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Article
Publication date: 8 August 2023

Grete Helle and John Roberts

The purpose of this paper is to explore how hierarchical accountability can be enacted and accounting control systems mobilized in a way that promotes a sense of felt…

Abstract

Purpose

The purpose of this paper is to explore how hierarchical accountability can be enacted and accounting control systems mobilized in a way that promotes a sense of felt responsibility.

Design/methodology/approach

The paper draws on interviews, shadowing and observations to explore the implementation of a strategy for “increasing accountability” in a Norwegian Oil Company. The case provided an opportunity to explore the dynamics of hierarchical accountability and felt responsibility, and in particular Roberts (2009) concept of “intelligent accountability”, in an empirical context.

Findings

The case study explores how the strategy of increasing accountability at OilCo was enacted around three operational issues; the control of costs, roles and relationships in the complex matrix structure, and the operation of the management system. It traces how the long history of Beyond Budgeting practices and philosophy in OilCo resulted both in an explicit recognition of the incompleteness of accounting numbers, and trust-based practices which avoided many of the dysfunctional individual and organizational effects typically associated with the exercise of hierarchical control.

Originality/value

The paper explores empirically how OilCo’s embrace of Beyond Budgeting practices and philosophy had created the conditions under which a more intelligent form of accountability could emerge. As a European case study, it calls into question the Anglo-American tradition of accounting research which suggests that externally imposed accountability within a hierarchy mitigates against employees’ felt responsibility.

Details

Accounting, Auditing & Accountability Journal, vol. 37 no. 3
Type: Research Article
ISSN: 0951-3574

Keywords

Article
Publication date: 29 March 2024

Sihao Li, Jiali Wang and Zhao Xu

The compliance checking of Building Information Modeling (BIM) models is crucial throughout the lifecycle of construction. The increasing amount and complexity of information…

Abstract

Purpose

The compliance checking of Building Information Modeling (BIM) models is crucial throughout the lifecycle of construction. The increasing amount and complexity of information carried by BIM models have made compliance checking more challenging, and manual methods are prone to errors. Therefore, this study aims to propose an integrative conceptual framework for automated compliance checking of BIM models, allowing for the identification of errors within BIM models.

Design/methodology/approach

This study first analyzed the typical building standards in the field of architecture and fire protection, and then the ontology of these elements is developed. Based on this, a building standard corpus is built, and deep learning models are trained to automatically label the building standard texts. The Neo4j is utilized for knowledge graph construction and storage, and a data extraction method based on the Dynamo is designed to obtain checking data files. After that, a matching algorithm is devised to express the logical rules of knowledge graph triples, resulting in automated compliance checking for BIM models.

Findings

Case validation results showed that this theoretical framework can achieve the automatic construction of domain knowledge graphs and automatic checking of BIM model compliance. Compared with traditional methods, this method has a higher degree of automation and portability.

Originality/value

This study introduces knowledge graphs and natural language processing technology into the field of BIM model checking and completes the automated process of constructing domain knowledge graphs and checking BIM model data. The validation of its functionality and usability through two case studies on a self-developed BIM checking platform.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 24 April 2023

Priya Garg and Shivarama Rao K.

This paper aims to discuss the process of building a 24×7 reference platform for facilitating the farmers with the easy access of information at any time from any location. It…

Abstract

Purpose

This paper aims to discuss the process of building a 24×7 reference platform for facilitating the farmers with the easy access of information at any time from any location. It takes the text string as input and process it to respond with the desired result to the user.

Design/methodology/approach

An interactive Web-based chatbot named as AgriRef was developed using free version of Dialogflow. The intents were defined based on the conversation flow diagram. Furthermore, the application was integrated with website on local server and telegram application.

Findings

With this chatbot application, the farmers will able to get answers of their queries. It provides the human-like conversational interface to the farmers. It will also be useful for librarians of agricultural libraries to save time in answering common queries.

Originality/value

This paper describes the various steps involved in developing the chatbot application using Dialogflow.

Details

Library Hi Tech News, vol. 41 no. 2
Type: Research Article
ISSN: 0741-9058

Keywords

Open Access
Article
Publication date: 26 December 2023

Christian Kowalkowski, Jochen Wirtz and Michael Ehret

Technology-enabled business-to-business (B2B) services contribute the largest share to GDP growth and are fundamental for an economy’s value creation. This article aims to…

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Abstract

Purpose

Technology-enabled business-to-business (B2B) services contribute the largest share to GDP growth and are fundamental for an economy’s value creation. This article aims to identify key service- and digital technology-driven B2B innovation modes and proposes a research agenda for further exploration.

Design/methodology/approach

This conceptual paper adopts a techno-demarcation view on service innovation, encompassing three core dimensions: service offering (the service product, or the “what”), service process (the “how”) and service ecosystem (the “who/for whom”). It delineates the implications of three digital technologies – the internet-of-things (IoT), intelligent automation (IA) and digital platforms – for service innovation across these core dimensions in B2B markets.

Findings

Digital technology has immense potential ramifications for value creation by reshaping all three core dimensions of service innovation. Specifically, IoT can transform physical resources into reconfigurable service products, IA can augment and automate a rapidly expanding array of service processes, while digital platforms provide the technical and organizational infrastructure for the integration of resources and stakeholders within service ecosystems.

Originality/value

This study suggests an agenda with six themes for further research, each linked to one or more of the three service innovation dimensions. They are (1) new recurring revenue models, (2) service innovation in the metaverse, (3) scaling up service innovations, (4) ecosystem innovations, (5) power dependency and lock-in effects and (6) security and responsibility in digital domains.

Details

Journal of Service Management, vol. 35 no. 2
Type: Research Article
ISSN: 1757-5818

Keywords

Abstract

Details

Understanding Intercultural Interaction: An Analysis of Key Concepts, 2nd Edition
Type: Book
ISBN: 978-1-83753-438-8

Article
Publication date: 21 March 2024

Thamaraiselvan Natarajan, P. Pragha, Krantiraditya Dhalmahapatra and Deepak Ramanan Veera Raghavan

The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and…

Abstract

Purpose

The metaverse, which is now revolutionizing how brands strategize their business needs, necessitates understanding individual opinions. Sentiment analysis deciphers emotions and uncovers a deeper understanding of user opinions and trends within this digital realm. Further, sentiments signify the underlying factor that triggers one’s intent to use technology like the metaverse. Positive sentiments often correlate with positive user experiences, while negative sentiments may signify issues or frustrations. Brands may consider these sentiments and implement them on their metaverse platforms for a seamless user experience.

Design/methodology/approach

The current study adopts machine learning sentiment analysis techniques using Support Vector Machine, Doc2Vec, RNN, and CNN to explore the sentiment of individuals toward metaverse in a user-generated context. The topics were discovered using the topic modeling method, and sentiment analysis was performed subsequently.

Findings

The results revealed that the users had a positive notion about the experience and orientation of the metaverse while having a negative attitude towards the economy, data, and cyber security. The accuracy of each model has been analyzed, and it has been concluded that CNN provides better accuracy on an average of 89% compared to the other models.

Research limitations/implications

Analyzing sentiment can reveal how the general public perceives the metaverse. Positive sentiment may suggest enthusiasm and readiness for adoption, while negative sentiment might indicate skepticism or concerns. Given the positive user notions about the metaverse’s experience and orientation, developers should continue to focus on creating innovative and immersive virtual environments. At the same time, users' concerns about data, cybersecurity and the economy are critical. The negative attitude toward the metaverse’s economy suggests a need for innovation in economic models within the metaverse. Also, developers and platform operators should prioritize robust data security measures. Implementing strong encryption and two-factor authentication and educating users about cybersecurity best practices can address these concerns and enhance user trust.

Social implications

In terms of societal dynamics, the metaverse could revolutionize communication and relationships by altering traditional notions of proximity and the presence of its users. Further, virtual economies might emerge, with virtual assets having real-world value, presenting both opportunities and challenges for industries and regulators.

Originality/value

The current study contributes to research as it is the first of its kind to explore the sentiments of individuals toward the metaverse using deep learning techniques and evaluate the accuracy of these models.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Open Access
Article
Publication date: 11 January 2024

Bartosz Niedzielski, Piotr Buła and Mengxi Yang

Hyperautomation is a technological concept whose popularity has been growing continuously since the German manufacturing industry “initiated” the Fourth Industrial Revolution…

Abstract

Purpose

Hyperautomation is a technological concept whose popularity has been growing continuously since the German manufacturing industry “initiated” the Fourth Industrial Revolution (Industry 4.0), whereas, on the basis of theory, hyperautomation is a term still new and little recognized. This applies equally to scientific studies (articles, conference reports) and empirical studies (quantitative, qualitative). Therefore, this article attempts to fill definition gap that exists in the literature on management and quality sciences on the term hyperautomation.

Design/methodology/approach

The authors use literature review approach to identify the gaps in the existing literature on hyperautomation. They present a nominal definition of hyperautomation, discuss related issues and provide a comparative perspective between hyperautomation and automation.

Findings

The article’s findings include a precise definition of hyperautomation and the problems it raises. The authors point out that the term “hyperautomation” is still relatively new and underutilized in the management and quality sciences literature. It also compares hyperautomation to automation from several angles and emphasizes how it affects businesses, industries and other economic sectors.

Practical implications

Authors emphasize that in order to deploy hyperautomation successfully, enterprises must take a distributed and integrated approach.

Originality/value

This article addresses a gap in the management and quality sciences literature about the definition of hyperautomation. Authors give a thorough explanation of hyperautomation, along with relevant problems, useful implications and a comparison between hyperautomation versus automation.

Details

Journal of Electronic Business & Digital Economics, vol. 3 no. 1
Type: Research Article
ISSN: 2754-4214

Keywords

Article
Publication date: 22 January 2024

Jun Liu, Junyuan Dong, Mingming Hu and Xu Lu

Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic…

Abstract

Purpose

Existing Simultaneous Localization and Mapping (SLAM) algorithms have been relatively well developed. However, when in complex dynamic environments, the movement of the dynamic points on the dynamic objects in the image in the mapping can have an impact on the observation of the system, and thus there will be biases and errors in the position estimation and the creation of map points. The aim of this paper is to achieve more accurate accuracy in SLAM algorithms compared to traditional methods through semantic approaches.

Design/methodology/approach

In this paper, the semantic segmentation of dynamic objects is realized based on U-Net semantic segmentation network, followed by motion consistency detection through motion detection method to determine whether the segmented objects are moving in the current scene or not, and combined with the motion compensation method to eliminate dynamic points and compensate for the current local image, so as to make the system robust.

Findings

Experiments comparing the effect of detecting dynamic points and removing outliers are conducted on a dynamic data set of Technische Universität München, and the results show that the absolute trajectory accuracy of this paper's method is significantly improved compared with ORB-SLAM3 and DS-SLAM.

Originality/value

In this paper, in the semantic segmentation network part, the segmentation mask is combined with the method of dynamic point detection, elimination and compensation, which reduces the influence of dynamic objects, thus effectively improving the accuracy of localization in dynamic environments.

Details

Industrial Robot: the international journal of robotics research and application, vol. 51 no. 2
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 26 January 2024

Yuanzhang Yang, Linqin Wang, Shengxiang Gao, Zhengtao Yu and Ling Dong

This paper aims to disentangle Chinese-English-rich resources linguistic and speaker timbre features, achieving cross-lingual speaker transfer for Cambodian.

Abstract

Purpose

This paper aims to disentangle Chinese-English-rich resources linguistic and speaker timbre features, achieving cross-lingual speaker transfer for Cambodian.

Design/methodology/approach

This study introduces a novel approach: the construction of a cross-lingual feature disentangler coupled with the integration of time-frequency attention adaptive normalization to proficiently convert Cambodian speaker timbre into Chinese-English without altering the underlying Cambodian speech content.

Findings

Considering the limited availability of multi-speaker corpora in Cambodia, conventional methods have demonstrated subpar performance in Cambodian speaker voice transfer.

Originality/value

The originality of this study lies in the effectiveness of the disentanglement process and precise control over speaker timbre feature transfer.

Details

International Journal of Web Information Systems, vol. 20 no. 2
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 3 October 2023

Anna Sokolova, Polina Lobanova and Ilya Kuzminov

The purpose of the paper is to present an integrated methodology for identifying trends in a particular subject area based on a combination of advanced text mining and expert…

Abstract

Purpose

The purpose of the paper is to present an integrated methodology for identifying trends in a particular subject area based on a combination of advanced text mining and expert methods. The authors aim to test it in an area of clinical psychology and psychotherapy in 2010–2019.

Design/methodology/approach

The authors demonstrate the way of applying text-mining and the Word2Vec model to identify hot topics (HT) and emerging trends (ET) in clinical psychology and psychotherapy. The analysis of 11.3 million scientific publications in the Microsoft Academic Graph database revealed the most rapidly growing clinical psychology and psychotherapy terms – those with the largest increase in the number of publications reflecting real or potential trends.

Findings

The proposed approach allows one to identify HT and ET for the six thematic clusters related to mental disorders, symptoms, pharmacology, psychotherapy, treatment techniques and important psychological skills.

Practical implications

The developed methodology allows one to see the broad picture of the most dynamic research areas in the field of clinical psychology and psychotherapy in 2010–2019. For clinicians, who are often overwhelmed by practical work, this map of the current research can help identify the areas worthy of further attention to improve the effectiveness of their clinical work. This methodology might be applied for the identification of trends in any other subject area by taking into account its specificity.

Originality/value

The paper demonstrates the value of the advanced text-mining approach for understanding trends in a subject area. To the best of the authors’ knowledge, for the first time, text-mining and the Word2Vec model have been applied to identifying trends in the field of clinical psychology and psychotherapy.

Details

foresight, vol. 26 no. 1
Type: Research Article
ISSN: 1463-6689

Keywords

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