Showing papers in "International Journal of Information Management in 2021"

TL;DR: This research offers significant and timely insight to AI technology and its impact on the future of industry and society in general, whilst recognising the societal and industrial influence on pace and direction of AI development.

TL;DR: This research offers a significant and timely contribution to both researchers and practitioners in the form of challenges and opportunities where it highlights the limitations within the current research, outline the research gaps and develop the questions and propositions that can help advance knowledge within the domain of digital and social marketing.

TL;DR: In this paper, the authors present a detailed step-by-step guide on how to apply fuzzy-set Qualitative Comparative Analysis (fsQCA) in Information Systems and marketing.

TL;DR: Emerging technologies used to mitigate the threats of COVID-19 and relevant challenges related to technology design, development, and use are examined and insights and suggestions into how information systems and technology scholars can help fight the CO VID-19 pandemic are provided.

TL;DR: A critical literature review related to the integration of AI to organizational strategy is provided, synthetizing the existing approaches and frameworks, highlighting the potential benefits, challenges and opportunities and presenting a discussion about future research directions.

TL;DR: A Long Short Term Memory network-based method for forecasting multivariate time series data and an LSTM Autoencoder network- based method combined with a one-class support vector machine algorithm for detecting anomalies in sales are suggested.

TL;DR: A text mining method to quantify constructs using a large-scale sample of 3,500,445 online review texts found that interactivity has a curvilinear relationship with customer engagement behavior.

TL;DR: A vision for a Disaster City Digital Twin paradigm that can enable interdisciplinary convergence in the field of crisis informatics and information and communication technology in disaster management and integrate artificial intelligence algorithms and approaches to improve situation assessment, decision making, and coordination among various stakeholders is presented.

TL;DR: This research employed cited reference search to systematically review studies that cited UTAUT2 originating article and mapped to Johns' context dimensions to identify various limitations of the existing technology adoption research and to provide multi-level framework for future researchers with libraries of context dimensions.

TL;DR: Deep neural networks, Rpart regression tree and Random forest with variable reduction procedures were used to create prediction models of specific energy consumption of Croatian public sector buildings, and the most accurate model was produced by Random forest method.

TL;DR: The present study aims to provide a comprehensive understanding of the main challenges related to user privacy that affect DDI, and identifies 14 topics related to the study of DDI and UGD strategies.

TL;DR: In this article, a growing concern that research on AI could experience a lack of attention due to a "lack of resources" is raised. But, the authors argue that this is not the case.

TL;DR: This paper argues that blockchain’s characteristics are especially important for enforcing sustainability standards in developing countries, and develops seven propositions, which describe how blockchain can help address a number of challenges various stakeholders face in promoting sustainable supply chains in developing nations.

TL;DR: The results reveal that the comparative effects of competence and warmth perception exist when artificial autonomy contributes to users' continuance usage intention and increase the understanding of AI-enabled artificial autonomy in information systems research.

TL;DR: The paper theoretically argues that the use of BD, in addition to enhancing intentional and direct collaborative innovation processes, allows the development of passive and unintentional co-innovation that can be implemented through indirect relationships between the collaborative actors.

TL;DR: Big Data applications in CI processes within organizations within organizations are examined by exploring how organizations deal with Big Data analytics, and this study provides a context for developing Big Data frameworks and process models for CI in organizations.

TL;DR: Analysis of survey data from social commerce customers in Indonesia indicates that repurchase and WOM intentions are positively affected by trust and satisfaction, where both Trust and satisfaction are negatively affected by reputation and information quality.

TL;DR: It is confirmed the perceived benefits of AV are vital factors for AV adoption whereas the perceived safety of AV significantly reduces the influence of various concerns regarding AV.

TL;DR: Consumer acceptance of holographic AR substitutes for real products is investigated and multiple marketing implications, such as the disruptive potential of AR, the possibility of “copying and pasting” the real world including the threat of virtual counterfeits, the role of offline ad blockers, and four generic response strategies for companies are presented.

TL;DR: Findings show that market mavens (when compared to non-mavens) have more followers, post more often, have less readable posts, use more uppercase letters, use less distinct words, and use hashtags more often.

TL;DR: The study proposes a 20-item scale in five distinct dimensions: Technology anxiety; Work–life interface; Engagement orientation; Support orientation; and Quality of life to demonstrate how to manage information for the benefit of all stakeholders involved in the making of a smart city.

TL;DR: This study analyzes the successful applications of AI at Alibaba's e-commerce fulfillment center and indicates that the key AI resources include data, AI algorithms, and robots must be orchestrated to work with other related resources to generate strong AI capabilities.

TL;DR: In this article, the authors introduce and situate computational data science processes for exploring urban fabric patterns and spatial order, and demonstrate these workflows with OSMnx and data from OpenStreetMap to examine street network patterns, orientations, and configurations in different study sites around the world, considering what these reveal about the urban fabric.

TL;DR: This article reviews the existing smart city literature and integrates knowledge management perspectives to provide an overview of future research directions and proposes a series of knowledge-driven policy recommendations to contribute towards the UN Sustainable Development Goals.

TL;DR: This study explores how personality, trust, privacy concerns, and prior experiences affectCustomer experience performance perceptions and the combinations of these factors that lead to high customer experience performance.

TL;DR: Regression analysis reveals that article attributes such as article order, methodology, presence of authors from Europe, number of references, number-of- keywords, and abstract length have a significant association with the citations.

TL;DR: New insights are provided into the role of gamification in influencing consumer buying behavior in the online marketplace and several antecedents of consumers’ impulse buying during arguably the largest e-commerce shopping festival in the world are highlighted.

TL;DR: In this paper, the authors explore the sources of algorithmic biases across the data-driven innovation process using a systematic literature review, thematic analysis and a case study on the Robo-Debt scheme in Australia.

TL;DR: This paper first generates different training path data sets applying two different offline path planning algorithms and evaluates the performance of a neural network as an online path planner depending on the training data under a simulation environment, and investigates the properties of theTraining data that make a Neural network more reliable for online path planning.

TL;DR: In this article, the authors quantitatively assess the digital government transformation and its driving and impeding factors by collecting and analyzing through structural equation modeling 491 answers to a survey to Italian administrations.