2,589 research outputs found

    Architectural framework of digital marketing: Examining its relationship with customers and the intermediary role of electronic quality in Saudi commercial banks

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    This study on the moderating effect of electronic quality in mobile marketing aims to examine the factors that influence how Saudi commercial banks are viewed by their customers. A research framework that sheds light on the state of the research was developed after a comprehensive analysis of the accessible literature. The theoretical foundation of this study is the idea of perceived characteristics, which identifies five critical factors that influence adoption rates. The empirical results of this study are presented based on a sample of 300 respondents (n = 300). The research was conducted using the statistical technique of least squares structural equation modeling (PLS-SEM). The reporting format conforms to accepted PLS-SEM analysis standards. The results reveal a significant association between mobile marketing and customer perceptions in the context of Saudi commercial banks, especially when electronic quality is used as a mediating variable. Based on these findings, we suggest that Saudi commercial banks should strategically include e-quality in their digital marketing campaigns, paying special attention to mobile marketing

    Applications of Deep Learning Models in Financial Forecasting

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    In financial markets, deep learning techniques sparked a revolution, reshaping conventional approaches and amplifying predictive capabilities. This thesis explored the applications of deep learning models to unravel insights and methodologies aimed at advancing financial forecasting. The crux of the research problem lies in the applications of predictive models within financial domains, characterised by high volatility and uncertainty. This thesis investigated the application of advanced deep-learning methodologies in the context of financial forecasting, addressing the challenges posed by the dynamic nature of financial markets. These challenges were tackled by exploring a range of techniques, including convolutional neural networks (CNNs), long short-term memory networks (LSTMs), autoencoders (AEs), and variational autoencoders (VAEs), along with approaches such as encoding financial time series into images. Through analysis, methodologies such as transfer learning, convolutional neural networks, long short-term memory networks, generative modelling, and image encoding of time series data were examined. These methodologies collectively offered a comprehensive toolkit for extracting meaningful insights from financial data. The present work investigated the practicality of a deep learning CNN-LSTM model within the Directional Change framework to predict significant DC events—a task crucial for timely decisionmaking in financial markets. Furthermore, the potential of autoencoders and variational autoencoders to enhance financial forecasting accuracy and remove noise from financial time series data was explored. Leveraging their capacity within financial time series, these models offered promising avenues for improved data representation and subsequent forecasting. To further contribute to financial prediction capabilities, a deep multi-model was developed that harnessed the power of pre-trained computer vision models. This innovative approach aimed to predict the VVIX, utilising the cross-disciplinary synergy between computer vision and financial forecasting. By integrating knowledge from these domains, novel insights into the prediction of market volatility were provided

    Industry Platforms: A New Mode of Coordination in the Economy

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    This discussion paper is a plea for an urgently needed shift in perspective: from the concentration of social science research on the ubiquitous platforms of the consumption- and communication-based internet to the investigation of the platform-oriented reorganization of industrial distribution, production and innovation processes, which has so far received far less attention. The paper focuses on two questions. Firstly, what distinguishes industrial platforms from the platforms that characterize the consumption- and- communication-based internet? Can typical peculiarities and overarching characteristics of platform-based forms of work and organization in industry be identified? And secondly, do platforms represent an independent form of organization and coordination of industrial market, production and innovation processes that is substantially different from organized networks? The paper undertakes an empirical mapping and classification of the little explored field of industrial platforms and discusses from a theoretical-conceptual perspective why platforms should be conceived of as a sui generis form of organization whose dominant mode of coordination can be described as rule-based curation

    Customers’ Continued Adoption of Mobile Apps and Their Satisfaction with Restaurants: The Case of McDonald’s

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    Background: The major purpose of this research is to examine Contactless Technology (CT) users’ post-adoption phenomena in the context of mobile apps (MA) run by a Quick Service Restaurant (QSR). It applies the Post-Adoption Model of Information System Continuance (PAMISC) to examine how QSR customers’ technology anxiety (TA), confirmation of initial expectations, perceived usefulness (PU), and satisfaction with CT relate to their continued intention of use. Furthermore, the study investigates the relationship between customers’ satisfaction with CT and their overall satisfaction with QSR. Methods: To test the research model, we collected survey data from 245 users of MA provided by McDonald’s restaurants in the US, which are analyzed through Partial Least Square analysis using SmartPLS 4.0. Results: The theoretical relationships in the PAMISC hold true in the context of QSR’s MA. Current QSR customers’ TA is negatively associated with their perceived usefulness, but is not related to the degree of confirmation of using MA. Customers’ continued intention of use and satisfaction with MA are positively related to overall satisfaction with QSR. Conclusion: Our study is among the first to provide empirical/practical evidence of the PAMISC in the context of IT-enabled hospitality services. It also extends the model in two important ways. First, the study examines the role of TA, an important personal trait relevant to individuals’ use of QSR technology. Second, it highlights customers’ satisfaction with firm-provided technology to improve their overall satisfaction with the firm in the context of QSRs. For practitioners, it is important for QSR managers to understand the impact of TA on customers’ adoption of MA, so that they can design their MA with simpler interfaces and more human aspects. Managers should also make sure that MA is well-designed to satisfy customers’ needs, which will then lead to those customers’ overall satisfaction with the QSR

    What is Business Process Automation Anyway?

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    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

    Digital Innovations for a Circular Plastic Economy in Africa

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    Plastic pollution is one of the biggest challenges of the twenty-first century that requires innovative and varied solutions. Focusing on sub-Saharan Africa, this book brings together interdisciplinary, multi-sectoral and multi-stakeholder perspectives exploring challenges and opportunities for utilising digital innovations to manage and accelerate the transition to a circular plastic economy (CPE). This book is organised into three sections bringing together discussion of environmental conditions, operational dimensions and country case studies of digital transformation towards the circular plastic economy. It explores the environment for digitisation in the circular economy, bringing together perspectives from practitioners in academia, innovation, policy, civil society and government agencies. The book also highlights specific country case studies in relation to the development and implementation of different innovative ideas to drive the circular plastic economy across the three sub-Saharan African regions. Finally, the book interrogates the policy dimensions and practitioner perspectives towards a digitally enabled circular plastic economy. Written for a wide range of readers across academia, policy and practice, including researchers, students, small and medium enterprises (SMEs), digital entrepreneurs, non-governmental organisations (NGOs) and multilateral agencies, policymakers and public officials, this book offers unique insights into complex, multilayered issues relating to the production and management of plastic waste and highlights how digital innovations can drive the transition to the circular plastic economy in Africa. The Open Access version of this book, available at https://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license

    Fictocritical Cyberfeminism: A Paralogical Model for Post-Internet Communication

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    This dissertation positions the understudied and experimental writing practice of fictocriticism as an analog for the convergent and indeterminate nature of “post-Internet” communication as well a cyberfeminist technology for interfering and in-tervening in metanarratives of technoscience and technocapitalism that structure contemporary media. Significant theoretical valences are established between twen-tieth century literary works of fictocriticism and the hybrid and ephemeral modes of writing endemic to emergent, twenty-first century forms of networked communica-tion such as social media. Through a critical theoretical understanding of paralogy, or that countercultural logic of deploying language outside legitimate discourses, in-volving various tactics of multivocity, mimesis and metagraphy, fictocriticism is ex-plored as a self-referencing linguistic machine which exists intentionally to occupy those liminal territories “somewhere in among/between criticism, autobiography and fiction” (Hunter qtd. in Kerr 1996). Additionally, as a writing practice that orig-inated in Canada and yet remains marginal to national and international literary scholarship, this dissertation elevates the origins and ongoing relevance of fictocriti-cism by mapping its shared aims and concerns onto proximal discourses of post-structuralism, cyberfeminism, network ecology, media art, the avant-garde, glitch feminism, and radical self-authorship in online environments. Theorized in such a matrix, I argue that fictocriticism represents a capacious framework for writing and reading media that embodies the self-reflexive politics of second-order cybernetic theory while disrupting the rhetoric of technoscientific and neoliberal economic forc-es with speech acts of calculated incoherence. Additionally, through the inclusion of my own fictocritical writing as works of research-creation that interpolate the more traditional chapters and subchapters, I theorize and demonstrate praxis of this dis-tinctively indeterminate form of criticism to empirically and meaningfully juxtapose different modes of knowing and speaking about entangled matters of language, bod-ies, and technologies. In its conclusion, this dissertation contends that the “creative paranoia” engendered by fictocritical cyberfeminism in both print and digital media environments offers a pathway towards a more paralogical media literacy that can transform the terms and expectations of our future media ecology

    A comparative analysis of good enterprise data management practices:insights from literature and artificial intelligence perspectives for business efficiency and effectiveness

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    Abstract. This thesis presents a comparative analysis of enterprise data management practices based on literature and artificial intelligence (AI) perspectives, focusing on their impact on data quality, business efficiency, and effectiveness. It employs a systematic research methodology comprising of a literature review, an AI-based examination of current practices using ChatGPT, and a comparative analysis of findings. The study highlights the importance of robust data governance, high data quality, data integration, and security, alongside the transformative potential of AI. The limitations revolve around the primarily qualitative nature of the study and potential restrictions in the generalizability of the findings. However, the thesis offers valuable insights and recommendations for enterprises to optimize their data management strategies, underscoring the enhancement potential of AI in traditional practices. The research contributes to scientific discourse in information systems, data science, and business management

    How is web design related to sales? The relationship between sales and web design within Amazon.com

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    Internship Report presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing IntelligenceThe development of technology has caused significant changes in the business environment and the management of companies, and business competitiveness has become an increasingly important factor. Thus, companies must capture consumers' attention and convince them to buy. Therefore, it is necessary to understand how small and medium-sized businesses can differentiate themselves in an extensive medium like the Internet. This study aims to delve into the importance of web design according to the four defined elements - image, text, color, and video - on the Amazon website. An interview was conducted with thirty regular Amazon.com consumers to understand their behavior. The results provided an understanding of consumer perception and feelings about web design through data categorization and in-depth analysis. The results reveal that consumers question several factors before buying, such as the credibility and trustworthiness they have for the brand, which is influenced by its web design. Therefore, brands need to use the four pre-defined elements to positively influence consumers at the time of purchase and segment their audience to understand the type of consumer and, consequently, each element's impact
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