implications
By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.
Originality/value
Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.
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