Zheming Yang and Wen Ji
The multiple factors of intelligence measurement are critical in intelligent science. The intelligence measurement is typically built as a model based on multiple factors. The…
Abstract
Purpose
The multiple factors of intelligence measurement are critical in intelligent science. The intelligence measurement is typically built as a model based on multiple factors. The different agent is generally difficult to measure because of the uncertainty between multiple factors. The purpose of this paper is to solve the problem of uncertainty between multiple factors and propose an effective method for universal intelligence measurement for the different agents.
Design/methodology/approach
In this paper, the authors propose a universal intelligence measurement method based on meta-analysis for crowd network. First, the authors get study data through keywords in the database and delete the low-quality data. Second, they compute the effect value by odds ratio, relative risk and risk difference. Then, they test the homogeneity by Q-test and analyze the bias by funnel plots. Third, they select the fixed effect and random effect as a statistical model. Finally, through the meta-analysis of time, complexity and reward, the weight of each factor in the intelligence measurement is obtained and then the meta measurement model is constructed.
Findings
This paper studies the relationship among time, complexity and reward through meta-analysis and effectively combines the measurement of heterogeneous agents such as human, machine, enterprise, government and institution.
Originality/value
This paper provides a universal intelligence measurement model for crowd network. And it can provide a theoretical basis for the research of crowd science.
Details
Keywords
Julia Slupska and Leonie Maria Tanczer
Technology-facilitated abuse, so-called “tech abuse,” through phones, trackers, and other emerging innovations, has a substantial impact on the nature of intimate partner violence…
Abstract
Technology-facilitated abuse, so-called “tech abuse,” through phones, trackers, and other emerging innovations, has a substantial impact on the nature of intimate partner violence (IPV). The current chapter examines the risks and harms posed to IPV victims/survivors from the burgeoning Internet of Things (IoT) environment. IoT systems are understood as “smart” devices such as conventional household appliances that are connected to the internet. Interdependencies between different products together with the devices' enhanced functionalities offer opportunities for coercion and control. Across the chapter, we use the example of IoT to showcase how and why tech abuse is a socio-technological issue and requires not only human-centered (i.e., societal) but also cybersecurity (i.e., technical) responses. We apply the method of “threat modeling,” which is a process used to investigate potential cybersecurity attacks, to shift the conventional technical focus from the risks to systems toward risks to people. Through the analysis of a smart lock, we highlight insufficiently designed IoT privacy and security features and uncover how seemingly neutral design decisions can constrain, shape, and facilitate coercive and controlling behaviors.
Details
Keywords
Jing Liu, Zhiwen Pan, Jingce Xu, Bing Liang, Yiqiang Chen and Wen Ji
With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a…
Abstract
Purpose
With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a growing demand for developing a universal intelligence measurement so that the intelligence of artificial intelligence systems can be evaluated. This paper aims to propose a more formalized and accurate machine intelligence measurement method.
Design/methodology/approach
This paper proposes a quality–time–complexity universal intelligence measurement method to measure the intelligence of agents.
Findings
By observing the interaction process between the agent and the environment, we abstract three major factors for intelligence measure as quality, time and complexity of environment.
Originality/value
This paper proposes a calculable universal intelligent measure method through considering more than two factors and the correlations between factors which are involved in an intelligent measurement.
Details
Keywords
Xiaoni Wang, Zhiwen Pan, Zhouxia Li, Wen Ji and Feng Yang
This paper aims to optimize and evaluating the performance of the crowd networks through analyzing their information sharing patterns. That is, in a crowd network, the qualities…
Abstract
Purpose
This paper aims to optimize and evaluating the performance of the crowd networks through analyzing their information sharing patterns. That is, in a crowd network, the qualities of accomplishing tasks are highly dependent on the effective information sharing among intelligent subjects within the networks. Hence, proposing an adaptive information-sharing approach can help improve the performance of crowd networks on accomplishing tasks that are assigned to them.
Design/methodology/approach
This paper first introduces the factors that affect effectiveness of information-sharing pattern: the network topology, the resources owned by intelligent subjects and the degree of information demand. By analyzing the correlation between these factors and the performance of crowd networks, an Adaptive Information Sharing Approach for Crowd Networks (AISCN approach) is proposed. By referring to information needed for accomplishing the historical tasks that are assigned to a crowd network, the AISCN approach can explore the optimized information-sharing pattern based on the predefined composite objective function. The authors implement their approach on two crowd networks including bee colony and supply chain, to prove the effectiveness of the approach.
Findings
The shared information among intelligent subjects affects the efficiency of task completion in the crowd network. The factors that can be used to describe the effectiveness of information-sharing patterns include the network topology, the resources owned by intelligent subjects and the degree of information demand. The AISCN approach used heuristic algorithm to solve a composite objective function which takes all these factors into consideration, so that the optimized information-sharing pattern can be obtained.
Originality/value
This paper introduces a set of factors that can be used to describe the correlation between information-sharing pattern and performance of crowd network. By quantifying such correlation based on these factors, this paper proposes an adaptive information-sharing approach which can explore the optimized information-sharing pattern for a variety of crowd networks. As the approach is a data-driven approach that explores the information-sharing pattern based on the network’s performance on historical tasks and network’s characteristics, it is adaptive to the dynamic change (change of incoming tasks, change of network characteristics) of the target crowd network. To ensure the commonality of the information-sharing approach, the proposed approach is not designed for a specific optimization algorithm. In this way, during the implementation of the proposed approach, heuristic algorithms can be chosen according to the complexity of the target crowd network.
Details
Keywords
Jassim Happa and Michael Goldsmith
Several attack models attempt to describe behaviours of attacks with the intent to understand and combat them better. However, all models are to some degree incomplete. They may…
Abstract
Purpose
Several attack models attempt to describe behaviours of attacks with the intent to understand and combat them better. However, all models are to some degree incomplete. They may lack insight about minor variations about attacks that are observed in the real world (but are not described in the model). This may lead to similar attacks being classified as the same type of attack, or in some cases the same instance of attack. The appropriate solution would be to modify the model or replace it entirely. However, doing so may be undesirable as the model may work well for most cases or time and resource constraints may factor in as well. This paper aims to explore the potential value of adding information about attacks and attackers to existing models.
Design/methodology/approach
This paper investigates used cases of minor variations in attacks and how it may and may not be appropriate to communicate subtle differences in existing attack models through the use of annotations. In particular, the authors investigate commonalities across a range of existing models and identify where and how annotations may be helpful.
Findings
The authors propose that nuances (of attack properties) can be appended as annotations to existing attack models. Using annotations appropriately should enable analysts and researchers to express subtle but important variations in attacks that may not fit the model currently being used.
Research limitations/implications
This work only demonstrated a few simple, generic examples. In the future, the authors intend to investigate how this annotation approach can be extended further. Particularly, they intend to explore how annotations can be created computationally; the authors wish to obtain feedback from security analysts through interviews, identify where potential biases may arise and identify other real-world applications.
Originality/value
The value of this paper is that the authors demonstrate how annotations may help analysts communicate and ask better questions during identification of unknown aspects of attacks faster,e.g. as a means of storing mental notes in a structured manner, especially while facing zero-day attacks when information is incomplete.
Details
Keywords
Morteza Moradi, Mohammad Moradi, Farhad Bayat and Adel Nadjaran Toosi
Human or machine, which one is more intelligent and powerful for performing computing and processing tasks? Over the years, researchers and scientists have spent significant…
Abstract
Purpose
Human or machine, which one is more intelligent and powerful for performing computing and processing tasks? Over the years, researchers and scientists have spent significant amounts of money and effort to answer this question. Nonetheless, despite some outstanding achievements, replacing humans in the intellectual tasks is not yet a reality. Instead, to compensate for the weakness of machines in some (mostly cognitive) tasks, the idea of putting human in the loop has been introduced and widely accepted. In this paper, the notion of collective hybrid intelligence as a new computing framework and comprehensive.
Design/methodology/approach
According to the extensive acceptance and efficiency of crowdsourcing, hybrid intelligence and distributed computing concepts, the authors have come up with the (complementary) idea of collective hybrid intelligence. In this regard, besides providing a brief review of the efforts made in the related contexts, conceptual foundations and building blocks of the proposed framework are delineated. Moreover, some discussion on architectural and realization issues are presented.
Findings
The paper describes the conceptual architecture, workflow and schematic representation of a new hybrid computing concept. Moreover, by introducing three sample scenarios, its benefits, requirements, practical roadmap and architectural notes are explained.
Originality/value
The major contribution of this work is introducing the conceptual foundations to combine and integrate collective intelligence of humans and machines to achieve higher efficiency and (computing) performance. To the best of the authors’ knowledge, this the first study in which such a blessing integration is considered. Therefore, it is believed that the proposed computing concept could inspire researchers toward realizing such unprecedented possibilities in practical and theoretical contexts.
Details
Keywords
Kun Sang, Pei Ying Woon and Poh Ling Tan
Against the background of the popularity of social media and heritage tourism, this study aims to focus on world heritage sites, proposing a method to examine and compare the…
Abstract
Purpose
Against the background of the popularity of social media and heritage tourism, this study aims to focus on world heritage sites, proposing a method to examine and compare the digital spatial footprints left by tourists using geographic information systems.
Methodology
By analyzing user-generated content from social media, this research explores how digital data shapes the destination image of WHS and the spatial relationships between the components of this destination image. Drawing on the cognitive-affective model (CAM), it investigates through an analysis of integrated data with more than 20,000 reviews and 2,000 photos.
Innovation
The creativity of this research lies in the creation of a comprehensive method that combines text and image analytics with machine learning and GIS to examine spatial relationships within the CAM framework in a visual manner.
Results
The results reveal tourists' perceptions, emotions, and attitudes towards George Town and Malacca in Malaysia, highlighting several key cognitive impressions, such as history, museums, churches, sea, and food, as well as the primary emotions expressed. Their distributions and relationships are also illustrated on maps.
Implications
Tourism practitioners, government officials, and residents can gain valuable insights from this study. The proposed methodology provides a valuable reference for future tourism studies and help to achieve a sustainable competitive advantage for other heritage destinations.
Details
Keywords
Theresa Eriksson, Alessandro Bigi and Michelle Bonera
This paper explores if and how Artificial Intelligence can contribute to marketing strategy formulation.
Abstract
Purpose
This paper explores if and how Artificial Intelligence can contribute to marketing strategy formulation.
Design/methodology/approach
Qualitative research based on exploratory in-depth interviews with industry experts currently working with artificial intelligence tools.
Findings
Key themes include: (1) Importance of AI in strategic marketing decision management; (2) Presence of AI in strategic decision management; (3) Role of AI in strategic decision management; (4) Importance of business culture for the use of AI; (5) Impact of AI on the business’ organizational model. A key consideration is a “creative-possibility perspective,” highlighting the future potential to use AI not only for rational but also for creative thinking purposes.
Research limitations/implications
This work is focused only on strategy creation as a deliberate process. For this, AI can be used as an effective response to the external contingencies of high volumes of data and uncertain environmental conditions, as well as being an effective response to the external contingencies of limited managerial cognition. A key future consideration is a “creative-possibility perspective.”
Practical implications
A practical extension of the Gartner Analytics Ascendancy Model (Maoz, 2013).
Originality/value
This paper aims to contribute knowledge relating to the role of AI in marketing strategy formulation and explores the potential avenues for future use of AI in the strategic marketing process. This is explored through the lens of contingency theory, and additionally, findings are expressed using the Gartner analytics ascendancy model.
Details
Keywords
Johan Erlank Warnick, Jace Pillay and Lucia Munongi
The risk factors related to the mental health issues of adolescents diagnosed with mild to moderate intellectual difficulties (MMID) are not consistently recognised in South…
Abstract
Purpose
The risk factors related to the mental health issues of adolescents diagnosed with mild to moderate intellectual difficulties (MMID) are not consistently recognised in South Africa. This paper aims to address the scarcity of literature by examining the risk factors linked to the mental health issues of adolescents with MMID.
Design/methodology/approach
Four hundred and fourteen participants were sampled from adolescent learners attending three special educational needs schools in Gauteng, South Africa. The selected sample included 275 male and 139 female participants with a median age of 16.5 years. The three schools represented Grade 8 with 177 learners and Grade 9 with 237 learners. Data were collected through a biographical questionnaire and an Adverse Child Experiences Questionnaire. A quantitative approach was used to identify the risk factors impacting the mental health of adolescents with MMID. The findings were used to propose intervention programmes for the support of adolescents diagnosed with MMID.
Findings
The findings suggest that risk factors for mental health difficulties issues among adolescents with MMID include family dysfunction, along with experiences of physical, sexual and verbal abuse as well as emotional and physical neglect. The recommendations stemming from the findings advocate empowering teachers, parents and caregivers to provide support for the mental health of learners with MMID.
Originality/value
The study makes a valuable contribution to reducing the existing gap in the literature regarding risk factors impacting the mental health of adolescents with MMID in South Africa. The study served as a platform for adolescents diagnosed with MMID to articulate their challenges. This cohort is occasionally marginalised and this research acts as an active contribution to research that focuses on their experiences. Their insights are crucial for enhancing intervention programmes and promoting their overall well-being.
Details
Keywords
Mohammad Shahidul Islam, Fariba Azizzadeh, Md. Shamimul Islam, Ummul Wara Adrita, Arif Hossain Mazumder and Rahma Akhter
This study investigates the socio-psychological and network dynamics influencing women’s entrepreneurial journeys in Bangladesh. It focuses on understanding how societal…
Abstract
Purpose
This study investigates the socio-psychological and network dynamics influencing women’s entrepreneurial journeys in Bangladesh. It focuses on understanding how societal expectations, financial barriers and emotional resilience shape these women’s entrepreneurial experiences and outcomes.
Design/methodology/approach
A hermeneutic phenomenological approach was employed, involving in-depth interviews and focus group discussions with 15 women entrepreneurs from various industries in Bangladesh. Thematic analysis was used to identify critical patterns and themes in their experiences.
Findings
Six major themes emerged from the data: societal biases and constraints, financial hurdles, balancing family and work, psychosocial processes, the impact of social networks and strategic interventions. The findings not only reveal the deeply ingrained gender biases, limited access to financial resources and the emotional toll of juggling professional and domestic responsibilities but also underscore the remarkable resilience of these women in the face of such challenges.
Practical implications
The study offers actionable insights for policymakers, support organizations and researchers. It underscores the urgent need for gender-sensitive financial policies, restructuring mentorship programs to include emotional support and developing cultural awareness campaigns to challenge societal norms that hinder women entrepreneurs.
Originality/value
This research uniquely contributes to the underexplored psychosocial dimensions of women’s entrepreneurship in Bangladesh. It highlights how emotional resilience and societal dynamics influence entrepreneurial success, offering valuable insights for enhancing support systems for women entrepreneurs.