Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study
رانندگان ، موانع و ملاحظات اجتماعی برای پذیرش هوش مصنوعی در مشاغل و مدیریت: یک مطالعه عالی-2020
The number of academic papers in the area of Artificial Intelligence (AI) and its applications across business and management domains has risen significantly in the last decade, and that rise has been followed by an increase in the number of systematic literature reviews. The aim of this study is to provide an overview of existing systematic reviews in this growing area of research and to synthesise their findings related to enablers, barriers and social implications of the AI adoption in business and management. The methodology used for this tertiary study is based on Kitchenham and Charter’s guidelines , resulting in a selection of 30 reviews published between 2005 and 2019 which are reporting results of 2,021 primary studies. These reviews cover the AI adoption across various business sectors (healthcare, information technology, energy, agriculture, apparel industry, engineering, smart cities, tourism and transport), management and business functions (HR, customer services, supply chain, health and safety, project management, decisionsupport, systems management and technology acceptance). While the drivers for the AI adoption in these areas are mainly economic, the barriers are related to the technical aspects (e.g. availability of data, reusability of models) as well as the social considerations such as, increased dependence on non-humans, job security, lack of knowledge, safety, trust and lack of multiple stakeholders’ perspectives. Very few reviews outside of the healthcare management domain consider human, organisational and wider societal factors and implications of the AI adoption. Most of the selected reviews are recommending an increased focus on social aspects of AI, in addition to more rigorous evaluation, use of hybrid approaches (AI and non-AI) and multidisciplinary approaches to AI design and evaluation. Furthermore, this study found that there is a lack of systematic reviews in some of the AI early adopter sectors such as financial industry and retail and that the existing systematic reviews are not focusing enough on human, organisational or societal implications of the AI adoption in their research objectives.
Keywords: artificial intelligence | business | machine learning | management | systematic literature review | tertiary study
Combining conventional and participatory approaches to identify and prioritise management and health-related constraints to smallholder pig production in San Simon, Pampanga, Philippines
تلفیق رویکردهای مرسوم و مشارکتی برای شناسایی و اولویت بندی مدیریت و محدودیتهای مرتبط با سلامتی در تولید خوک های خرده فروش در سن سیمون ، پامبانگا ، فیلیپین-2020
Pork is the main meat produced and consumed in the Philippines. The majority of pigs are raised by smallholders who experience a range of constraints to their pig production. This study presents the findings of the first part of an overarching project that used an Ecohealth approach and aimed to improve the production and competitiveness of the smallholder pig system in an area of the Philippines. A participatory approach was embraced, combining conventional and participatory epidemiology methods followed by a stakeholder discussion. The first aim was to identify management and health-related constraints to pig production among smallholder famers in San Simon, Pampanga, Philippines. The second aim was for the project team and stakeholders to jointly prioritise activities for the immediate future to address these constraints. Key management and health-related constraints identified included inadequate water supply to pigs, particularly lactating and gestating sows, and a range of feeding-related issues. Diarrhoea was recognised as the disease syndrome of highest priority and limited record keeping meant that farmers were unable to assess the productivity and profitability of their pig farming enterprises. Actions jointly prioritised by stakeholders and the project team were: the appointment of a project coordinator within each barangay; conduct two sets of seminars, the first covering water and nutrition and the second piglet management and diarrhoea, to be delivered by technical experts but with farmer “trusted sources” also sharing their experiences; development of easily understandable leaflets and posters covering key technical information; promotion of nipple drinkers attached to five-gallon water containers and creep boxes for piglets, and conduct of a record keeping workshop with a small group of innovative farmers to develop a useful and usable tool for record keeping. The use of multiple approaches to data-gathering enabled triangulation of study findings. Without any one of these components the understanding of the pig production system would have been less complete and it is possible that the proposed actions would not have been as well-tailored to the needs of the farmers. The participatory approach, in particular the stakeholder discussion, provided the opportunity to embrace the “deciding together” and “acting together” stances of participation rather than the lower “information giving” stance, thereby giving stakeholders greater ownership of the future activities of the overarching project and beyond.
Keywords: Philippines | Pig | Smallholder | Constraints | Participatory epidemiology | Ecohealth
Fast Authentication and Progressive Authorization in Large-Scale IoT: How to Leverage AI for Security Enhancement
احراز هویت سریع و مجوز پیشرو در اینترنت اشیا با مقیاس بزرگ: نحوه استفاده از هوش مصنوعی برای تقویت امنیت-2020
Security provisioning has become the most important design consideration for large-scale Internet of Things (IoT) systems due to their critical roles in supporting diverse vertical applications by connecting heterogenous devices, machines, and industry processes. Conventional authentication and authorization schemes are insufficient to overcome the emerging IoT security challenges due to their reliance on both static digital mechanisms and computational complexity for improving security levels. Furthermore, the isolated security designs for different layers and link segments while ignoring the overall protection leads to cascaded security risks as well as growing communication latency and overhead. In this article, we envision new artificial intelligence (AI)-enabled security provisioning approaches to overcome these issues while achieving fast authentication and progressive authorization. To be more specific, a lightweight intelligent authentication approach is developed by exploring machine learning at the base station to identify the prearranged access time sequences or frequency bands or codes used in IoT devices. Then we propose a holistic authentication and authorization approach, where online machine learning and trust management are adopted for achieving adaptive access control. These new AI-enabled approaches establish the connections between transceivers quickly and enhance security progressively so that communication latency can be reduced and security risks are well controlled in large-scale IoT systems. Finally, we outline several areas for AI-enabled security provisioning for future research.
The use of big data and data mining in nurse practitioner clinical education
استفاده از داده های بزرگ و داده کاوی در آموزش بالینی پزشکان -2020
Nurse practitioner (NP) faculty have not fully used data collected in NP clinical education for data mining. With current advances in database technology including data storage and computing power, NP faculty have an opportunity to data mine enormous amounts of clinical data documented by NP students in electronic clinical management systems. The purpose of this project was to examine the use of big data and data mining from NP clinical education and to establish a foundation for competency-based education. Using a data mining knowledge discovery process, faculty are able to gain increased understanding of clinical practicum experiences to inform competency-based NP education and the use of entrusted professional activities for the future.
Keywords: Big data | Data mining | Nurse practitioner clinical education | Competency-based education | Nurse Practitioner Core Competencies | Entrustable professional activities
In law we trust: Lawyer CEOs and stock liquidity
اعتماد ما به قانون : مدیرعامل وکالت و نقدینگی سهام-2020
I find that about 8.5% of firms in the sample of S&P 1500 firms are run by CEOs with a law degree (lawyer CEOs) and these firms have higher stock market liquidity than non-lawyer run CEO firms. I also find stock market liquidity improves following the appointment of lawyer CEOs. Lawyer CEOs improve stock market liquidity because they improve the firm’s information environment and reduce firm risk. Firms led by CEOs with legal expertise are associated with less stock price delay, weaker market reactions to corporate earnings announcements, and lower insider trading profits. Overall, this paper highlights the importance of CEO characteristics in enhancing financial market quality.
Keywords: Stock market liquidity | CEOs | Legal education | Insider trading
Data mining of customer choice behavior in internet of things within relationship network
داده کاوی رفتار انتخاب مشتری در اینترنت اشیایی که در شبکه ارتباطی قرار دارند-2020
Internet of Things has changed the relationship between traditional customer networks, and traditional information dissemination has been affected. Smart environment accelerates the changes in customer behaviors. Apparently, the new customer relationship network, benefitted from the Internet of Things technology, will imperceptibly influence customer choice behaviors for the cyber intelligence. In this work, we selected 298 customers click browsing records as training data, and collected 50 customers who used the platform for the first time as research objects. and use the smart customer relationship network correspond to cyber intelligence to build the customer intelligence decision model in Internet of Things. The results showed that the MAE (Mean Absolute Deviation) of the customer trust evaluation model constructed in this study is 0.215, 45% improvement over the traditional equal assignment method. In addition, customers consumer experience can be enhanced with the support of data mining technology in cyber intelligence. Our work indicated the key to build eliminates confusion in customer choice behavior mechanism is to establish a consumer-centric, effective network of customers and service providers, and to be supported by the Internet of Things, big data analysis, and relational fusion technologies.
Keywords: Internet of things | Customer relationship network | Decision making | Recommendation | Fusion algorithm
From elite-driven to community-based governance mechanisms for the delivery of public goods from land management
از مکانیسم های حاکم بر نخبگان گرفته تا مکانیسم های حاکم بر جامعه برای تحویل کالاهای عمومی از مدیریت زمین-2020
Several non-governmental initiatives have emerged in the Czech Republic in recent years with the aim to organise the provision of public goods or ecosystem services from agriculture and forestry. These initiatives are usually started by activists (elites) and take forms such as foundations or trust funds, but often present themselves as collective actions of communal interests. This paper sets out to present four cases of such efforts and to show their common and contrasting features in light of their relevance to local needs and possible integration in the future CAP framework. A particular focus is on the community-based character of these initiatives for the provision of public goods. This is done by examining the necessary conditions for the success of collectively managed common pool resources. The research shows that elite-driven non-governmental organisations often emerge because of a lack of interest on the part of public bodies and because local communities do not have the capacity to set up a collective action for the provision of environmentally and socially “beneficial outcomes” (ESBO). The investigated NGOs, however, soon came into conflict with non-involved actors. To improve the governance mechanism, an extension towards a community-based collective action is proposed. However, each step of such a transition is a challenge for the initiatives of the presented case studies. The first critical issue is to find a common interest among actors. Similarly, “sharing power” represents a struggle which consequently delays progress in creating effective internal governance. The difficulty in progressing towards community-based collective action is amplified by the uncertainty concerning property rights induced by the activities of the NGOs and unfavourable socioeconomic and institutional conditions. Finding that the private initiatives are far from being able to transform into community-based collective action, we propose to launch a measure of institutional funding for the coordination and management of their projects – similar to LEADER but more concentrated in scope.
Keywords: Public goods | Ecosystem services | Common pool resources | Non-governmental initiatives | Governance mechanism | Community-based collective action
Facilitating collaboration in forest management: Assessing the benefits of collaborative policy innovations
تسهیل همکاری در مدیریت جنگل: ارزیابی مزایای نوآوری های سیاست مشارکتی-2020
Collaborative governance and landscape approaches have become a more prevalent in public land management in the United States in the face of increasing ecological and societal complexity and decreasing government resources and capacity. In this era of devolution and social-ecological change, there is a growing need for policy approaches that facilitate partnerships and participatory approaches to land management. One unique policy that emphasizes collaboration and large-landscape restoration on US federal forestlands is the Collaborative Forest Landscape Restoration Program (CFLRP), established in 2009 to accelerate the pace and scale of forest restoration. The policy included novel characteristics such as a decade-long commitment to landscapes and formal requirements for collaboration. This program presented an opportunity to assess how this policy affected collaboration and the factors that led to differential policy implementation. We conducted 89 interviews across all 23 CFLRP projects with internal agency staff and external collaborators on each project. We found that the CFLRP generated a variety of benefits related to collaboration, including increased trust and stronger relationships, increased collaborative partner influence, decreased litigation and conflict, and increased capacity to accomplish work; however, there were also challenges associated with the program, including thetime-intensive nature of collaboration and the lack of industry or contractors. Various local factors affected collaborative outcomes under the policy, including staff turnover and capacity, local leadership, and collaborative history. Successful collaborative outcomes were widespread under the CFLRP, and from this, we draw implications for the broader environmental governance literature about the policy characteristics that facilitate collaboration and the other institutional variables that may require attention in this context.
Keywords: Collaborative governance | Community-based forestry | Adaptive governance | Ecological | Restoration | Policy design
Fisheries co-management in hilsa shad sanctuaries of Bangladesh: Early experiences and implementation challenges
مدیریت شیلات در پناهگاه های هیلسا از بنگلادش: تجربیات اولیه و چالش های اجرایی-2020
Community-based fisheries management has long been practiced in the management of the inland fisheries of Bangladesh. However, formal coastal co-management has only been implemented recently in hilsa shad (Tenualosa ilisha) sanctuaries. The study analysed the pre-implementation processes, institutional arrangements, implementation activities, as well as challenges for fisheries co-management that are currently being implemented in the Padma-Meghna riverine-estuarine system. As a first step in establishing a co-management system in hilsa shad sanctuaries, communities (both fishing villages and fish landing centres) were selected for interventions. Co-management committees were formed from the community-village to district level with the defined tasks of developing plans and programs, implementing management rules and regulations, monitoring compliance, and creating awareness in a cost-effective manner among various stakeholders. Still, the operationalization of co-management in this large riverine-estuarine system is a challenging task. To overcome these challenges, several issues had to be considered through lessons learned from previously implemented community-based fisheries management projects in Bangladesh. To ensure that fisheries co-management is functional, the institutional framework needs to be flexible with support from local government institutions and NGOs. The boundary of the management unit needs to be clearly defined and community-based organization also needs a clear legal status. To make co-management sustainable, a relationship of trust and respect among comanagement partners needs to be developed and maintained. The effective implementation of fisheries comanagement will require an inclusive compensation scheme that will motivate stakeholders to comply and maintain fisheries management efforts through collective action.
Keywords: Hilsa sanctuaries | Co-management | Small-scale fisheries | Implementation challenges
AI Crimes: A Classification
جرایم هوش مصنوعی: طبقه بندی-2020
Intelligent and machine learning systems have infiltrated cyber-physical systems and smart cities with technologies such as internet of things, image processing, robotics, speech recognition, self-driving, and predictive maintenance. To gain user trust, such systems must be transparent and explainable. Regulations are required to control crimes associated with these technologies. Such regulations and legislations depend on the severity of the artificial intelligence (AI) crimes subject to these regulations, and on whether humans and/or intelligent systems are responsible for committing such crimes, and therefore can benefit from a classification tree of AI crimes. The aim of this paper to review prior work in ethics for AI, and classify AI crimes by producing a classification tree to assist in AI crime investigation and regulation.
Keywords: AI | classification tree | crimes | ethics | explainable AI | transparency | trust | privacy