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1 – 10 of 65Milad Dehghani, A. Mohammed Abubakar and Mohsen Pashna
The purpose of this paper is to identify and describe the drivers of lean approaches and successful management of wearable technology start-ups. The paper is a descriptive study…
Abstract
The purpose of this paper is to identify and describe the drivers of lean approaches and successful management of wearable technology start-ups. The paper is a descriptive study that employed a case study methodology based on semi-structured interviews with ten start-ups’ managers in Wearable Technology 2017 conference. Participants were selected based on convenience sampling and the pre-set criteria. The current study contributes to this field through the main findings, which suggest that four stages need to be considered by starts-up for a successful market readiness, including the time of entry and overcoming market entry barriers, product attributes, product development process, and commercialization. Finally, findings were categorized in the form of an iterative learning loop model and also, practical strategies and methods were recommended for successfully going through each stage.
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Ali Sevilmiş, Mehmet Doğan, Pablo Gálvez-Ruiz and Jerónimo García-Fernández
The user experience during the use of activities and services is a fundamental aspect for sports managers and can provide a competitive advantage. The purpose of this study was to…
Abstract
Purpose
The user experience during the use of activities and services is a fundamental aspect for sports managers and can provide a competitive advantage. The purpose of this study was to identify the dimensions of experiential quality and the relationship of this construct with customer trust and customer satisfaction in achieving behavioral intention.
Design/methodology/approach
Using a convenience sampling technique, a total of 322 gym users in Turkey participated. A two-step approach was used to test both the model and the research hypotheses [confirmatory factor analysis (CFA) and structural equation modeling (SEM)].
Findings
The interaction quality, physical environmental quality, outcome quality and enjoyment quality were positively related to experiential quality. Similarly, the experimental quality was positively related to customer satisfaction and customer trust. Finally, customer satisfaction was related to behavioral intentions.
Originality/value
This study provides empirical evidence about the importance of experiential quality to gain a competitive advantage in the context of fitness centers.
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The study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt…
Abstract
Purpose
The study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt m-learning in teaching and learning, including its acceptance.
Design/methodology/approach
A structured questionnaire was administered to open and distance learning (ODL) students in Odisha, India, to assess their readiness and acceptance of m-learning. 665 valid responses were collected, and collected data was analysed using statistical packages for social sciences (SPSS) and SmartPLS.
Findings
The findings of the study reveal that optimism contributes positively to perceived ease of use (PEOU) and perceived usefulness (PU) of m-learning (β = 7.921, p < 0.001; β = 2.123, p < 0.05), whereas innovativeness positively contributes to PEOU of m-learning (β = 2.227, p < 0.05), but not PU of m-learning. ODL student's optimism improves his/her PEOU and PU of m-learning, but innovativeness improves only his/her PEOU. Further, the impact of innovativeness is higher than that of optimism in the TRAM and innovativeness is the strong predictor to adopt m-learning. It also shows that the PU of m-learning positively influences behavioural intention to use m-learning (β = 4.757, p < 0.001). Integrating technology readiness (TR) with technology acceptance model (TAM) to predict students' acceptance of m-learning is very useful.
Practical implications
The paper will help decision-makers to adopt and use m-learning in higher educational institutions.
Originality/value
This paper is the first to explore the readiness and acceptance of m-learning in higher education in India.
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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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Jiaqi Lu, Shijun Liu, Lizhen Cui, Li Pan and Lei Wu
A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic…
Abstract
Purpose
A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic principle for intelligent crowds in an attempt to show that crowd wisdom could help in making accurate judgments and proper decisions. This further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.
Design/methodology/approach
Efforts to support the critical role of crowd wisdom in intelligent manufacturing involve theoretical explanation, including a discussion of several prevailing concepts, such as consumer-to-business (C2B), crowdfunding and an interpretation of the contemporary Big Data mania. In addition, an empirical study with three business cases was conducted to prove the conclusion that our ideas could well explain the current business phenomena and guide the future of manufacturing.
Findings
This paper shows that crowd wisdom could help make accurate judgments and proper decisions. It further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.
Originality/value
The paper highlights the importance of crowd wisdom in manufacturing with sufficient theoretical and empirical analysis, potentially providing a guideline for future industry.
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Antje Fricke, Nadine Pieper and David M. Woisetschläger
Consumers' perceptions of product intelligence affect their willingness to accept smart offerings. This paper explores how people perceive various smart products based on their…
Abstract
Purpose
Consumers' perceptions of product intelligence affect their willingness to accept smart offerings. This paper explores how people perceive various smart products based on their smartness profiles, composed of five distinct smartness facets. Additionally, the study investigates how these perceptions of product intelligence impact consumers' evaluation of factors that either promote or impede the adoption of smart products. These factors are examined as potential mediators in the adoption process. This paper aims to determine if the value-based adoption model can be applied to a broad range of smart service systems.
Design/methodology/approach
Consumers assessed one of 28 smart products in a scenario-based quantitative study. Multilevel structural equation modeling (SEM) is used to test the conceptual model, taking the nested data structure into account.
Findings
The findings show that product smartness essentially enhances usage intention via adoption drivers (enjoyment and usefulness) and reduces usage intention via adoption barriers (intrusiveness). In particular, the ability to interact in a humanlike manner increases the benefits consumers perceive, which in turn increases consumer acceptance. Only the smartness characteristic of awareness impairs usage intention, mediated by the perceived benefits of enjoyment and usefulness.
Originality/value
In contrast to previous research, which usually focuses on single smart products, this work examines a variety of different products, which allows for better transferability of the results to other smart offerings. Furthermore, prior research has mainly focused on single facets of product smartness or researched smartness on an aggregated level. By considering the consumer perception of each smartness facet, the authors gain deeper insights into the perceptual differences regarding product smartness and how this affects technology adoption via conflicting key acceptance drivers and barriers.
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Kabir Ibrahim, Fredrick Simpeh and Oluseyi Julius Adebowale
Technologies have had a positive impact on the construction industry. Technologies such as BIM, automation, augmented and virtual reality, Internet of Things and robotics have…
Abstract
Purpose
Technologies have had a positive impact on the construction industry. Technologies such as BIM, automation, augmented and virtual reality, Internet of Things and robotics have been adopted by construction firms to enhance productivity. However, not much research has been done on the awareness and adoption of wearable technologies for health and safety (H&S) management. This paper investigates the level of awareness and adoption of wearable technologies for H&S management in the Nigerian construction industry.
Design/methodology/approach
A quantitative research method was adopted for the study. An electronic questionnaire format was used as an instrument to collect the data. Both descriptive (mean score) and inferential statistics (Kruskal–Wallis test) were used to analyse the data.
Findings
The results indicate that organisations rarely use H&S wearable devices for H&S management although professionals within the construction industry are somewhat aware of the common H&S wearable devices. The findings further indicate that all 11 variables were perceived as “rarely adopted”, whereas 2 variables were perceived as “aware”, 3 variables as “slightly aware” and the remaining 6 variables as “somewhat aware”.
Research limitations/implications
Data were collected from only construction professionals working in government agencies, consultancy firms and grade D contracting firms in Lagos and Abuja. For a broader perspective, a study that expands the number of states and categories of construction firms is recommended.
Practical implications
The construction industry in Nigeria can use the recommendations to improve H&S management on site. Moreover, the recommendations can contribute to the development of policies to promote the adoption of wearable technologies in construction sites.
Originality/value
Research on wearable technologies, particularly in the Nigerian construction industry, is at the developing stage. With this article, the authors contribute to the body of knowledge in this area of research.
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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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Elina Ilén, Farid Elsehrawy, Elina Palovuori and Janne Halme
Solar cells could make textile-based wearable systems energy independent without the need for battery replacement or recharging; however, their laundry resistance, which is…
Abstract
Purpose
Solar cells could make textile-based wearable systems energy independent without the need for battery replacement or recharging; however, their laundry resistance, which is prerequisite for the product acceptance of e-textiles, has been rarely examined. This paper aims to report a systematic study of the laundry durability of solar cells embedded in textiles.
Design/methodology/approach
This research included small commercial monocrystalline silicon solar cells which were encapsulated with functional synthetic textile materials using an industrially relevant textile lamination process and found them to reliably endure laundry washing (ISO 6330:2012). The energy harvesting capability of eight textile laminated solar cells was measured after 10–50 cycles of laundry at 40 °C and compared with light transmittance spectroscopy and visual inspection.
Findings
Five of the eight textile solar cell samples fully maintained their efficiency over the 50 laundry cycles, whereas the other three showed a 20%–27% decrease. The cells did not cause any visual damage to the fabric. The result indicates that the textile encapsulated solar cell module provides sufficient protection for the solar cells against water, washing agents and mechanical stress to endure repetitive domestic laundry.
Research limitations/implications
This study used rigid monocrystalline silicon solar cells. Flexible amorphous silicon cells were excluded because of low durability in preliminary tests. Other types of solar cells were not tested.
Originality/value
A review of literature reveals the tendency of researchers to avoid standardized textile washing resistance testing. This study removes the most critical obstacle of textile integrated solar energy harvesting, the washing resistance.
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Hamad Al Jassmi, Mahmoud Al Ahmad and Soha Ahmed
The first step toward developing an automated construction workers performance monitoring system is to initially establish a complete and competent activity recognition solution…
Abstract
Purpose
The first step toward developing an automated construction workers performance monitoring system is to initially establish a complete and competent activity recognition solution, which is still lacking. This study aims to propose a novel approach of using labor physiological data collected through wearable sensors as means of remote and automatic activity recognition.
Design/methodology/approach
A pilot study is conducted against three pre-fabrication stone construction workers throughout three full working shifts to test the ability of automatically recognizing the type of activities they perform in-site through their lively measured physiological signals (i.e. blood volume pulse, respiration rate, heart rate, galvanic skin response and skin temperature). The physiological data are broadcasted from wearable sensors to a tablet application developed for this particular purpose, and are therefore used to train and assess the performance of various machine-learning classifiers.
Findings
A promising result of up to 88% accuracy level for activity recognition was achieved by using an artificial neural network classifier. Nonetheless, special care needs to be taken for some activities that evoke similar physiological patterns. It is expected that blending this method with other currently developed camera-based or kinetic-based methods would yield higher activity recognition accuracy levels.
Originality/value
The proposed method complements previously proposed labor tracking methods that focused on monitoring labor trajectories and postures, by using additional rich source of information from labors physiology, for real-time and remote activity recognition. Ultimately, this paves for an automated and comprehensive solution with which construction managers could monitor, control and collect rich real-time data about workers performance remotely.
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