scholarly journals Seasonal Losses in Capture Fisheries: Occurrence, Market Responses and Response Constraints

2020 ◽  
Vol 16 ◽  
Keyword(s):  
Artificial Intelligence ◽  
Seasonal Variation ◽  
Case Study Approach ◽  
Government Interventions ◽  
Technological Factors ◽  
Study Approach ◽  
Market Responses ◽  
Harvest Control Rule ◽  
Artificial Intelligence Systems

Seasonal losses have challenged capture fishery. Chellenges include difficulty market players to maintain production, and consumers to secure quality fish supply. This paper aims to confirm problems of seasonal fish loss and shows how this links to management. The study, conducted in 2016, followed a case study approach, carried out in seven locations: Palabuhanratu, Blanakan, Probolinggo, Sendangbiru, Pekalongan, Cilacap, and Pati. Interviews were done with fishers, fresh and processed fish traders, processors, consumers, each represented by ten respondents per location. Results show that respondents face problems of seasonal variation and respond with available options. Responses are constrained mainly by financial, facility, and technological factors. I is recommended then that problems and factors be addressed through a harvest control rule schemes. Within these schemes, the rule is described as aiming at (i) imposing harvest levels within the range sufficient to sustain stocks, (ii) avoiding fish deterioration in peak seasons, and (iii) allowing for manageable peak season oversupply to be stored in preparation for low seasons. Complementing to this rule, government interventions are necessary and this can be implemented in concrete actions such as strengthening capital to withstand fluctuations in income, introducing artificial intelligence systems to help market players make decisions.

scholarly journals EARLY EVIDENCE ON THE XBRL ADOPTION PROCESS IN MALAYSIA: DRIVERS AND CHALLENGES ON THE TECHNOLOGICAL PERSPECTIVE

2020 ◽  
Vol 8 (2) ◽  
pp. 957-968
Author(s):  
Azleen Ilias ◽  
Erlane K Ghani ◽  
Zubir Azhar
Keyword(s):  
Document Analysis ◽  
Relative Advantage ◽  
Adoption Process ◽  
Case Study Approach ◽  
Technological Factors ◽  
Study Approach ◽  
Early Evidence ◽  
Phase Compatibility ◽  
Technological Perspective

Purpose: This study aims to identify technological factors and how these factors influence the XBRL adoption process of the regulators in Malaysia. Methodology: This paper applied Rogers’s (1983) adoption process and DiPietro, Wiarda, and Fleischer’s (1990) Technological, Organisational, and Environmental (TOE) framework. The paper adopted a case study approach consisting of an interview and document analysis. The data has been analysed with thematic analysis. Results: This paper shows ten (10) factors within the technological perspective—the relative advantage as driving factor while trialability are the challenging factor in the knowledge and persuasion phase. In the decision-making phase, compatibility of XBRL taxonomy and stability production of XBRL instance documents are the driving factors whilst stability of XBRL taxonomy, standardised XBRL taxonomy, standardised XBRL submission, availability of tools and software and observability are challenges in the XBRL adoption process. In the implementation and confirmation phase, the complexity of the XBRL taxonomy is considered a challenge in the XBRL adoption process. Implications: The findings in this paper serve as strategies to the other regulators that have plans to adopt XBRL as well as to attract the different government agencies to start with XBRL for reporting.

scholarly journals China’s AI Strike Force on COVID-19

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wilson Kia Onn Wong
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
Full Potential ◽  
Case Study Approach ◽  
Content Type ◽  
Study Approach ◽  
The World ◽  
Remarkable Progress ◽  
Made In

PurposeThis paper examines the methodical and highly efficacious manner in which China deployed its comprehensive AI (artificial intelligence) strategy to significantly stymie the spread of COVID-19 across the country.Design/methodology/approachThis study deploys a case-study approach, supported by the literature on existing and emerging AI and related technologies.FindingsThe onset of the COVID-19 pandemic has revealed to the world the remarkable progress China has made in AI and its accompanying ecosystem. More importantly, this outlier event demonstrates the surgical, hybridised manner in which China has utilised these emerging technologies in containing its spread (i.e. “AI Epidemiological Targeting”) and set itself on the path to unleashing their full potential (i.e. “AI Symbiosis Paradigm”). Nonetheless, China still needs to harness its rapidly advancing AI prowess in identifying COVID-19's pathogenesis and developing a proven vaccine.Originality/valueThis study presents a pioneering effort to analyse the deployment of AI and its ecosystem in the “war” against COVID-19.

scholarly journals Healthcare Professional Association Agency In Preparing For Artificial Intelligence: A Multi-Case Study Protocol (Preprint)

2021 ◽  
Author(s):  
Caitlin Gillan ◽  
Brian Hodges ◽  
David Wiljer ◽  
Mark Dobrow
Keyword(s):  
Artificial Intelligence ◽  
Healthcare Professional ◽  
Macro Level ◽  
Sense Making ◽  
Disruptive Technology ◽  
Case Study Approach ◽  
Study Approach ◽  
Healthcare Professions ◽  
Future Practice

UNSTRUCTURED Background The emergence of artificial intelligence (AI) in healthcare impacts on most aspects of our healthcare systems including consideration of employment, training, education, and professional regulation for healthcare professions. It is incumbent on healthcare professional associations (HPAs) to assist their membership in defining and preparing for AI-related change. HPAs, or the national groups convened to represent the interests of the members of a profession, hold a unique role in establishing and maintaining the socio-cultural, normative, and regulative elements of healthcare professions. The objective of this study is to examine how, when faced with AI as a disruptive technology, HPAs engage in sense-making and legitimization of change in order to support their membership in preparing for future practice. Methods An exploratory multi-case study approach will be employed. This study will be informed by normalization process theory (NPT), which suggests behavioural constructs required for complex change, providing a novel lens through which to consider the agency of macro-level actors in practice change. Four HPAs will be studied, with each representing an instrumental case and related fields, selected for their early consideration and adoption of AI technologies. Data collection will consist of key-informant interviews, observation of relevant meetings, and document review. Individual and collective sense-making activities and action toward change will be identified and characterized using stakeholder network mapping. A hybrid inductive/deductive model will be used for a concurrent thematic analysis, mapping emergent themes against the NPT framework to assess fit and identify areas of discordance. Discussion A linear cross-case analytic approach will be taken to present the data, highlighting both guidance for the implementation of AI and implications for the application of NPT at the macro level. The ability to inform consideration of AI will depend on the degree to which the engaged HPAs have considered this topic at the time of the study, and hence what priority it has been assigned within the HPA and what actions have been taken to consider or prepare for it. The fact that this may differ between HPAs and associated professions and practice environments will require consideration throughout the analysis. Ultimately, this protocol outlines a case study approach to understanding how, when faced with AI as a disruptive technology, HPAs engage in sense-making and legitimization of the change in order to support their membership in preparing for future practice.

scholarly journals Research and Practice of AI Ethics: A Case Study Approach Juxtaposing Academic Discourse with Organisational Reality

2021 ◽  
Vol 27 (2) ◽  
Author(s):  
Mark Ryan ◽  
Josephina Antoniou ◽  
Laurence Brooks ◽  
Tilimbe Jiya ◽  
Kevin Macnish ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Ethical Issues ◽  
Case Study Approach ◽  
Detailed Understanding ◽  
Research And Practice ◽  
Ethical Concerns ◽  
Study Approach ◽  
Ai Ethics ◽  
Applications Of Ai

AbstractThis study investigates the ethical use of Big Data and Artificial Intelligence (AI) technologies (BD + AI)—using an empirical approach. The paper categorises the current literature and presents a multi-case study of 'on-the-ground' ethical issues that uses qualitative tools to analyse findings from ten targeted case-studies from a range of domains. The analysis coalesces identified singular ethical issues, (from the literature), into clusters to offer a comparison with the proposed classification in the literature. The results show that despite the variety of different social domains, fields, and applications of AI, there is overlap and correlation between the organisations’ ethical concerns. This more detailed understanding of ethics in AI + BD is required to ensure that the multitude of suggested ways of addressing them can be targeted and succeed in mitigating the pertinent ethical issues that are often discussed in the literature.

scholarly journals Healthcare Professional Association Agency In Preparing For Artificial Intelligence: A Multi-Case Study Protocol

2020 ◽  
Author(s):  
Caitlin Gillan ◽  
Brian Hodges ◽  
David Wiljer ◽  
Mark Dobrow
Keyword(s):  
Artificial Intelligence ◽  
Healthcare Professional ◽  
Macro Level ◽  
Sense Making ◽  
Disruptive Technology ◽  
Case Study Approach ◽  
Study Approach ◽  
Healthcare Professions ◽  
Future Practice

Abstract BackgroundThe emergence of artificial intelligence (AI) in healthcare impacts on most aspects of our healthcare systems including consideration of employment, training, education, and professional regulation for healthcare professions. It is incumbent on healthcare professional associations (HPAs) to assist their membership in defining and preparing for AI-related change. HPAs, or the national groups convened to represent the interests of the members of a profession, hold a unique role in establishing and maintaining the socio-cultural, normative, and regulative elements of healthcare professions. The objective of this study is to examine how, when faced with AI as a disruptive technology, HPAs engage in sense-making and legitimization of change in order to support their membership in preparing for future practice.MethodsAn exploratory multi-case study approach will be employed. This study will be informed by normalization process theory (NPT), which suggests behavioural constructs required for complex change, providing a novel lens through which to consider the agency of macro-level actors in practice change. Four HPAs will be studied, with each representing an instrumental case and related fields, selected for their early consideration and adoption of AI technologies. Data collection will consist of key-informant interviews, observation of relevant meetings, and document review. Individual and collective sense-making activities and action toward change will be identified and characterized using stakeholder network mapping. A hybrid inductive/deductive model will be used for a concurrent thematic analysis, mapping emergent themes against the NPT framework to assess fit and identify areas of discordance. DiscussionA linear cross-case analytic approach will be taken to present the data, highlighting both guidance for the implementation of AI and implications for the application of NPT at the macro level. The ability to inform consideration of AI will depend on the degree to which the engaged HPAs have considered this topic at the time of the study, and hence what priority it has been assigned within the HPA and what actions have been taken to consider or prepare for it. The fact that this may differ between HPAs and associated professions and practice environments will require consideration throughout the analysis. Ultimately, this protocol outlines a case study approach to understanding how, when faced with AI as a disruptive technology, HPAs engage in sense-making and legitimization of the change in order to support their membership in preparing for future practice.

The adaptation of anthropomorphism and archetypes for marketing artificial intelligence

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gulnara Z. Karimova ◽  
Valerie Priscilla Goby
Keyword(s):  
Artificial Intelligence ◽  
Design Methodology ◽  
Consumer Trust ◽  
Case Study Approach ◽  
Content Type ◽  
Study Approach ◽  
Jungian Archetypes ◽  
Human Attributes

Purpose This paper aims to present an exploration of possible associations between the Jungian archetypes frequently used in marketing and three well-known products based on artificial intelligence (AI), namely, Sophia, Alexa and Articoolo. Design/methodology/approach The study conducted emotionalist interviews to gather thick data from 11 participants on how they conceptualize these AI-based products. In the absence of any existing relevant hypotheses, this paper attempts to build theory using a case study approach and qualitative analysis of interview narratives. Findings Despite the human attributes ascribed to these products, participants were principally concerned with their purpose, efficiency and the degree of trust which they felt could be accorded to the product. Anthropomorphism emerged as significant with participants making some associations with common archetypes traditionally exploited in marketing and this suggests a possible means of enhancing consumer trust in AI products. Originality/value Little research has been conducted on the marketing of AI and this study presents a timely identification of some potentially significant issues. As AI is intended to mimic some aspects of human intelligence, the role of the archetype in creating a personality to enhance trust may prove crucial in securing consumer confidence.

Overcoming Challenges of International Migration Research: A Case Study Approach in Southern Mexico

2016 ◽  
Vol 13 (1) ◽  
pp. 131-143
Author(s):  
Julie Boyles
Keyword(s):  
International Migration ◽  
Common Ground ◽  
Data Gathering ◽  
Ethnographic Case Study ◽  
Case Study Approach ◽  
Southern Mexico ◽  
Mixed Methods Approach ◽  
Study Approach ◽  
Migration Research

An ethnographic case study approach to understanding women’s actions and reactions to husbands’ emigration—or potential emigration—offers a distinct set of challenges to a U.S.-based researcher.  International migration research in a foreign context likely offers challenges in language, culture, lifestyle, as well as potential gender norm impediments. A mixed methods approach contributed to successfully overcoming barriers through an array of research methods, strategies, and tactics, as well as practicing flexibility in data gathering methods. Even this researcher’s influence on the research was minimized and alleviated, to a degree, through ascertaining common ground with many of the women. Research with the women of San Juan Guelavía, Oaxaca, Mexico offered numerous and constant challenges, each overcome with ensuing rewards.

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