Article
Hospitality, Leisure, Sport & Tourism
Marcello Mariani, Stefano Bresciani, Giovanni Battista Dagnino
Summary: This study aims to establish an integrated conceptual framework of tourism destination competitive productivity (TDCP) and explore the drivers of TDCP in the context of the ongoing 4th industrial revolution. By integrating existing research and empirical work, it reveals the crucial role of destination management information systems in helping destination managers effectively manage and market tourism destinations.
INTERNATIONAL JOURNAL OF CONTEMPORARY HOSPITALITY MANAGEMENT
(2021)
Article
Computer Science, Information Systems
Yanfang Niu, Limeng Ying, Jie Yang, Mengqi Bao, C. B. Sivaparthipan
Summary: Business intelligence helps organizations extract key information from a wide variety of unstructured data to improve decision-making and business efficiency. Challenges in business intelligence and decision-making include plan failure, lack of preparation, resource failure, and risk-taking capability.
INFORMATION PROCESSING & MANAGEMENT
(2021)
Article
Computer Science, Information Systems
Jie Yang, Pishi Xiu, Lipeng Sun, Limeng Ying, Blaanand Muthu
Summary: Social media analytics is a crucial method for making business decisions, providing insights into social consumers and facilitating effective decision-making. The Business Decision Making System (BDMS) has been proposed to utilize social media data analytics for business development, emphasizing key principles, issues, and functionality.
INFORMATION PROCESSING & MANAGEMENT
(2022)
Article
Business
Morten Brinch, Angappa Gunasekaran, Samuel Fosso Wamba
Summary: The study identified firm-level capabilities required to create value from big data, confirming the application of adjacent theories and uncovering unexplored capabilities in the realm of big data. This provides a holistic overview of the capabilities needed for big data value creation.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Urban Studies
Josep A. Ivars-Baidal, Marco A. Celdran-Bernabeu, Francisco Femenia-Serra, Jose F. Perles-Ribes, J. Fernando Vera-Rebollo
Summary: The impact of technology on tourist cities and destinations has led to the emergence of new management approaches aimed at adapting planning processes to challenges and opportunities of the smart scenario. However, little is known about the translation of these ideas into real policies and their impact. This paper aims to understand how the smart approach is being implemented in Spanish tourist cities and destinations and its implications for governance, sustainability, and data-driven public management.
Article
Business
Lei Li, Jiabao Lin, Ye Ouyang, Xin (Robert) Luo
Summary: Big data analytics usage has a positive impact on decision-making quality, with data analytics capabilities playing a mediating role in this relationship. Firms should promote the use of big data analytics and improve their data analytics capabilities to enhance decision-making quality and gain competitive advantages.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Green & Sustainable Science & Technology
Mercedes Raquel Garcia Revilla, Javier Perogil Burgos, Carmen Sarah Einsle, Olga Martinez Moure
Summary: This paper investigates the response of smart tourism destinations (STDs) to the COVID-19 crisis in terms of sustainability. It includes a literature review on tourism sustainability, a case study of several STDs, and the proposal of a strategy for destinations to follow in similar situations, aiming to avoid disorganization and uncertainty.
Article
Operations Research & Management Science
Honglei Zhang, Zhenbo Zang, Hongjun Zhu, Sunil Kumar Sharma, S. Sridhar
Summary: This paper introduces an Improved Data Analytics Model (IDAM) to enhance industrial decision-making and business development. Through data analytics, companies can predict customer behavior, improve decision-making, and evaluate the ROI of marketing activities, thus increasing operational efficiency, sales, and market share.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Economics
Jean-Louis Monino
Summary: With the integration of different technologies and the growing range of products, big data is a paradigm shift involving data analysis to extract patterns in hidden relationships. Companies now focus on utilizing high performance to efficiently analyze big data and find useful information rather than just launching new products. The challenges of the data revolution era highlight the importance of data usage and the rise of the intangible economy.
JOURNAL OF THE KNOWLEDGE ECONOMY
(2021)
Article
Computer Science, Information Systems
Stefan Lessmann, Johannes Haupt, Kristof Coussement, Koen W. De Bock
Summary: The study highlights the importance of targeting the right customer groups in marketing campaigns and proposes a profit-conscious ensemble selection modeling framework that integrates statistical learning principles with business objectives, contributing to the field of profit analytics.
INFORMATION SCIENCES
(2021)
Article
Management
Mengzhuo Guo, Qingpeng Zhang, Xiuwu Liao, Frank Youhua Chen, Daniel Dajun Zeng
Summary: Multiple criteria decision aiding (MCDA) is a family of analytic approaches used to explain human decision rationale, but the traditional methods sacrifice the ability to describe decision maker preferences due to model simplification. To enhance prediction performance and capture attribute relationships, NN-MCDA combines MCDA models and machine learning, using linear and nonlinear components to optimize correlations and predictions.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Business
Kasuni Weerasinghe, Shane L. Scahill, David J. Pauleen, Nazim Taskin
Summary: The ongoing discussion about the introduction and use of 'big data and analytics' in the global health sector is driven by the efforts of developed countries to improve healthcare value through data and technology. However, while there is recognition of the potential value of big data and analytics in clinical decision-making, the adoption of such technologies in clinical care remains relatively unexplored in New Zealand. Concerns over data quality and the need for engagement and participation at all levels to discuss data quality and implement big-data-based changes are highlighted in the findings, along with recommendations for policy and practice.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Hospitality, Leisure, Sport & Tourism
Abbie-Gayle Johnson, Jillian M. Rickly, Scott McCabe
Summary: Although the importance of diverse tourism stakeholders in smart destination development is acknowledged, local tourism supplier participation is still lacking. This study explores supplier perceptions on engagement with smart initiatives in Ljubljana, Slovenia. Findings revealed that relational influences and organizational factors played a role in supplier engagement. The study also highlights the importance of considering destination-specific context and cultural norms for successful engagement.
TOURISM MANAGEMENT PERSPECTIVES
(2023)
Article
Green & Sustainable Science & Technology
Josep A. Ivars-Baidal, J. Fernando Vera-Rebollo, Jose Perles-Ribes, Francisco Femenia-Serra, Marco A. Celdran-Bernabeu
Summary: This paper examines the relationship between smart cities and destinations and sustainable tourism indicators and evaluates the contribution of smart cities/destinations to sustainable tourism development. The study finds that despite efforts in smart cities and destinations, progress in sustainable tourism development has been slow. The research highlights the importance of strengthening public governance.
JOURNAL OF SUSTAINABLE TOURISM
(2023)
Article
Information Science & Library Science
Francesco Caputo, Barbara Keller, Michael Moehring, Luca Carrubbo, Rainer Schmidt
Summary: This paper aims to codify the main phases and challenges of approaching and managing big data analytics in companies' decision-making processes through case studies. It provides a possible depiction of the development stages and challenges of big data analytics and its impact on decision-making processes.
JOURNAL OF KNOWLEDGE MANAGEMENT
(2023)
Editorial Material
Engineering, Environmental
Davide Chiaroni, Pasquale Del Vecchio, David Peck, Andrea Urbinati, Demetris Vrontis
RESOURCES CONSERVATION AND RECYCLING
(2021)
Article
Computer Science, Information Systems
Piera Centobelli, Roberto Cerchione, Pasquale Del Vecchio, Eugenio Oropallo, Giustina Secundo
Summary: Trust, traceability, and transparency are critical factors in designing circular blockchain platforms in supply chains. This paper proposes the integrated Triple Retry framework for designing circular blockchain platforms to bridge the three circular supply chain reverse processes and the three factors affecting blockchain technologies. The results highlight the role of blockchain as a technological capability for improving control in waste transportation and product return management activities.
INFORMATION & MANAGEMENT
(2022)
Article
Business
Gianluca Solazzo, Ylenia Maruccia, Gianluca Lorenzo, Valentina Ndou, Pasquale Del Vecchio, Gianluca Elia
Summary: This paper explores how big social data (BSD) and analytics can assist destination management organizations (DMOs) in understanding tourist behaviors and destination images. By utilizing data from various sources like Flickr and Twitter, different analytics techniques are used to gain insights on tourist behavior and destination image. The results show that these insights can help DMOs in discovering new points of interest, identifying trends in tourist demand, monitoring sentiment, and enhancing destination attractiveness through new marketing strategies.
MEASURING BUSINESS EXCELLENCE
(2022)
Article
Business
Pasquale Del Vecchio, Andrea Urbinati, Julian Kirchherr
Summary: The concept of circular economy has gained attention in management research, especially in the agricultural sector. This article analyzes the enablers of managerial practices in a rural agro-energy company to understand the factors that contribute to the design of circular business models.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Business, Finance
Piera Centobelli, Roberto Cerchione, Pasquale Del Vecchio, Eugenio Oropallo, Giustina Secundo
Summary: This study presents a conceptual framework for blockchain-based accounting, which includes a technological infrastructure, permission and validation controls, and integration of business and security applications at different scalable levels.
ACCOUNTING AUDITING & ACCOUNTABILITY JOURNAL
(2022)
Review
Business
Pasquale Del Vecchio, Gioconda Mele, Evangelia Siachou, Gloria Schito
Summary: This study advances the international marketing debate by examining the implementation of Big Data in CRM strategies through a structured literature review. It provides a conceptual framework and identifies specialized areas of focus emerging from the literature. The research findings offer important insights for the development of future research agenda in international marketing.
INTERNATIONAL MARKETING REVIEW
(2022)
Article
Business
Gianluca Solazzo, Ylenia Maruccia, Valentina Ndou, Pasquale Del Vecchio
Summary: This paper discusses how Smart Tourism Destination can utilize smart and digital technologies to tackle the impact of the Covid-19 pandemic, providing valuable insights through the use of Big Data and Analytics.
Review
Information Science & Library Science
Pasquale Del Vecchio, Gioconda Mele, Giuseppina Passiante, Donata Serra
Summary: This study provides a systematic review of the literature on the use of Big Data in the process of New Product Development (NPD) by analyzing articles published from 2015 to 2021. The findings reveal a lack of research in this field and fragmentation of publications, indicating the need for further investigation. The analysis identifies emerging research trends and implications for both research and practice.
KNOWLEDGE MANAGEMENT RESEARCH & PRACTICE
(2023)
Article
Business
Schena Rosamartina, Secundo Giustina, De Fano Domenico, Del Vecchio Pasquale, Russo Angeloantonio
Summary: This study examines the impact of a firm's digital reputation on its performance and investigates the moderating role of its orientation towards sustainable development. The findings suggest that digital reputation has a positive effect on both financial and non-financial performance. The breadth and concentration of Sustainable Development Goals (SDGs) coverage influence this relationship, while depth does not appear to be significant. Additionally, the study introduces a new data operationalization process to measure a firm's commitment to the SDGs of the 2030 Agenda.
JOURNAL OF BUSINESS RESEARCH
(2022)
Review
Agricultural Economics & Policy
Raffaele Silvestri, Domenico Morrone, Pasquale Del Vecchio, Gioconda Mele
Summary: This paper contributes to the literature on the blue economy and aquaculture by providing a systematic review of the research in these areas. The study identifies statistical trends and thematic areas, and highlights practical implications for both firms and policymakers. The use of systematic literature review to analyze the impact of the recent pandemic is a unique aspect of this research.
BRITISH FOOD JOURNAL
(2023)
Review
Business
Giustina Secundo, Gioconda Mele, Giuseppina Passiante, Angela Ligorio
Summary: This paper explores the prospects and opportunities of applying Machine Learning (ML) algorithms to project risk management for organizational innovation. Through the analysis of 42 papers, prospective future developments and challenges of ML applications for managing risks in software development projects, construction industry projects, climate and environmental issues, and Health and Safety projects are identified. The findings suggest that ML can enhance organizational innovation and play a strategic role in risk management for companies engaged in complex projects.
EUROPEAN JOURNAL OF INNOVATION MANAGEMENT
(2023)
Article
Business
Pasquale Del Vecchio, Gioconda Mele, Marco Villani
Summary: In the last decade, digital transformation has significantly impacted healthcare and created new opportunities in the field of e-health. Digital technologies, such as electronic health records, telemedicine, and artificial intelligence, play a crucial role in shaping a new healthcare model. This article employs a system dynamic approach to analyze the impact of digital technologies on e-health, specifically in intensive care units. The findings demonstrate the potential of using system dynamics as a policymaking tool to overcome barriers to sustainable healthcare development.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Article
Business
Pasquale del Vecchio, Caterina Malandugno, Giuseppina Passiante, Georgia Sakka
Summary: This study examines the process of value creation and business model innovation resulting from circular economy in the context of smart tourism, focusing on a single case study and integrating web-based desk analysis, interviews, and social big data analytics. Findings are related to Ecobnb, a network-based tourism company, coherent with the principles of value creation and business model innovation in the context of circular economy and smart tourism.
EUROMED JOURNAL OF BUSINESS
(2022)
Article
Computer Science, Information Systems
Sang-Bing Tsai, Xusen Cheng, Yanwu Yang, Jason Xiong, Alex Zarifis
Summary: This article structurally concludes the methods proposed and evidenced to develop digital entrepreneurship from a socio-technical perspective. The technology itself and the process of utilization should be carefully considered. From a social perspective, fulfilling the needs of customers in social interaction and nurturing characteristics and social skills for the digital work environment are crucial.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Xiaochang Fang, Hongchen Wu, Jing Jing, Yihong Meng, Bing Yu, Hongzhu Yu, Huaxiang Zhang
Summary: This study proposes a novel fake news detection framework, utilizing news semantic environment perception (NSEP) to identify fake news content. The framework consists of steps such as dividing the semantic environment into macro and micro levels, applying graph convolutional networks, and utilizing multihead attention. Empirical experiments show that the NSEP framework achieves high accuracy in detecting Chinese fake news, outperforming other baseline methods and highlighting the importance of both micro and macro semantic environments in early detection of fake news.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Xudong Sun, Alladoumbaye Ngueilbaye, Kaijing Luo, Yongda Cai, Dingming Wu, Joshua Zhexue Huang
Summary: This paper proposes a scalable distributed frequent itemset mining (ScaDistFIM) algorithm to address the data scalability and flexibility issues in basket analysis in the big data era. Experiment results demonstrate that the ScaDistFIM algorithm is more efficient compared to the Spark FP-Growth algorithm.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Boxu Guan, Xinhua Zhu, Shangbo Yuan
Summary: This paper aims to improve the interpretability of machine reading comprehension models by utilizing the pre-trained T5 model for evidence inference. They propose an interpretable reading comprehension model based on T5, which is trained on a more accurate evidence corpus and can infer precise interpretations for answers. Experimental results show that their model outperforms the baseline BERT model on the SQuAD1.1 task.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Yanhao Wang, Baohua Zhang, Weikang Liu, Jiahao Cai, Huaping Zhang
Summary: In this study, we propose a data augmentation-based semantic text matching model called STMAP. By using Gaussian noise and noise mask signal for data augmentation, as well as employing an adaptive optimization network for training target optimization, our model achieves good performance in few-shot learning and semantic deviation problems.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Jiahao Yang, Shuo Feng, Wenkai Zhang, Ming Zhang, Jun Zhou, Pengyuan Zhang
Summary: To pursue profit from stock markets, researchers utilize deep learning methods to forecast asset price movements. However, there are two issues in current research, the discrepancy between forecasting results and profits, and heavy reliance on prior knowledge. To address these issues, researchers propose a novel optimization objective and modeling method, and conduct experiments to validate their approach.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Heng Zhang, Chengzhi Zhang, Yuzhuo Wang
Summary: This study provides an accurate analysis of technology development in the field of Natural Language Processing (NLP) from an entity-centric perspective. The findings indicate an increase in the average number of entities per paper, with pre-trained language models becoming mainstream and the impact of Wikipedia dataset and BLEU metric continuing to rise. There has been a surge in popularity for new high-impact technologies in recent years, with researchers accepting them at an unprecedented speed.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Davide Buscaldi, Danilo Dessi, Enrico Motta, Marco Murgia, Francesco Osborne, Diego Reforgiato Recupero
Summary: In scientific papers, citing other articles is a common practice to support claims and provide evidence. This paper proposes two automatic methods using Transformer models to address citation placement, and achieves significant improvements in experiments.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Baozhuang Niu, Lingfeng Wang, Xinhu Yu, Beibei Feng
Summary: This paper examines whether the incumbent brand should adopt digital technology to forecast demand and adjust order decisions in the face of soaring demand for medical supply caused by frequent outbreaks of regional COVID-19 epidemic. The study finds that digital transformation can lead to a triple-win situation among the incumbent brand, social welfare, and consumer surplus, as well as bring benefits to the manufacturer. Furthermore, the research provides insights for firms' digital entrepreneurship decisions through theoretical optimization and data processing/policy simulation.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Xueyang Qin, Lishang Li, Fei Hao, Meiling Ge, Guangyao Pang
Summary: Image-text retrieval is important in connecting vision and language. This paper proposes a method that utilizes prior knowledge to enhance feature representations and optimize network training for better retrieval results.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Review
Computer Science, Information Systems
Gang Ren, Lei Diao, Fanjia Guo, Taeho Hong
Summary: This paper proposes a novel approach for predicting the helpfulness of reviews by utilizing both textual and image features. The proposed method considers the correlation between features through self-attention and co-attention mechanisms, and fuses multi-modal features for prediction. Experimental results demonstrate the superior performance of the proposed method compared to benchmark methods.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Zhongquan Jian, Jiajian Li, Qingqiang Wu, Junfeng Yao
Summary: Aspect-Level Sentiment Classification (ALSC) is a crucial challenge in Natural Language Processing (NLP). Most existing methods fail to consider the correlations between different instances, leading to a lack of global viewpoint. To address this issue, we propose a Retrieval Contrastive Learning (RCL) framework that extracts intrinsic knowledge across instances for improved instance representation. Experimental results demonstrate that training ALSC models with RCL leads to substantial performance improvements.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Ying Hu, Yanping Chen, Ruizhang Huang, Yongbin Qin, Qinghua Zheng
Summary: Biomedical relation extraction aims to extract the interactive relations between biomedical entities in a sentence. This study proposes a hierarchical convolutional model to address the semantic overlapping and data imbalance problems. The model encodes both local contextual features and global semantic dependencies, enhancing the discriminability of the neural network for biomedical relation extraction.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Zhou Yang, Yucai Pang, Xuehong Li, Qian Li, Shihong Wei, Rong Wang, Yunpeng Xiao
Summary: This study proposes a rumor detection model based on topic audiolization, which transforms the topic space into audio-like signals. Experimental results show that the model achieves significant performance improvements in rumor identification.
INFORMATION PROCESSING & MANAGEMENT
(2024)
Article
Computer Science, Information Systems
Alistair Moffat
Summary: This paper proposes the buying power metric for assessing the quality of product rankings on e-commerce sites. It discusses the relationship between the buying power metric and user reactions, and introduces an alternative product ranking effectiveness metric.
INFORMATION PROCESSING & MANAGEMENT
(2024)
