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1 – 4 of 4Kristiina Niemi-Kaija and Steven Pattinson
The purpose of this systematic narrative review is to discourse on vision and organizational performance. By analysing work-life and organization studies journals, the authors…
Abstract
Purpose
The purpose of this systematic narrative review is to discourse on vision and organizational performance. By analysing work-life and organization studies journals, the authors respond to a call to view the process of visioning more holistically.
Design/methodology/approach
The methodological approach is a discourse-oriented qualitative content analysis. The authors explore visioning through an epistemological lens, which emphasizes both the connections and differences between “traditional” philosophical approaches.
Findings
The findings show how the different interpretations of vision and related concepts are tied to the following themes: clarity, causality, embodiment and sensory experiences and actionability.
Originality/value
Through the frameworks of scientific realism and relativism, the authors illustrate novel insights into the ways in which visioning occupies a place in knowledge management.
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Weak repeatability is observed in handcrafted keypoints, leading to tracking failures in visual simultaneous localization and mapping (SLAM) systems under challenging scenarios…
Abstract
Purpose
Weak repeatability is observed in handcrafted keypoints, leading to tracking failures in visual simultaneous localization and mapping (SLAM) systems under challenging scenarios such as illumination change, rapid rotation and large angle of view variation. In contrast, learning-based keypoints exhibit higher repetition but entail considerable computational costs. This paper proposes an innovative algorithm for keypoint extraction, aiming to strike an equilibrium between precision and efficiency. This paper aims to attain accurate, robust and versatile visual localization in scenes of formidable complexity.
Design/methodology/approach
SiLK-SLAM initially refines the cutting-edge learning-based extractor, SiLK, and introduces an innovative postprocessing algorithm for keypoint homogenization and operational efficiency. Furthermore, SiLK-SLAM devises a reliable relocalization strategy called PCPnP, leveraging progressive and consistent sampling, thereby bolstering its robustness.
Findings
Empirical evaluations conducted on TUM, KITTI and EuRoC data sets substantiate SiLK-SLAM’s superior localization accuracy compared to ORB-SLAM3 and other methods. Compared to ORB-SLAM3, SiLK-SLAM demonstrates an enhancement in localization accuracy even by 70.99%, 87.20% and 85.27% across the three data sets. The relocalization experiments demonstrate SiLK-SLAM’s capability in producing precise and repeatable keypoints, showcasing its robustness in challenging environments.
Originality/value
The SiLK-SLAM achieves exceedingly elevated localization accuracy and resilience in formidable scenarios, holding paramount importance in enhancing the autonomy of robots navigating intricate environments. Code is available at https://github.com/Pepper-FlavoredChewingGum/SiLK-SLAM.
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Liezl Smith and Christiaan Lamprecht
In a virtual interconnected digital space, the metaverse encompasses various virtual environments where people can interact, including engaging in business activities. Machine…
Abstract
Purpose
In a virtual interconnected digital space, the metaverse encompasses various virtual environments where people can interact, including engaging in business activities. Machine learning (ML) is a strategic technology that enables digital transformation to the metaverse, and it is becoming a more prevalent driver of business performance and reporting on performance. However, ML has limitations, and using the technology in business processes, such as accounting, poses a technology governance failure risk. To address this risk, decision makers and those tasked to govern these technologies must understand where the technology fits into the business process and consider its limitations to enable a governed transition to the metaverse. Using selected accounting processes, this study aims to describe the limitations that ML techniques pose to ensure the quality of financial information.
Design/methodology/approach
A grounded theory literature review method, consisting of five iterative stages, was used to identify the accounting tasks that ML could perform in the respective accounting processes, describe the ML techniques that could be applied to each accounting task and identify the limitations associated with the individual techniques.
Findings
This study finds that limitations such as data availability and training time may impact the quality of the financial information and that ML techniques and their limitations must be clearly understood when developing and implementing technology governance measures.
Originality/value
The study contributes to the growing literature on enterprise information and technology management and governance. In this study, the authors integrated current ML knowledge into an accounting context. As accounting is a pervasive aspect of business, the insights from this study will benefit decision makers and those tasked to govern these technologies to understand how some processes are more likely to be affected by certain limitations and how this may impact the accounting objectives. It will also benefit those users hoping to exploit the advantages of ML in their accounting processes while understanding the specific technology limitations on an accounting task level.
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Crystal Glenda Rodrigues and B.V. Gopalakrishna
The investment behaviour of individuals has been a major area of interest for several researchers and policymakers due to its great impact on the economy. This study aimed to…
Abstract
Purpose
The investment behaviour of individuals has been a major area of interest for several researchers and policymakers due to its great impact on the economy. This study aimed to assess the investment behaviour of individuals in light of their risk appetite and how financial literacy regulates this relationship.
Design/methodology/approach
A self-administered structured questionnaire was used to collect responses from individuals using purposive and convenience sampling techniques. Individuals were presented with 16 investment avenues widely offered by the Indian financial market to choose from to construct a hypothetical portfolio. The association between risk appetite, financial literacy and the composition of the hypothetical portfolio was analysed using a gologit model.
Findings
Increased risk appetite increased the probability of respondents creating a portfolio with a greater proportion of risky assets and less diversification. Lower levels of financial literacy pointed towards portfolios with traditional and low-risk avenues. The results also revealed a significant moderating impact of financial literacy on risk appetite and the creation of the type of a hypothetical portfolio.
Research limitations/implications
Even though the intended behaviour is a close estimate of actual behaviour, there is a possibility of deviation that cannot be ignored.
Originality/value
The present study provides insights into how individuals make portfolio choices by incorporating risk appetite and diversification factors whilst making investment decisions, thereby expanding the literature from an emerging economy perspective. The role of financial literacy as a moderator has not been studied in the domain of hypothetical portfolio creation in India, which has been empirically explored in the current study.
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