Dimitrios Buhalis, T. Harwood, Vanja Bogicevic
et al.
Purpose Technological disruptions such as the Internet of Things and autonomous devices, enhanced analytical capabilities (artificial intelligence) and rich media (virtual and augmented reality) are creating smart environments that are transforming industry structures, processes and practices. The purpose of this paper is to explore critical technological advancements using a value co-creation lens to provide insights into service innovations that impact ecosystems. The paper provides examples from tourism and hospitality industries as an information dependent service management context. Design/methodology/approach The research synthesizes prevailing theories of co-creation, service ecosystems, networks and technology disruption with emerging technological developments. Findings Findings highlight the need for research into service innovations in the tourism and hospitality sector at both macro-market and micro-firm levels, emanating from the rapid and radical nature of technological advancements. Specifically, the paper identifies three areas of likely future disruption in service experiences that may benefit from immediate attention: extra-sensory experiences, hyper-personalized experiences and beyond-automation experiences. Research limitations/implications Tourism and hospitality services prevail under varying levels of infrastructure, organization and cultural constraints. This paper provides an overview of potential disruptions and developments and does not delve into individual destination types and settings. This will require future work that conceptualizes and examines how stakeholders may adapt within specific contexts. Social implications Technological disruptions impact all facets of life. A comprehensive picture of developments here provides policymakers with nuanced perspectives to better prepare for impending change. Originality/value Guest experiences in tourism and hospitality by definition take place in hostile environments that are outside the safety and familiarity of one’s own surroundings. The emergence of smart environments will redefine how customers navigate their experiences. At a conceptual level, this requires a complete rethink of how stakeholders should leverage technologies, engage and reengineer services to remain competitive. The paper illustrates how technology disrupts industry structures and stimulates value co-creation at the micro and macro-societal level.
Paula Höhrová, Jakub Soviar, Martin Holubčík
et al.
This paper explores the potential applications of unmanned aerial vehicles (UAVs) in healthcare, focusing on their implementation in real-world scenarios. UAVs, commonly known as drones, have shown significant promise in improving healthcare services, particularly in the rapid transport of medical supplies such as blood, vaccines, and laboratory samples. Through a systematic review of existing literature, this study identifies five key areas where drones are already being utilized or hold potential for further integration: sample transportation, emergency medical services (e.g., AED delivery), organ transport, disaster relief, and mosquito population control. The study highlights both the benefits and risks associated with UAV deployment in healthcare, including increased efficiency and accessibility of medical supplies versus concerns over safety, battery life, and regulatory challenges. The paper concludes with an evaluation of the readiness of these technologies for widespread adoption, suggesting that with further improvements and regulatory adjustments, drones could become integral to modern healthcare systems.
Technological innovation is constantly reshaping the materiality and mechanics of smart-city initiatives. Recently, innovation in artificial intelligence (AI) in the shape of self-driving cars, robots and city brains, has been pushing the so-called smart city to morph into an autonomous urban creature which is largely unknown. In this emerging strand of smart urbanism, artificially intelligent entities are taking the management of urban services as well as urban governance out of the hands of humans, operating the city in an autonomous manner. This paper explores, in theory and practice, how the development of AI intersects with the development of the city. The contribution of the paper is threefold. First, the paper advances a theoretical framework to understand AI specifically in urban contexts. It develops the concept of urban artificial intelligence, capturing the main manifestations of AI in cities. Second, the paper examines the case of Masdar City, an Emirati urban experiment, to show how the genesis of urban artificial intelligences is part of a long-standing process of technological development and a politico-economic agenda which together are enabling the transition from automation to autonomy. Third, it proposes a research agenda to investigate what the paper terms the autonomous city.
Modern precision manufacturing faces the challenge of integrating accuracy requirements into a framework of agile and sustainable production technologies. This development leads to numerous further challenges, affecting almost all areas of precision manufacturing industry. To overcome those challenges, this article presents promising technologies and innovative solution concepts from the field of temperature measurement in the cutting zone, process design for advanced materials, the development of reconfigurable machine tools, the optimization of the temperature behaviour of high-speed spindles and the use of edge computing in machine tools. Using the presented solutions, modern precision machining can be made more future-oriented in terms of sustainability and resilience.
This research examines the implementation of marketing automation technologies in optimizing various customer journey touchpoints within e-commerce contexts. Through a comprehensive analysis of peer-reviewed articles from the Scopus database spanning 2020-2024, this study explores how marketing automation, particularly programmatic marketing, leverages advanced data analytics and machine learning to personalize customer interactions and optimize marketing effectiveness. Our systematic review reveals three key findings. First, the strategic implementation of marketing automation significantly enhances revenue generation through improved customer data analytics, predictive modeling, and dynamic pricing strategies, with studies showing increased conversion rates and higher customer lifetime value. Second, marketing automation demonstrates substantial impact on customer retention by enabling personalized experiences and proactive engagement, leading to increased customer satisfaction and loyalty. Third, successful implementation of marketing automation requires robust technological infrastructure, organizational alignment, and continuous optimization of marketing processes. The analysis also highlights that effective integration of predictive analytics and personalization plays a crucial role in driving customer engagement, while the combination of social media analytics and game theory provides businesses with comprehensive frameworks for optimizing competitive strategies. This review contributes to the existing literature by providing a systematic understanding of marketing automation's role in the e-commerce customer journey, highlighting key success factors, implementation challenges, and emerging trends in the field. The findings offer valuable insights for practitioners and researchers interested in leveraging marketing automation for enhanced business performance and competitive advantage in the rapidly evolving e-commerce landscape.
This quantitative study rigorously investigates the impact of tax system automation on revenue mobilization, taxpayer compliance behavior, and organizational transparency within the Federal Inland Revenue Service (FIRS) of Nigeria’s Southwest zone. Drawing upon survey data from 97 randomly selected FIRS administrators, the research employs descriptive statistics and inferential techniques—simple linear regression and chi-square analysis—to test three hypotheses derived from the Technology Acceptance Model. Results reveal that increased utilization of e-filing, e-payment, ITAS, and TaxProMax platforms significantly predicts revenue generation (β = 0.243, p = 0.016) and compliance rates (β = 0.280, p = 0.005), while higher automation adoption is moderately associated with perceptions of enhanced transparency (χ²(1) = 9.112, p = 0.003; Cramer’s V = 0.306). These findings underscore that digital transformation in tax administration contributes to measurable performance gains, albeit with modest effect sizes that point to supplementary determinants such as technological infrastructure quality, user training adequacy, and regulatory support. Practical recommendations include targeted legislative amendments, infrastructure investments, capacity-building initiatives, and stakeholder-specific implementation protocols to optimize system uptime, security, and user engagement. This study extends empirical literature on e-governance and public sector innovation by providing localized evidence and a robust methodological template for future longitudinal and comparative analyses. .
The adoption of Information Technologies in organizations is a crucial decision for growth, productivity, competitiveness, and even survival in an increasingly competitive market. It highlights the growing importance of automation solutions such as Robotic Process Automation to achieve or maintain competitiveness. Although there is research on Robotic Process Automation, most of it focuses on technology, and what it can provide, rather than on the effective contribution to the better performance of organizations, which depends on adoption and use. This work studies the propensity to the adoption and usage of Robotic Process Automation. As a basis for the conceptual model of this research, the Diffusion of Innovation and Technology Organization Environment theoretical models were used in order to evaluate the propensity for adoption and use of Robotic Process Automation from an organizational perspective. This research uses mixed methods. Initially, in the exploratory phase, interviews were carried out to complement the information collected in the literature with a view to developing a model for assessing the propensity to use Robotic Process Automation, and, subsequently, hypotheses were made based on the existing literature and combined with the exploratory phase results; in addition, data from surveys collected from 141 organizations were utilized to evaluate the suggested model, as well as the underlying hypotheses. The findings suggest that it is in the technological context that the antecedents prove to be significant in the propensity for the adoption and use of Robotic Process Automation, namely Compatibility and Relative Advantage. The implications of these findings are discussed from a practical and research perspective.
William Douglas Carvalho, Salustiano V. Costa-Neto, Fernando Cesar Paiva Dagosta
et al.
Abstract Conservation policies in Brazil differ between the “biomes” into which the country has divided its territory since 2004. The Amazon biome is predominantly tropical forest but also includes unique savanna ecosystems, while the Cerrado biome is composed of various types of savanna but also includes islands and corridors of forest. Confusion, both inadvertent and deliberate, between the terms Cerrado and “savanna” has resulted in reducing the protection of Amazonian savannas by allowing less-demanding requirements applicable to the Cerrado biome to be applied. Threats to Amazonian savannas are also increased by legal provisions that allow required “legal reserves” in private properties to be compensated by reserves elsewhere in the same biome without requiring them to be of the same ecosystem type. We suggest needed clarifications and changes in Brazil’s regulations to guarantee the protection of the country’s unique Amazonian savanna ecosystems.
General. Including nature conservation, geographical distribution, Technological innovations. Automation
Orlando Enrique Contreras-Pacheco, Rodolfo Mosquera-Navarro, Juan Camilo Lésmez-Peralta
Este estudio examina las percepciones de las empresas del departamento de Santander, Colombia, sobre la rigurosidad en el desarrollo de programas de capacitación y la evaluación de sus resultados mediante técnicas de Retorno de Inversión (ROI). Mediante un estudio Delphi en dos rondas, se consolidaron las perspectivas de 21 académicos y profesionales sobre la efectividad de dichas evaluaciones. A pesar del consenso sobre la importancia de los procesos de capacitación y desarrollo, los resultados sugieren discrepancia entre la intención de medir el impacto estratégico y la falta de implementación de modelos robustos de evaluación. Se tiende a priorizar lo urgente (evaluaciones inmediatas basadas en percepciones) sobre lo importante (medición del ROI a largo plazo), lo cual apunta a una desconexión entre intención y acción. Este estudio ofrece una primera aproximación al tema en Colombia y sugiere futuras investigaciones sobre la implementación de modelos de evaluación en el sector productivo.
Many organizations strive to increase the level of automation in their business processes. While automation historically was mainly concerned with automating physical labor, current automation efforts mostly focus on automation in a digital manner, thus targeting work that is related to the interaction between humans and computers. This type of automation, commonly referred to as business process automation, has many facets. Yet, academic literature mainly focuses on Robotic Process Automation, a specific automation capability. Recognizing that leading vendors offer automation capabilities going way beyond that, we use this paper to develop a detailed understanding of business process automation in industry. To this end, we conduct a structured market analysis of the 18 predominant vendors of business process automation solutions as identified by Gartner. As a result, we provide a comprehensive overview of the business process automation capabilities currently offered by industrial vendors. We show which types and facets of automation exist and which aspects represent promising directions for the future.
The article examines the impact of 16 key parameters of the Georgian economy on economic inequality, using the Perelman model and Ricci flow mathematical methods. The study aims to conduct a deep analysis of the impact of socio-economic challenges and technological progress on the dynamics of the Gini coefficient. The article examines the following parameters: income distribution, productivity (GDP per hour), unemployment rate, investment rate, inflation rate, migration (net negative), education level, social mobility, trade infrastructure, capital flows, innovative activities, access to healthcare, fiscal policy (budget deficit), international trade (turnover relative to GDP), social protection programs, and technological access. The results of the study confirm that technological innovations and social protection programs have a positive impact on reducing inequality. Productivity growth, improving the quality of education, and strengthening R&D investments increase the possibility of inclusive development. Sensitivity analysis shows that social mobility and infrastructure are important factors that affect economic stability. The accuracy of the model is confirmed by high R^2 values (80-90%) and the statistical reliability of the Z-statistic (<0.05). The study uses Ricci flow methods, which allow for a geometric analysis of the transformation of economic parameters in time and space. Recommendations include the strategic introduction of technological progress, the expansion of social protection programs, improving the quality of education, and encouraging international trade, which will contribute to economic sustainability and reduce inequality. The article highlights multifaceted approaches that combine technological innovation and responses to socio-economic challenges to ensure sustainable and inclusive economic development.
Artificial intelligence (AI) is a key enabler of innovation against climate change. In this study, we investigate the intersection of AI and climate adaptation and mitigation technologies through patent analyses of a novel dataset of approximately 63 000 Green AI patents. We analyze patenting trends, corporate ownership of the technology, the geographical distributions of patents, their impact on follow-on inventions and their market value. We use topic modeling (BERTopic) to identify 16 major technological domains, track their evolution over time, and identify their relative impact. We uncover a clear shift from legacy domains such as combustion engines technology to emerging areas like data processing, microgrids, and agricultural water management. We find evidence of growing concentration in corporate patenting against a rapidly increasing number of patenting firms. Looking at the technological and economic impact of patents, while some Green AI domains combine technological impact and market value, others reflect weaker private incentives for innovation, despite their relevance for climate adaptation and mitigation strategies. This is where policy intervention might be required to foster the generation and use of new Green AI applications.
Preprints have become increasingly essential in the landscape of open science, facilitating not only the exchange of knowledge within the scientific community but also bridging the gap between science and technology. However, the impact of preprints on technological innovation, given their unreviewed nature, remains unclear. This study fills this gap by conducting a comprehensive scientometric analysis of patent citations to bioRxiv preprints submitted between 2013 and 2021, measuring and accessing the contribution of preprints in accelerating knowledge transfer from science to technology. Our findings reveal a growing trend of patent citations to bioRxiv preprints, with a notable surge in 2020, primarily driven by the COVID-19 pandemic. Preprints play a critical role in accelerating innovation, not only expedite the dissemination of scientific knowledge into technological innovation but also enhance the visibility of early research results in the patenting process, while journals remain essential for academic rigor and reliability. The substantial number of post-online-publication patent citations highlights the critical role of the open science model-particularly the "open access" effect of preprints-in amplifying the impact of science on technological innovation. This study provides empirical evidence that open science policies encouraging the early sharing of research outputs, such as preprints, contribute to more efficient linkage between science and technology, suggesting an acceleration in the pace of innovation, higher innovation quality, and economic benefits.
Within the expansive domain of “Natural Language Processing” (NLP), the task of “text summarization” emerges as a foundational element, playing a pivotal role in distilling relevant information from extensive textual corpora. In the digital age, the importance of efficient summarization becomes increasingly critical, given the overwhelming volume of textual information. This comprehensive study delves into the intricacies of both extractive and abstractive summarization techniques, placing a specific focus on transformer-based models like BERT and GPT. These models, celebrated for their remarkable capabilities in context comprehension and coherent summarization, are rigorously evaluated alongside established methods like TF-IDF, TextRank, Sumy, Fine Tuning Transformers, Model-T5, LSTM, greedy, and beam search. The practical implications of text summarization extend across diverse fields, encompassing news stories, academic papers, and social media content, underscoring its broad utility in various domains. This study not only incorporates cutting-edge models but also explores a gamut of evaluation methods to discern the quality of summarization. By intertwining theory and application, this research positions itself at the forefront of evolving summarization approaches, shedding light on the transformative impact on information consumption patterns. The dynamic landscape of summarization methods underscores the need for continuous research and innovation, as technological advancements continue to reshape how individuals access and comprehend information.
Monitoring of aquatic ecosystems has been historically accomplished by intensive campaigns of direct measurements (by probes and other boat instruments) and indirect extensive methods such as aero-photogrammetry and satellite detection. These measurements characterized the research in the last century, with significant but limited improvements within those technological boundaries. The newest advances in the field of smart devices and increased networking capabilities provided by emerging tools, such as the Internet of Things (IoT), offer increasing opportunities to provide accurate and precise measurements over larger areas. These perspectives also correspond to an increasing need to promptly respond to frequent catastrophic impacts produced by drilling stations and intense transportation activities of dangerous materials over ocean routes. The shape of coastal ecosystems continuously varies due to increasing anthropic activities and climatic changes, aside from touristic activities, industrial impacts, and conservation practices. Smart buoy networks (SBNs), autonomous underwater vehicles (AUVs), and multi-sensor microsystems (MSMs) such as smart cable water (SCW) are able to learn specific patterns of ecological conditions, along with electronic “noses”, permitting them to set innovative low-cost monitoring stations reacting in real time to the signals of marine environments by autonomously adapting their monitoring programs and eventually sending alarm messages to prompt human intervention. These opportunities, according to multimodal scenarios, are dramatically changing both the coastal monitoring operations and the investigations over large oceanic areas by yielding huge amounts of information and partially computing them in order to provide intelligent responses. However, the major effects of these tools on the management of marine environments are still to be realized, and they are likely to become evident in the next decade. In this review, we examined from an ecological perspective the most striking innovations applied by various research groups around the world and analyzed their advantages and limits to depict scenarios of monitoring activities made possible for the next decade.
The rapid evolution of technology has precipitated the widespread adoption of Robotic Process Automation (RPA) across industries, offering the potential to revolutionize traditional audit procedures. In the realm of auditing, RPA stands as a game-changer, promising to automate repetitive tasks, enhance data accuracy, and empower auditors to focus on intricate, judgment-based activities. This paper explores the transformative journey of RPA, tracing its evolution from early applications in the 2000s to its current sophistication. Auditors have recognized its potential to revolutionize traditional methodologies, initiating pilot programs and experiments that demonstrated efficiency gains and error reductions, particularly in routine tasks. The maturation phase from 2019 to 2021 witnessed the integration of RPA into complex audit processes, accompanied by challenges such as data security and ethical considerations. Presently, RPA is seamlessly integrated with advanced technologies like artificial intelligence and machine learning, contributing to significant improvements in operational efficiency and reduced error risks in audit processes. A thorough literature review synthesizes key studies, highlighting RPA's dynamic journey and addressing challenges through a balanced approach. The paper concludes by outlining crucial regulatory considerations in India and globally, emphasizing ethical technology use and the need for ongoing oversight. Future research directions include the integration of RPA with emerging technologies, exploration of ethical implications, continuous monitoring of regulatory landscapes, tracking technological advancements, assessing evolving skill sets for auditors, and studying user experiences for a comprehensive understanding of RPA's transformative impact on auditing. In summary, the paper underscores the necessity for auditors to navigate the delicate balance between embracing RPA innovation and upholding the integrity and quality of audit engagements in an ever- evolving, technology-driven business environment.
PurposeThis theme issue aims to explore the depth and breadth of automation and artificial intelligence’s (AI’s) impact on the hospitality and tourism industry.Design/methodology/approachThe thematic examination of the articles presented in this theme issue highlights the central results concerning the strategic inquiry, especially regarding their addition to knowledge, which is vital for fostering idea creation and theoretical research beneficial to various stakeholders in the tourism and hospitality sector. Given the swift evolution of these technologies, grasping their utilization, advantages and obstacles is essential for industry experts, decision-makers and scholars.FindingsThis theme issue encapsulates the transformative impact of automation and AI in the tourism and hospitality industry, highlighting the juxtaposition of enhanced operational efficiency against employment security concerns. It emphasizes the need for ethical governance to address AI’s ethical dilemmas and security vulnerabilities. The exploration of consumer attitudes towards AI, particularly in service robots and facial emotion recognition technologies, is deemed crucial for leveraging AI’s full potential in service delivery. Furthermore, AI’s entry into gastronomy prompts a reevaluation of traditional culinary practices, advocating for a balance between technological innovation and the preservation of cultural heritage.Originality/valueThis theme issue stands out for its focused exploration of the transformative effects of automation and AI within the hospitality and tourism industry. Unlike broader discussions on technology in business, it delves into specific AI-driven innovations, operational changes and the resultant shifts in consumer behavior and industry standards. By curating a collection of empirical research, theoretical analyses and content analyses, this issue is providing important insights into how automation and AI are reshaping service delivery, management practices and strategic decision-making in an industry characterized by its intense customer focus and reliance on human-to-human interaction.