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Article
Publication date: 19 January 2024

Ping Huang, Haitao Ding, Hong Chen, Jianwei Zhang and Zhenjia Sun

The growing availability of naturalistic driving datasets (NDDs) presents a valuable opportunity to develop various models for autonomous driving. However, while current NDDs…

Abstract

Purpose

The growing availability of naturalistic driving datasets (NDDs) presents a valuable opportunity to develop various models for autonomous driving. However, while current NDDs include data on vehicles with and without intended driving behavior changes, they do not explicitly demonstrate a type of data on vehicles that intend to change their driving behavior but do not execute the behaviors because of safety, efficiency, or other factors. This missing data is essential for autonomous driving decisions. This study aims to extract the driving data with implicit intentions to support the development of decision-making models.

Design/methodology/approach

According to Bayesian inference, drivers who have the same intended changes likely share similar influencing factors and states. Building on this principle, this study proposes an approach to extract data on vehicles that intended to execute specific behaviors but failed to do so. This is achieved by computing driving similarities between the candidate vehicles and benchmark vehicles with incorporation of the standard similarity metrics, which takes into account information on the surrounding vehicles' location topology and individual vehicle motion states. By doing so, the method enables a more comprehensive analysis of driving behavior and intention.

Findings

The proposed method is verified on the Next Generation SIMulation dataset (NGSim), which confirms its ability to reveal similarities between vehicles executing similar behaviors during the decision-making process in nature. The approach is also validated using simulated data, achieving an accuracy of 96.3 per cent in recognizing vehicles with specific driving behavior intentions that are not executed.

Originality/value

This study provides an innovative approach to extract driving data with implicit intentions and offers strong support to develop data-driven decision-making models for autonomous driving. With the support of this approach, the development of autonomous vehicles can capture more real driving experience from human drivers moving towards a safer and more efficient future.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 26 February 2024

Nicola Martino, Lorenzo Ardito, Antonio Messeni Petruzzelli and Daniele Rotolo

This paper aims to map the evolution of hydrogen-based technologies (HBTs) by examining the patenting activity associated to these technlogies from 1930 to 2020. In doing so, the…

Abstract

Purpose

This paper aims to map the evolution of hydrogen-based technologies (HBTs) by examining the patenting activity associated to these technlogies from 1930 to 2020. In doing so, the study provides a novel perspective on the development of HBTs and offers implications for managers and policymakers.

Design/methodology/approach

We collected patent data at the level of patent families (PFs). Our sample includes 317,089 PFs related to hydrogen production and 62,496 PFs to hydrogen storage. We examined PF data to delineate the state of the art and major technical advancements of HBTs.

Findings

Our analysis provides evidence of an increasing patenting activity in the area of HBTs, hence suggesting relatively high levels of expectations on the economic potential of these technologies. US and Japan hold the largest proportion of PFs related to HBTs (about 60%), while European applicants hold the highest proportion of highly cited PFs (about 60%). While firms represent the applicant with the highest share of PFs, our analysis reveals that firms holding HBT PFs are primarily from the chemical sector.

Research limitations/implications

While our analysis is limited to examining patent data which capture some aspects of the innovation activity around HBTs (namelly, patented inventions), our study enriches existing literature by performinng a patent analysis on a much larger sample of data when compared to previous studies.

Practical implications

Two main implications emerge from our study. Firstly, there seems to be an urgent need to support the emergence of a dominant design so as to facilitate the consolidation and diffusion of the HBTs, hence the transition to a more sustainable energy production. Secondly, the majority of HBT PFs are held by a small number of countries. This, in turn, suggests opportunities to develop cross-country cooperation (e.g. international agreements, research and technology offices) to support the development and adoption of HBTs globally.

Social implications

Considering the results obtained in this study, from a social point of view, the attention that organizations have paid to hydrogen related technologies is evident. This suggests that the development HBTs can function as a social enabler for a sustianable energy transition.

Originality/value

Extant research has focused on the individual components of the hydrogen chain. As a result, we lack a comprehensive understanding of the progress made in the area of HBTs. To address this gap, this study examined HBTs by focusing on both production and storage technologies since their initial developments, hence adopting an observation period of about 70 years.

Details

EuroMed Journal of Business, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1450-2194

Keywords

Article
Publication date: 21 August 2023

Gleb Glukhov, Ivan Derevitskii, Oksana Severiukhina and Klavdiya Bochenina

Using the data set about the restaurants from different countries and their customer's feedback, the purpose of this paper is to address the following issues: in the restaurant…

Abstract

Purpose

Using the data set about the restaurants from different countries and their customer's feedback, the purpose of this paper is to address the following issues: in the restaurant industry, how have user behavior and preferences changed during the COVID-19 restrictions period, how did these changes influence the performance of recommendation algorithms and which methods can be proposed to improve the quality of restaurant recommendations in a lockdown scenario.

Design/methodology/approach

To assess changes in user behavior and preferences, quantitative and qualitative data analysis was performed to assess the changes in user behavior and preferences. The authors compared the situation before and during the COVID-19 restrictions period. To evaluate the performance of restaurant recommendation systems in a non-stationary setting, the authors tested state-of-the-art collaborative filtering algorithms. This study proposes and investigates a filtering-based approach to improve the quality of recommendation algorithms for a lockdown scenario.

Findings

This study revealed that during the COVID-19 restrictions period, the average rating values and the number of reviews have changed. The experimental study confirmed that: the performance of all state-of-the-art recommender systems for the restaurant industry has significantly degraded during the COVID-19 restrictions period; and the accuracy and the stability of restaurant recommendations in non-stationary settings may be improved using the sliding window and post-filtering methods.

Practical implications

The authors propose two novel methods: the sliding window and closed restaurants post-filtering method based on the CatBoost classification model. These methods can be applied to classical collaborative recommender algorithms and increase the value of metrics under non-stationary conditions. These methods can be helpful for developers of recommender systems and massive aggregators of restaurants and hotels. Thus, it benefits both the app end-user and business owners because users honestly rate restaurants when they receive good recommendations and do not downgrade because of external factors.

Originality/value

To the best of the authors’ knowledge, this paper provides the first extensive and multifaceted experimental study of the impact of COVID-19 restrictions on the effectiveness of restaurant recommendation systems in different countries. Two novel methods to tackle restaurant recommendations' performance degradation are proposed and validated.

研究目的

利用关于不同国家餐厅及其顾客反馈的数据, 我们探索了以下问题:(i) 在餐饮行业, 用户行为和偏好在COVID-19限制期间如何改变, (ii) 这些变化如何影响推荐算法的性能, 以及 (iii) 可以提出哪些方法来改进封锁情景下的餐厅推荐质量。

研究方法

为了评估用户行为和偏好的变化, 本研究进行了定量和定性数据分析, 对比了COVID-19限制期前后的情况。为了评估非稳态环境中餐厅推荐系统的性能, 我们测试了最先进的协同过滤算法。我们提出并研究了一种基于过滤的方法, 以提高封锁情景下推荐算法的质量。

研究发现

研究发现, 在COVID-19限制期间, 平均评分和评论数量发生了变化。实验研究证实:(i) 在COVID-19限制期间, 所有最先进的餐厅行业推荐系统的性能显著下降; (ii) 使用滑动窗口和后过滤方法可以改进非稳态环境下餐厅推荐的准确性和稳定性。

实践意义

我们提出了两种新方法:基于CatBoost分类模型的关闭餐厅后过滤和滑动窗口方法。这些方法可以应用于经典的协同过滤推荐算法, 并在非稳态条件下提高指标值。这些方法对于推荐系统的开发者和大规模餐厅和酒店聚合平台都有帮助。因此, 这对于应用的最终用户和企业主都有好处, 因为当用户得到良好的推荐时, 他们会诚实地对餐厅进行评价, 而不会因为外部因素降低评分。

研究创新

本文首次提供了COVID-19限制对不同国家餐厅推荐系统有效性影响的广泛多方面的实验研究, 并提出和验证了两种解决餐厅推荐性能下降问题的新方法。

Article
Publication date: 10 January 2024

Jaime García-Rayado and Chesney Callens

This research analyzes the roles of users in innovative digital health collaborative projects from the perspective of the user by considering three dimensions: their motivation…

Abstract

Purpose

This research analyzes the roles of users in innovative digital health collaborative projects from the perspective of the user by considering three dimensions: their motivation, project activities and the support of the partnership for their effective involvement.

Design/methodology/approach

The authors unraveled profiles of users by using a Q-methodological analysis of 24 statements and 44 service users. The statements for the three dimensions were designed according to previous models of stakeholder identification and customer participation in new product management.

Findings

The authors obtained two profiles that advocate active participation of users, though with a different degree of involvement. One of them supports the role of users as “advisors” of users' preferences and needs, and the other indicates a higher involvement of users as “cocreators” of the innovation, with the same contribution and responsibility as the other partners.

Originality/value

Previous research has analyzed user involvement in digital health, as part of wider research on factors leading to the success and adoption of innovations. Moreover, previous research has analyzed user involvement in innovation projects, but without differentiating between projects carried out by an individual organization and those conducted by a partnership. This research contributes to filling this gap by revealing users' expectations about their involvement and how they think they will fit in with the dynamics of collaborative projects.

Details

Journal of Health Organization and Management, vol. 38 no. 1
Type: Research Article
ISSN: 1477-7266

Keywords

Article
Publication date: 6 February 2024

Lin Xue and Feng Zhang

With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web…

Abstract

Purpose

With the increasing number of Web services, correct and efficient classification of Web services is crucial to improve the efficiency of service discovery. However, existing Web service classification approaches ignore the class overlap in Web services, resulting in poor accuracy of classification in practice. This paper aims to provide an approach to address this issue.

Design/methodology/approach

This paper proposes a label confusion and priori correction-based Web service classification approach. First, functional semantic representations of Web services descriptions are obtained based on BERT. Then, the ability of the model is enhanced to recognize and classify overlapping instances by using label confusion learning techniques; Finally, the predictive results are corrected based on the label prior distribution to further improve service classification effectiveness.

Findings

Experiments based on the ProgrammableWeb data set show that the proposed model demonstrates 4.3%, 3.2% and 1% improvement in Macro-F1 value compared to the ServeNet-BERT, BERT-DPCNN and CARL-NET, respectively.

Originality/value

This paper proposes a Web service classification approach for the overlapping categories of Web services and improve the accuracy of Web services classification.

Details

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

Keywords

Article
Publication date: 22 February 2024

Wenhao Zhou and Hailin Li

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough…

Abstract

Purpose

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Design/methodology/approach

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

Findings

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Originality/value

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.

Details

European Journal of Innovation Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1460-1060

Keywords

Book part
Publication date: 28 March 2024

Lucia Mesquita, Gabriela Gruszynski Sanseverino, Mathias-Felipe de-Lima-Santos and Giuliander Carpes

This study examines three significant collaborative journalism projects in the Americas: The Panama Papers, from the United States-based International Consortium of Investigative…

Abstract

This study examines three significant collaborative journalism projects in the Americas: The Panama Papers, from the United States-based International Consortium of Investigative Journalists (ICIJ); “América Latina, Región de Carteles,” by Colombian-based Connectas; and the first phase of the Brazilian-based project, Comprova, supported by Brazilian Association of Investigative Journalists (Abraji) and First Draft. The work investigates what encompasses collaborative journalism; and explores whether it is a recent phenomenon of the news ecosystem, a consequence of the institutional crisis of journalism, and if it is influenced by a network-based and platformed society. A mixed-method approach is applied in a three-stage analysis: (1) desk research; (2) quantitative content analysis; and (3) qualitative semi-structured in-depth interviews. To gain a broader picture of the organizations and their respective projects, documental and bibliographical research was carried out with a focus on data from press releases, corporate reports, and articles published on the websites of the organizations coordinating the projects. Furthermore, a quantitative content analysis of 10 news articles published by each of these collaboration partnerships was completed. Finally, qualitative semi-structured in-depth interviews were conducted with the directors, managers, and professional journalists’ part of the organizations and project. This study emphasizes the importance of collaborative practices, demonstrates how collaborative practices contribute to a new modus operandi of the news ecosystem; and considers why journalists and media organizations have turned to collaborative journalism as a model of production, circulation, and distribution of journalistic investigations.

Article
Publication date: 18 January 2024

Jin Xu, Pei Hua Shi and Xi Chen

This study aims to unveil the pivotal components and implementation pathways in the digital innovation of smart tourism destinations, while constructing a theoretical framework…

Abstract

Purpose

This study aims to unveil the pivotal components and implementation pathways in the digital innovation of smart tourism destinations, while constructing a theoretical framework from a holistic perspective.

Design/methodology/approach

The research focuses on 31 significant urban smart tourism destinations in China. Secondary data was collected through manual search supplemented by big data scraping, whereas primary data was obtained from interviews with municipal tourism authorities. Grounded theory was used to theoretically construct the phenomenon of digital innovation in smart tourism destinations.

Findings

This research has formulated a data-driven knowledge framework for digital innovation in smart tourism destinations. Core components include digital organizational innovation, smart data platforms, multi-stakeholder digital collaborative ecosystem and smart tourism scenario systems. Destinations can achieve smart tourism scene innovation through closed innovation driven by smart data platforms or open innovation propelled by a multi-stakeholder digital collaborative ecosystem.

Practical implications

Based on insights from digital innovation practices, this study proposes a series of concrete recommendations aimed at assisting Destination Management Organizations in formulating and implementing more effective digital innovation strategies to enhance the sustainable digital competitiveness of destinations.

Originality/value

This study advances smart tourism destination innovation research from localized thinking to systemic thinking; extends digital innovation theory into the realm of smart tourism destination innovation; repositions the significance of knowledge in smart tourism destination innovation; and constructs a comprehensive framework for digital innovation in smart tourism destinations.

目的

本研究致力于揭示智能旅游目的地数字创新中的核心组件及实施路径, 并创建一个整体视角下的理论框架。

设计/方法/方法

研究选定中国31座重要城市型智能旅游目的地为研究对象。通过人工检索结合大数据抓取的方式收集二手资料, 以各市旅游主管部门为访谈对象收集一手资料。运用扎根理论对智能旅游目的地的数字创新现象进行理论构建。

发现

本研究构建了一个数据型知识驱动的智能旅游目的地数字创新框架。其中, 核心组件包括数字组织创新、智慧数据平台、多主体数字协同生态和智慧旅游场景体系。目的地可通过智慧数据平台驱动的内生型创新或多主体数字协同生态推动的开放式创新, 实现智能旅游场景创新。

原创性/价值

本研究将智能旅游目的地创新相关研究由局部思考推向系统思考; 将数字创新理论扩展到智能旅游目的地创新的研究中; 重新定位知识在智能旅游目的地创新中的重要地位; 以及构建了一个智能旅游目的地数字创新整体框架。

实践意义

本研究基于数字创新实践洞察, 提出了一系列具体建议。旨在帮助目的地管理组织更有效地制定和实施数字创新策略, 以增强旅游目的地可持竞争力。

Diseño/metodología/enfoque

La investigación se centra en 31 destacados destinos turísticos urbanos inteligentes de China. Los datos secundarios se recopilaron mediante una búsqueda manual complementada con técnicas de big data, mientras que los datos primarios se obtuvieron a partir de entrevistas con las autoridades turísticas municipales. Se empleó la teoría fundamentada para construir teóricamente el fenómeno de la innovación digital en los destinos turísticos inteligentes.

Objetivo

Esta investigación tiene como objetivo identificar los componentes esenciales y las rutas de implementación de la innovación digital en destinos turísticos inteligentes, y construir un marco teórico desde una perspectiva holística.

Resultados

Este estudio ha desarrollado un marco de conocimiento basado en datos para la innovación digital en destinos turísticos inteligentes. Los componentes centrales incluyen la innovación organizativa digital, la plataforma de datos inteligentes, el ecosistema digital colaborativo de múltiples actores y el sistema de escenarios turísticos inteligentes. Además, tanto la innovación endógena impulsada por la plataforma de datos inteligentes como la innovación abierta impulsada por el ecosistema digital colaborativo de múltiples actores contribuyen a la innovación por escenarios en destinos turísticos inteligentes.

Implicaciones prácticas

A partir de las prácticas de innovación digital, este estudio ofrece una serie de recomendaciones dirigidas a las Organizaciones de Gestión de Destinos (DMOs) para la formulación e implementación de estrategias de innovación digital de manera más efectiva, y mejorar la competitividad digital sostenible de los destinos turísticos.

Originalidad/valor

Este estudio avanza la investigación sobre innovación en destinos turísticos inteligentes desde el pensamiento localizado hasta el pensamiento sistémico; extiende la teoría de la innovación digital al ámbito de la innovación en destinos turísticos inteligentes; reposiciona la importancia del conocimiento en la innovación de destinos turísticos inteligentes; y construye un marco integral para la innovación digital en destinos turísticos inteligentes.

Abstract

Details

Supervising Doctoral Candidates
Type: Book
ISBN: 978-1-83797-051-3

Open Access
Article
Publication date: 31 May 2022

Kari-Pekka Tampio and Harri Haapasalo

The purpose of this paper is to identify the areas and logic of integration of different stakeholders using different methods and to analyse their applicability and challenges in…

Abstract

Purpose

The purpose of this paper is to identify the areas and logic of integration of different stakeholders using different methods and to analyse their applicability and challenges in practical projects. The main aim is to describe how these different methods impact value creation.

Design/methodology/approach

Action design research was carried out in a large hospital construction project where the first author acted as an “involved researcher” and the second author acted as an “outside researcher”. Two workshops were organised to evaluate the direct and indirect challenges and benefits of the applied four methods and to explain how different methods enable value creation.

Findings

All the studied methods provide good results in terms of usability and commitment to the aims of the project, thus delivering the direct benefits expected. Process, people and tools logic works well in this case project when applying the methods properly. Significant evidence was provided on secondary deliverables of the methods, and all analysed methods had a significant impact in the area of leading people, clarifying what “focus on people” means and how it is enabled.

Practical implications

Focus on people can be achieved through different operative methods if applied in the right way. It is necessary to select the most suitable methods based on all the direct and indirect deliverables.

Originality/value

This case project offered a platform to analyse integration methods in a real-life project using the collaborative contract method. The authors were able to participate in the analysis by taking action from the very beginning of the project in terms of training, learning, continuous development and coaching of these methods and evaluating the applicability.

Details

Construction Innovation , vol. 24 no. 7
Type: Research Article
ISSN: 1471-4175

Keywords

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