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1 – 10 of 52Christophe Gaie, Bertrand Florat and Steven Morvan
In the present article, the authors tackle the problem of IT documentation, which plays an important role in information technology (IT) project management.
Abstract
Purpose
In the present article, the authors tackle the problem of IT documentation, which plays an important role in information technology (IT) project management.
Design/methodology/approach
They provide a simple tool based on five complementary views, which should be detailed by the project team using a classic source code management platform.
Findings
The proposed tool is open source and may be reused by any IT team in various project contexts and heterogeneous development methods.
Originality/value
This research provides an operational framework, which facilitates IT project management and documentation. The framework is open source and may be easily downloaded by any other IT team.
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Sarah Schönherr, Robert Eller, Andreas Kallmuenzer and Mike Peters
Organisational learning drives tourism organisations towards more sustainable tourism. Digital transformation also provides opportunities for sustainable tourism development. This…
Abstract
Purpose
Organisational learning drives tourism organisations towards more sustainable tourism. Digital transformation also provides opportunities for sustainable tourism development. This study aims to combine these perspectives and explore how digital transformation enables organisational learning to contribute to sustainable tourism, following organisational learning theory (OLT).
Design/methodology/approach
Based on a critical realist paradigm, this study focuses on developing an in-depth understanding of organisational learning in tourism organisations. Thirty qualitative interviews with tourism organisations participating in an executive development programme (EDP) show how tourism organisations create, retain and transfer knowledge.
Findings
This study demonstrates that the EDP initiates knowledge creation through content transmission and exchange, triggers knowledge retention through utilisation of digital technologies and reinforces digitalisation through data value creation. Furthermore, this study enables knowledge transformation as implementation, which contributes to the three pillars of sustainable tourism and facilitates the development of networks encouraging sustainable tourism.
Originality/value
This study identifies approaches that enable economic, social and environmentally sustainable tourism development by facilitating collaborations via digital transformation, digital technologies that guide guest streams, online mobility offers and online environmental awareness campaigns that reduce environmental impacts. Thus, this study strengthens OLT and has implications for organisational learning and tourism policymakers.
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Elena Barbierato, Iacopo Bernetti and Irene Capecchi
Wine packaged tours as a specific aspect of wine tourism have so far been neglected in research, for this reason, the purpose of this study is to study the key elements for the…
Abstract
Purpose
Wine packaged tours as a specific aspect of wine tourism have so far been neglected in research, for this reason, the purpose of this study is to study the key elements for the success of the wine tour in Tuscany (Italy), evaluating the points of strength and weakness.
Design/methodology/approach
The study combines approaches of text mining, sentiment analysis and natural language processing, drawing on data from the TripAdvisor platform, obtaining through an automatic procedure 9,616 reviews from 600 tours in the years 2010–2020.
Findings
The authors identified six elements of successful wine tours expressed by research subjects: tour guide; logistical aspects; the quality of the wine; the quality of the food; complementary tourist and recreational activities; the landscape and historic villages. The key strength associated with success was the integration of the leading wine product with food, landscape and historic villages, while the main criticisms were concerned with the organization and planning of the tour. Furthermore, the tour guide also plays a fundamental role in consumer satisfaction.
Research limitations/implications
The limitations of the method were linked to the origin of the data used. The main one is that TripAdvisor does not allow you to have social and personal information about the tourist who wrote the review; therefore, the methods are substantially complementary to the traditional survey through questionnaires.
Practical implications
The proposed model can be used both by professionals to improve the quality of their products and by policymakers to promote the territorial development of quality wine-growing areas.
Social implications
The proposed model can be useful for policymakers to promote the territorial development of quality wine-growing areas.
Originality/value
The methodology we tested is easily transferable to many countries and to the authors’ knowledge, for the first time attempts to combine multidimensional scaling, sentiment analysis and natural language processing approaches.
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Giuseppe Grossi, Paolo Pietro Biancone, Silvana Secinaro and Valerio Brescia
The purpose of this study is to explore the usefulness of popular reporting (PR) in an Italian city as a dialogic accounting tool for promoting citizens’ engagement with digital…
Abstract
Purpose
The purpose of this study is to explore the usefulness of popular reporting (PR) in an Italian city as a dialogic accounting tool for promoting citizens’ engagement with digital platforms. This study aims to contribute to the debate on democratic accounting technologies with a focus on PR and digital platforms, using the theoretical lens of dialogic accounting.
Design/methodology/approach
A longitudinal case study is used to analyse the implementation and evolution of PR in the city of Turin, Italy and explore how the city involved its citizens with digital platforms.
Findings
This study contributes to the debate on public accountability through dialogic accounting tools.
Research limitations/implications
Multiple sources (surveys, interviews and interventionist workshops) are used to analyse Turin, Italy as a longitudinal case study.
Practical implications
This study offers practical reflections for legislators, politicians and public managers who need new knowledge and empirical analysis of the effective implementation of the PR as a tool for dialogue and empowering public accounting to hold continuous dialogue with the citizens.
Originality/value
PR can be considered a useful dialogic accounting tool for politicians, managers and government experts to encourage citizens’ engagement in a pluralistic society.
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Lichao Zhu, Hangzhou Yang and Zhijun Yan
The purpose of this paper is to develop a new method to extract medical temporal information from online health communities.
Abstract
Purpose
The purpose of this paper is to develop a new method to extract medical temporal information from online health communities.
Design/methodology/approach
The authors trained a conditional random-filed model for the extraction of temporal expressions. The temporal relation identification is considered as a classification task and several support vector machine classifiers are built in the proposed method. For the model training, the authors extracted some high-level semantic features including co-reference relationship of medical concepts and the semantic similarity among words.
Findings
For the extraction of TIMEX, the authors find that well-formatted expressions are easy to recognize, and the main challenge is the relative TIMEX such as “three days after onset”. It also shows the same difficulty for normalization of absolute date or well-formatted duration, whereas frequency is easier to be normalized. For the identification of DocTimeRel, the result is fairly well, and the relation is difficult to identify when it involves a relative TIMEX or a hypothetical concept.
Originality/value
The authors proposed a new method to extract temporal information from the online clinical data and evaluated the usefulness of different level of syntactic features in this task.
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Sofia Baroncini, Bruno Sartini, Marieke Van Erp, Francesca Tomasi and Aldo Gangemi
In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides…
Abstract
Purpose
In the last few years, the size of Linked Open Data (LOD) describing artworks, in general or domain-specific Knowledge Graphs (KGs), is gradually increasing. This provides (art-)historians and Cultural Heritage professionals with a wealth of information to explore. Specifically, structured data about iconographical and iconological (icon) aspects, i.e. information about the subjects, concepts and meanings of artworks, are extremely valuable for the state-of-the-art of computational tools, e.g. content recognition through computer vision. Nevertheless, a data quality evaluation for art domains, fundamental for data reuse, is still missing. The purpose of this study is filling this gap with an overview of art-historical data quality in current KGs with a focus on the icon aspects.
Design/methodology/approach
This study’s analyses are based on established KG evaluation methodologies, adapted to the domain by addressing requirements from art historians’ theories. The authors first select several KGs according to Semantic Web principles. Then, the authors evaluate (1) their structures’ suitability to describe icon information through quantitative and qualitative assessment and (2) their content, qualitatively assessed in terms of correctness and completeness.
Findings
This study’s results reveal several issues on the current expression of icon information in KGs. The content evaluation shows that these domain-specific statements are generally correct but often not complete. The incompleteness is confirmed by the structure evaluation, which highlights the unsuitability of the KG schemas to describe icon information with the required granularity.
Originality/value
The main contribution of this work is an overview of the actual landscape of the icon information expressed in LOD. Therefore, it is valuable to cultural institutions by providing them a first domain-specific data quality evaluation. Since this study’s results suggest that the selected domain information is underrepresented in Semantic Web datasets, the authors highlight the need for the creation and fostering of such information to provide a more thorough art-historical dimension to LOD.
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Soheila Bahrami and Davood Zeinali
This paper explores the quality and flow of facade product information and the capabilities for avoiding the risk of facade fires early in the design process.
Abstract
Purpose
This paper explores the quality and flow of facade product information and the capabilities for avoiding the risk of facade fires early in the design process.
Design/methodology/approach
A qualitative case study using the process tracing method is conducted in two stages. First, a thematic analysis of reports and literature identified two categories for the problems that caused fast fire spread across the Grenfell Tower facade. This enabled classifying the identified problems into four stages of a facade life cycle: product design and manufacturing, procurement, facade design and construction. Second, the capabilities for avoiding the problems were explored by conducting in-depth interviews with 18 experts in nine countries, analyzing design processes and designers' expertise and examining the usability of three digital interfaces in providing required information for designing fire-safe facades.
Findings
The results show fundamental flaws in the quality of facade product information and usability of digital interfaces concerning fire safety. These flaws, fragmented design processes and overreliance on other specialists increase the risk of design defects that cause fast fire spread across facades.
Practical implications
The findings have implications for standardization of building product information, digitalization in industrialized construction and facade design management.
Originality/value
This research adds to the body of knowledge on sustainability in the built environment. It is the first study to highlight the fundamental problem of facade product information, which requires urgent attention in the rapid transition toward digital and industrialized construction.
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This paper purposed a multi-facet sentiment analysis system.
Abstract
Purpose
This paper purposed a multi-facet sentiment analysis system.
Design/methodology/approach
Hence, This paper uses multidomain resources to build a sentiment analysis system. The manual lexicon based features that are extracted from the resources are fed into a machine learning classifier to compare their performance afterward. The manual lexicon is replaced with a custom BOW to deal with its time consuming construction. To help the system run faster and make the model interpretable, this will be performed by employing different existing and custom approaches such as term occurrence, information gain, principal component analysis, semantic clustering, and POS tagging filters.
Findings
The proposed system featured by lexicon extraction automation and characteristics size optimization proved its efficiency when applied to multidomain and benchmark datasets by reaching 93.59% accuracy which makes it competitive to the state-of-the-art systems.
Originality/value
The construction of a custom BOW. Optimizing features based on existing and custom feature selection and clustering approaches.
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Luca Rampini and Fulvio Re Cecconi
This study aims to introduce a new methodology for generating synthetic images for facility management purposes. The method starts by leveraging the existing 3D open-source BIM…
Abstract
Purpose
This study aims to introduce a new methodology for generating synthetic images for facility management purposes. The method starts by leveraging the existing 3D open-source BIM models and using them inside a graphic engine to produce a photorealistic representation of indoor spaces enriched with facility-related objects. The virtual environment creates several images by changing lighting conditions, camera poses or material. Moreover, the created images are labeled and ready to be trained in the model.
Design/methodology/approach
This paper focuses on the challenges characterizing object detection models to enrich digital twins with facility management-related information. The automatic detection of small objects, such as sockets, power plugs, etc., requires big, labeled data sets that are costly and time-consuming to create. This study proposes a solution based on existing 3D BIM models to produce quick and automatically labeled synthetic images.
Findings
The paper presents a conceptual model for creating synthetic images to increase the performance in training object detection models for facility management. The results show that virtually generated images, rather than an alternative to real images, are a powerful tool for integrating existing data sets. In other words, while a base of real images is still needed, introducing synthetic images helps augment the model’s performance and robustness in covering different types of objects.
Originality/value
This study introduced the first pipeline for creating synthetic images for facility management. Moreover, this paper validates this pipeline by proposing a case study where the performance of object detection models trained on real data or a combination of real and synthetic images are compared.
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Linzi Wang, Qiudan Li, Jingjun David Xu and Minjie Yuan
Mining user-concerned actionable and interpretable hot topics will help management departments fully grasp the latest events and make timely decisions. Existing topic models…
Abstract
Purpose
Mining user-concerned actionable and interpretable hot topics will help management departments fully grasp the latest events and make timely decisions. Existing topic models primarily integrate word embedding and matrix decomposition, which only generates keyword-based hot topics with weak interpretability, making it difficult to meet the specific needs of users. Mining phrase-based hot topics with syntactic dependency structure have been proven to model structure information effectively. A key challenge lies in the effective integration of the above information into the hot topic mining process.
Design/methodology/approach
This paper proposes the nonnegative matrix factorization (NMF)-based hot topic mining method, semantics syntax-assisted hot topic model (SSAHM), which combines semantic association and syntactic dependency structure. First, a semantic–syntactic component association matrix is constructed. Then, the matrix is used as a constraint condition to be incorporated into the block coordinate descent (BCD)-based matrix decomposition process. Finally, a hot topic information-driven phrase extraction algorithm is applied to describe hot topics.
Findings
The efficacy of the developed model is demonstrated on two real-world datasets, and the effects of dependency structure information on different topics are compared. The qualitative examples further explain the application of the method in real scenarios.
Originality/value
Most prior research focuses on keyword-based hot topics. Thus, the literature is advanced by mining phrase-based hot topics with syntactic dependency structure, which can effectively analyze the semantics. The development of syntactic dependency structure considering the combination of word order and part-of-speech (POS) is a step forward as word order, and POS are only separately utilized in the prior literature. Ignoring this synergy may miss important information, such as grammatical structure coherence and logical relations between syntactic components.
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