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Impact of digital assistant attributes on millennials' purchasing intentions: a multi-group analysis using PLS-SEM, artificial neural network and fsQCA
Get PDFThe rising population of millennials, coupled with Digital Assistants (DA) and online purchasing trends among consumers have gained increasing attention by global marketers. The study evaluates the influence of DA attributes on the purchasing intention (PUI) of millennials. A combined approach of PLS-SEM, Artificial Neural Network (ANN) and Fuzzy-set Qualitative Comparative Analysis (fsQCA) is used to predict the PUI of 345 millennials. Also, multi-group analysis is employed to uncover the influence of gender on the relationship between PUI and DA attributes. The findings suggest that DA attributes may amplify purchasing intention among millennials, especially through perceived interactivity and anthropomorphism. Further, the moderating role of gender was found significant on the inter-relationship of perceived interactivity and PUI. This research is a pioneer study in the area of artificial intelligence, conversational commerce, DA and AI-powered chatbots. This study will help marketers and practitioners to predict millennial purchasing intentions. An evaluation of this paper may help them to foster immersive and effective engagement through DA
Artificial Intelligence as an enabler of quick and effective production repurposing manufacturing: an exploratory review and future research propositions
Get PDFThe outbreak of Covid-19 created disruptions in manufacturing operations. One of the most serious negative impacts is the shortage of critical medical supplies. Manufacturing firms faced pressure from governments to use their manufacturing capacity to repurpose their production for meeting the critical demand for necessary products. For this purpose, recent advancements in technology and artificial intelligence (AI) could act as response solutions to conquer the threats linked with repurposing manufacturing (RM). The study’s purpose is to investigate the significance of AI in RM through a systematic literature review (SLR). This study gathered around 453 articles from the SCOPUS database in the selected research field. Structural Topic Modeling (STM) was utilized to generate emerging research themes from the selected documents on AI in RM. In addition, to study the research trends in the field of AI in RM, a bibliometric analysis was undertaken using the R-package. The findings of the study showed that there is a vast scope for research in this area as the yearly global production of articles in this field is limited. However, it is an evolving field and many research collaborations were identified. The study proposes a comprehensive research framework and propositions for future research development
A comprehensive analysis of the role of artificial intelligence and machine learning in modern digital forensics and incident response
Get PDFIn the dynamic landscape of digital forensics, the integration of Artificial Intelligence (AI) and Machine Learning (ML) stands as a transformative technology, poised to amplify the efficiency and precision of digital forensics investigations. However, the use of ML and AI in digital forensics is still in its nascent stages. As a result, this paper gives a thorough and in-depth analysis that goes beyond a simple survey and review. The goal is to look closely at how AI and ML techniques are used in digital forensics and incident response. This research explores cutting-edge research initiatives that cross domains such as data collection and recovery, the intricate reconstruction of cybercrime timelines, robust big data analysis, pattern recognition, safeguarding the chain of custody, and orchestrating responsive strategies to hacking incidents. This endeavour digs far beneath the surface to unearth the intricate ways AI-driven methodologies are shaping these crucial facets of digital forensics practice. While the promise of AI in digital forensics is evident, the challenges arising from increasing database sizes and evolving criminal tactics necessitate ongoing collaborative research and refinement within the digital forensics profession. This study examines the contributions, limitations, and gaps in the existing research, shedding light on the potential and limitations of AI and ML techniques. By exploring these different research areas, we highlight the critical need for strategic planning, continual research, and development to unlock AI's full potential in digital forensics and incident response. Ultimately, this paper underscores the significance of AI and ML integration in digital forensics, offering insights into their benefits, drawbacks, and broader implications for tackling modern cyber threats
Age-hypogamy, emotional intelligence, sexual self-efficacy, and subjective happiness associations
Get PDFResearch examining age-gap relationships is sparse, particularly on women who date younger men. Using a content analysis consisting of non-parametric statistical analysis, we investigated age-hypogamy (with male partners approximately 7-10 years younger) and age homogamy with levels of emotional intelligence (E.I.), sexual self-efficacy (SSE), and subjective happiness (S.H.). Twenty-four women were recruited via social media platforms. Seventeen women in age-hypogamy relationships had a mean age = 45.86 years (SD = 4.47), and seven women in age-homogamy relationships had a mean age = 42.34 years (SD = 9.04) with an age range for both groups between 25 and 57 years. Results suggested that age-hypogamy relationships scored higher on levels of E.I., S.H., and SSE when compared to women in age-homogamy relationships. Since SSE, E.I., and S.H. are associated with fulfilling intimate relationships, this study questions the preconceived notion that age-hypogamy relationships are any less fulfilling or successful than those in age-homogamy relationships. Future research among a larger and more diverse cohort in age gap relationships is needed to confirm the unique qualities of this population
Trans vocabularies: topics, clashes, and affordances in YouTube streaming wars
Get PDFAfter decades of invisibility in the media, trans content creators have established popular 6 channels on YouTube and other streaming platforms. This article investigates channels from Western and non-Western locations to understand their priorities and interests from a comparative perspective. Applying a word cloud analysis and an LDA topic analysis, this study identified creators’ preferred topics and occasional conflicts while allowing many insights into an emerging and diversifying trans sphere online. As creators have demonstrated varying levels of engagement in a context of mainstream media backlash and radical ideologies, the ability to generate common vocabularies within the trans community worldwide demonstrates an emerging and complex communicative power present on multiple fronts
Young Europeans’ constructions and discussions of migrancy and racism
Get PDFThis chapter [9] considers how young people in Europe - of both migrant and non-migrant origins - construct attitudes towards migrants and refugees. We argue that accessing the voices of young people may provide necessary and significant starting points for the development of systems of policy and practice for migrant education. We are particularly focused on how these young people articulated their discussions about migrancy and racism, and how they utilised contextual resources to develop and elaborate their arguments, rather than what particular view they came to. We focus on the necessity of supporting young people in discussing their values and experiences in a deliberative context, following their specific contingent concerns, and using the vocabulary and terms they use. Deliberation with peers promotes the growth of personal development and an inclusive culture, respecting and including heritages and the marginalised groups. We argue that simply having discussions improves understanding and awareness, leading to personal development. We thus suggest there needs to be a greater focus on the processes and structures that ensure group discussion, and a curricular requirement to discuss issues of migrancy and racism, at least within the European context. We illustrate how such discussions can be developed and supported to focus on issues of social justice and equality, particularly in the data analysed with reference to racism in society, and the treatment of refugees and migrants. We shows the immediacy and news-led focus of the subjects of discussion, but also demonstrate in many cases that young people can analyse their own and their family’s experiences, or will listen to, and appreciate, the experiences of members of their discussion group and friends who have experiences of racism and discrimination, and that many young people – clearly a substantial majority – empathise with them
Political economy of artificial intelligence: critical reflections on Big Data market, economic development and data society
No full textThis book explores how artificial intelligence, the platform economy, and big data will impact economic development and societal change. It outlines how artificial intelligence is used as a capitalist tool that aids the corporate monopoly and creates alienating development. The ways in which artificial intelligence effects governance, economies, and global societies is also discussed, with particular attention given to how it undermines various forms of democracy.
This book aims to challenge established theories on artificial intelligence and technological singularity and highlight how they create new forms of capital accumulation. It will be relevant to students and researchers interested in the economic and social impact of artificial intelligence
Road surface analysis through machine learning techniques
Get PDFRoads are an important part of transporting goods and products from one place to another. In developing countries, the main challenge is to maintain road conditions regularly. Roads can deteriorate from time to time. Monitoring the conditions of the roads, which may degrade with time, is very difficult, resulting in a delay in transportation and damage to the vehicles moving on the roads. Poor road conditions cause road accidents. A model is being proposed to monitor the conditions of the road surface by smartphone sensors. Accelerometer, gyroscope, and GPS sensors are deployed in the mobile phones, which will help to collect data on the road conditions. After collecting the data about the road conditions, various machine learning approaches, such as supervised, multi-layered, and multiclass, are applied to data filtration. Road conditions are divided into three categories to achieve this methodology: potholes, deep traverse cracks, and smooth roads.This categorization helped in analyzing the road surface condition through smartphone sensors over all three axes instead of taking it over a single axis. Neural networks helped analyze data or road conditions more accurately than Decision Tree and SVM
Making of intimate capitalism: from cultrural economy to creative and cultural industries
No full textThis chapter conceptualises ‘intimate capitalism’. It develops the concept of ‘intimate capitalism’, which is a process wherein workers put all labour and work overtime as they feel intimate with the affective processes of production and work within a cultural setup. Intimate capitalism creates conditions where the market economy interacts with the objective and subjective realms of the everyday lives of people within intimate social, religious, and cultural contexts. Creative and cultural industries create conditions for the growth of ‘intimate capitalism’ in the name of the cultural economy
The whole thing needs a shake-up: a mixed method study examining teachers’ perspectives on social and emotional skills in schools
Get PDFThis study employed an explanatory sequential design to investigate how teachers' social and emotional capacities and schooling stage impact beliefs about Social and Emotional Learning (SEL). 109 primary and 72 secondary teachers completed surveys assessing emotional traits, comfort, and commitment to SEL. Results showed that relational capacity, the ability to form positive relationships, predicted comfort in promoting positive SEL beliefs, while self-compassion predicted commitment to SEL. Comfort with SEL was higher among primary teachers, indicating a schooling stage effect. Interviews with 8 teachers revealed that identity influenced SEL provision, while beliefs conflicted with job demands, highlighting areas for future research