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1 – 10 of 12Salman Khan, Qingyu Zhang, Safeer Ullah Khan, Ikram Ullah Khan and Rafi Ullah Khan
Augmented reality (AR) adoption has boomed globally in recent years. The prospective of AR to seamlessly integrate digital information into the actual environment has proven to be…
Abstract
Purpose
Augmented reality (AR) adoption has boomed globally in recent years. The prospective of AR to seamlessly integrate digital information into the actual environment has proven to be a challenge for academics and industry, as they endeavor to understand and predict the influence on users' perceptions, adoption intentions and usage. This study investigates the factors affecting consumers’ behavioral intention to adopt AR technology in shopping malls by offering the mobile technology acceptance model (MTAM).
Design/methodology/approach
This conceptual framework is based on mobile self-efficacy, rewards, social influence and enjoyment of existing MTAM constructs. A self-administered questionnaire, constructed by measuring questions modified from previous research, elicited 311 usable responses from mobile respondents who had recently used AR technology in shopping malls. This analysis was performed using SmartPLS3.0.
Findings
Grounded on the findings of the study, it was found that, aside from factors such as mobile usefulness, ease of use and social influence, the remaining independent variables had the most significant impact on adopting AR technologies. Considering the limitations of this study, the paper concludes by discussing the significant implications and insinuating avenues for future research.
Originality/value
To better investigate mobile AR app adoption in Pakistan’s shopping malls, the researchers modified the newly proposed MTAM model by incorporating mobile self-efficacy theory, social influence, rewards and perceived enjoyment. However, the extended model has not been extensively studied in previous research. This study is the first to examine the variables that affect an individual’s intention to accept mobile AR apps by using a novel extended MTAM.
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Valtteri Kaartemo and Anu Helkkula
Applications of artificial intelligence (AI), such as virtual and physical service robots, generative AI, large language models and decision support systems, alter the nature of…
Abstract
Purpose
Applications of artificial intelligence (AI), such as virtual and physical service robots, generative AI, large language models and decision support systems, alter the nature of services. Most service research centers on the division between human and AI resources. Less attention has been paid to analyzing the entangled resource relations and interactions between humans and AI entities. Thus, the purpose of this paper is to extend our metatheoretical understanding of resource integration and value cocreation by analyzing different human–AI resource relations in service ecosystems.
Design/methodology/approach
The conceptual paper adapts a novel framework from postphenomenology, specifically cyborg intentionality. This framework is used to analyze what kinds of human–AI resource relations enable resource integration and value cocreation in service ecosystems.
Findings
We conceptualize seven different human–AI resource relations, namely background, embodiment, hermeneutic, alterity, cyborg, immersion and composite relation. The sociotechnical entangled perspective on human–AI resource relations challenges and reframes our understanding of interactions between humans and nonhumans in resource integration and value cocreation and the distinction between operant and operand resources in service research.
Originality/value
Our primary contribution to researchers and service providers is dissolving the distinction between operant and operand resources. We present two foundational propositions. 1. Humans and AI become entangled value cocreating resources in inherently sociotechnical service ecosystems; and 2. Human and AI entanglements in value cocreation manifest through seven resource relations in inherently sociotechnical service ecosystems. Understanding the combinatorial potential of different human–AI resource relations enables service providers to make informed choices in service ecosystems.
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The purpose of this study is to focus on, namely, the international financial reporting standards (IFRS) or local generally accepted accounting principles (GAAP) effects of…
Abstract
Purpose
The purpose of this study is to focus on, namely, the international financial reporting standards (IFRS) or local generally accepted accounting principles (GAAP) effects of financial reporting as a corporate governance mechanism on mergers and acquisitions (M&As) for banking institutions during the global financial crisis.
Design/methodology/approach
I investigate the characteristics of bank financial statements before the start of the global crisis, which helps to explain the relationships between the accounting standards and the global financial crisis. The observations, which are based on 3,178 deals in a sample period, are crucially important for corporate governance and bank performance. The results from our analysis are robust to a wide variety of modifications in our research design and are corroborated by descriptive statistics, one-way ANOVA and a two-sample t-test on a sample of banks that voluntarily adopted IFRS for M&As.
Findings
The find that IFRS-based monitoring of banks M&As in terms of higher quality financial reporting is negatively linked with bank performance, whereas local GAAP-based monitoring of banks’ M&A is positively associated with accounting performance. Finally, our main results for higher quality financial reporting under local GAAP or IFRS generally hold after controlling for various analyses and relationships between account standards and the financial crisis.
Practical implications
Financial reporting standards setting a corporate governance mechanism are considered since it was impacted recently during the global financial crisis and became a great matter of concern.
Originality/value
The value of this paper is determined by an empirical investigation of the relationships between bank performance and accounting and financial reporting standards in the context of the global economy.
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Ahmed Elaksher and Bhavana Kotla
Photogrammetry enables scientists and engineers to make accurate and precise measurements from optical images and other patterns of reflected electromagnetic energy…
Abstract
Purpose
Photogrammetry enables scientists and engineers to make accurate and precise measurements from optical images and other patterns of reflected electromagnetic energy. Photogrammetry is taught in surveying, geomatics and similar academic programs. For a long time, it has been observed that there is a lack of diversity and underrepresentation of different groups in the surveying and geomatics workforces for various reasons. Diversity fosters more innovative environments, helps employees be more engaged and boosts productivity rates. Although efforts are being made to solve this problem, most attempts did not significantly improve the diversity issues in this field. To address this problem, we designed a new curriculum for a photogrammetry course, which integrates entrepreneurial mindset (EM), bio-inspired design and Science, Technology, Engineering, Arts and Mathematics (STEAM) into the photogrammetry course for this study.
Design/methodology/approach
In this study, the participatory action research method, Photovoice, was used to gather data. Students were asked to respond to photovoice and metacognitive reflection prompts to understand student perceptions about the importance of Unmanned Aerial Vehicles (UAVs) in photogrammetric mapping. Students were required to respond to each prompt with three pictures and a narrative. These reflections were analyzed using thematic analysis.
Findings
The analysis of the photovoice and metacognitive reflections resulted in six themes: promoting digital literacy, promoting job readiness and awareness, improving perceived learning outcomes, increasing interest in pursuing careers in surveying/geomatics, encouraging learner engagement and increasing awareness of the role of art in map making.
Originality/value
This is the first study conducted at our Hispanic Serving Institution, which specifically designed a curriculum integrating EM, bio-inspired design and STEAM concepts to address diversity issues in surveying and geomatics engineering disciplines.
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Jane F. Maley, Marina Dabić, Alain Neher, Lucia Wuersch, Lynn Martin and Timothy Kiessling
This conceptual work examines how, in times of post-COVID-19 paradigm shift, the employee performance management (PM) process can help multinational corporations (MNCs) strengthen…
Abstract
Purpose
This conceptual work examines how, in times of post-COVID-19 paradigm shift, the employee performance management (PM) process can help multinational corporations (MNCs) strengthen their talent management and, at the same time, meet their future needs.
Design/methodology/approach
We take a conceptual approach and present our perspective on what we see as the most critical trends shaping PM and talent management. Contingency theory and Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) theory provide a sound theoretical framework for understanding and responding to the complex and rapidly changing business context post-COVID-19.
Findings
Drawing on these theories, we create a framework providing a means of understanding why and how MNCs can maintain talent and, at the same time, develop new talent through the PM process.
Practical implications
Importantly, our study emphasizes the critical role that project management and talent management techniques play for both practitioners and scholars. In order to gain and sustain a competitive edge in the ever-changing VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) landscape, these processes necessitate ongoing reassessment and adaptation. As Plato eloquently stated, “Our Need Will Be the Real Creator,” encapsulating our vision for the proactive and dynamic nature of effective project management and talent management practices.
Originality/value
The study establishes the benefits of an agile and flexible PM approach to help develop talent and pave the way for future research in this increasingly critical area
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This paper aims to examine the low-cost carriers (LCC) impact on the high-quality carriers (HQC) in the aviation industry. The impact of LCCs on high-quality producers in the…
Abstract
Purpose
This paper aims to examine the low-cost carriers (LCC) impact on the high-quality carriers (HQC) in the aviation industry. The impact of LCCs on high-quality producers in the aviation industry has been a significant and multifaceted phenomenon.
Design/methodology/approach
The study employs a captivating case study approach, investigating into the intricate fabric of the subject matter. Interviews serve as the cornerstone of primary evidence, offering first-hand insights, while secondary data sourced from documents adds depth to the exploration of the challenges encountered by the HQC.
Findings
The study concludes that LCCs have disrupted the traditional aviation landscape by offering low fares, simplified service models and aggressive cost-cutting strategies. This disruption has affected both the high-quality producers, such as full-service airlines. Full-service airlines have adopted a strategy of segmenting their market by offering multiple fare classes, with varying levels of service and flexibility. This allows them to target both price-sensitive travelers and those seeking premium services, catering to a broader customer base. The competition from LCCs has spurred innovation within the aviation industry, leading to advancements in technology, digital services and operational efficiency. Airlines, both LCCs and traditional carriers, have had to adapt to evolving consumer preferences and embrace digital solutions for booking, check-in and in-flight services.
Research limitations/implications
While this study provides a valuable cost-benefit analysis of the impact of LCC on high-quality producers in the aviation industry, it is essential to acknowledge its limitations and recognize the avenues for future research to further enhance our understanding of this complex and evolving industry landscape. While this study contributes valuable insights into the impact of LCCs on high-quality producers in the aviation industry, it is essential to recognize its limitations and identify opportunities for future research to expand our understanding of this complex and dynamic landscape. By addressing these limitations and exploring new avenues of inquiry, we can continue to advance our knowledge and inform evidence-based decision-making within the industry.
Originality/value
This study pioneers an exploration into the intricate tapestry of factors molding the future of the aviation sector. Through its groundbreaking analysis, it furnishes indispensable insights for industry stakeholders, policymakers and the discerning traveling public, setting a new benchmark for understanding and navigating the aviation landscape.
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Abderahman Rejeb, Karim Rejeb, Andrea Appolloni, Suhaiza Zailani and Mohammad Iranmanesh
Given the growing significance of contemporary socio-economic and infrastructural conversations of Public-Private Partnerships (PPP), this research seeks to provide a general…
Abstract
Purpose
Given the growing significance of contemporary socio-economic and infrastructural conversations of Public-Private Partnerships (PPP), this research seeks to provide a general overview of the academic landscape concerning PPP.
Design/methodology/approach
To offer a nuanced perspective, the study adopts the Latent Dirichlet Allocation (LDA) methodology to meticulously analyse 3,057 journal articles, mapping out the thematic contours within the PPP domain.
Findings
The analysis highlights PPP's pivotal role in harmonising public policy goals with private sector agility, notably in areas like disaster-ready sustainable infrastructure and addressing rapid urbanisation challenges. The emphasis within the literature on financial, risk, and performance aspects accentuates the complexities inherent in financing PPP and the critical need for practical evaluation tools. An emerging focus on healthcare within PPP indicates potential for more insightful research, especially amid ongoing global health crises.
Originality/value
This study pioneers the application of LDA for an all-encompassing examination of PPP-related academic works, presenting unique theoretical and practical insights into the diverse facets of PPP.
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Mohd Firdaus Naif Omran Zailuddin, Nik Ashri Nik Harun, Haris Abadi Abdul Rahim, Azmul Fadhli Kamaruzaman, Muhammad Hawari Berahim, Mohd Hilmi Harun and Yuhanis Ibrahim
The purpose of this research is to explore the transformative impact of AI-augmented tools on design pedagogy. It aims to understand how artificial intelligence technologies are…
Abstract
Purpose
The purpose of this research is to explore the transformative impact of AI-augmented tools on design pedagogy. It aims to understand how artificial intelligence technologies are being integrated into educational settings, particularly in creative design courses, and to assess the potential advancements these tools can bring to the field.
Design/methodology/approach
The research adopts a case-study approach, examining three distinct courses within a creative technology curriculum. This methodology involves an in-depth investigation of the role and impact of AI in each course, focusing on how these technologies are incorporated into different creative disciplines such as production design, fine arts, and digital artistry.
Findings
The research findings highlight that the integration of AI with creative disciplines is not just a passing trend but signals the onset of a new era in technological empowerment in creative education. This amalgamation is found to potentially redefine the boundaries of creative education, enhancing various aspects of the learning process. However, the study also emphasizes the irreplaceable value of human mentorship in cultivating creativity and advancing analytical thinking.
Research limitations/implications
The limitations of this research might include the scope of the case studies, which are limited to three courses in a specific curriculum. This limitation could affect the generalizability of the findings. The implications of this research are significant for educational institutions, as it suggests the need for a balanced interaction between AI's computational abilities and the intrinsic qualities of human creativity, ensuring that the core essence of artistry is preserved in the age of AI.
Originality/value
The originality of this paper lies in its specific focus on the intersection of AI and creative education, a relatively unexplored area in design pedagogy. The value of this research is in its contribution to understanding how AI can be harmoniously integrated with traditional creative teaching methods. It offers insights for educational institutions preparing for this technological transformation, highlighting the importance of maintaining a balance between technological advancements and humanistic aspects of creative education.
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Tianyi Zhang, Haowu Luo, Ning Liu, Feiyan Min, Zhixin Liang and Gao Wang
As the demand for human–robot collaboration in manufacturing applications grows, the necessity for collision detection functions in robots becomes increasingly paramount for…
Abstract
Purpose
As the demand for human–robot collaboration in manufacturing applications grows, the necessity for collision detection functions in robots becomes increasingly paramount for safety. Hence, this paper aims to improve the existing method to achieve efficient, accurate and sensitive robot collision detection.
Design/methodology/approach
The external torque is estimated by momentum observers based on the robot dynamics model. Because the state of the joints is more accessible to distinguish under the action of the suppression operator proposed in this paper, the mutated external torque caused by joint reversal can be accurately attenuated. Finally, time series analysis (TSA) methods can continuously generate dynamic thresholds based on external torques.
Findings
Compared with the collision detection method based only on TSA, the invalid time of the proposed method is less during joint reversal. Although the soft-collision detection accuracy of this method is lower than that of the symmetric threshold method, it is superior in terms of detection delay and has a higher hard-collision detection accuracy.
Originality/value
Owing to the mutated external torque caused by joint reversal, which seriously affects the stability of time series models, the collision detection method based only on TSA cannot detect continuously. The consequences are disastrous if the robot collides with people or the environment during joint reversal. After multiple experimental verifications, the proposed method still exhibits detection capabilities during joint reversal and can implement real-time collision detection. Therefore, it is suitable for various engineering applications.
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The accurate valuation of second-hand vessels has become a prominent subject of interest among investors, necessitating regular impairment tests. Previous literature has…
Abstract
Purpose
The accurate valuation of second-hand vessels has become a prominent subject of interest among investors, necessitating regular impairment tests. Previous literature has predominantly concentrated on inferring a vessel's price through parameter estimation but has overlooked the prediction accuracy. With the increasing adoption of machine learning for pricing physical assets, this paper aims to quantify potential factors in a non-parametric manner. Furthermore, it seeks to evaluate whether the devised method can serve as an efficient means of valuation.
Design/methodology/approach
This paper proposes a stacking ensemble approach with add-on feedforward neural networks, taking four tree-driven models as base learners. The proposed method is applied to a training dataset collected from public sources. Then, the performance is assessed on the test dataset and compared with a benchmark model, commonly used in previous studies.
Findings
The results on the test dataset indicate that the designed method not only outperforms base learners under statistical metrics but also surpasses the benchmark GAM in terms of accuracy. Notably, 73% of the testing points fall within the less-than-10% error range. The designed method can leverage the predictive power of base learners by incrementally adding a small amount of target value through residuals and harnessing feature engineering capability from neural networks.
Originality/value
This paper marks the pioneering use of the stacking ensemble in vessel pricing within the literature. The impressive performance positions it as an efficient desktop valuation tool for market users.
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