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The purpose of this research is to systematically review the properties of supply chains demonstrating that they are complex systems, and that the management of supply chains is best achieved by steering rather than controlling these systems toward desired outcomes.

The research study was designed as both exploratory and explanatory. Data were collected from secondary sources using a comprehensive literature review process. In parallel with data collection, data were analyzed and synthesized.

The main finding is the introduction of an inductive framework for steering supply chains from a complex systems perspective by explaining why supply chains have properties of complex systems and how to deal with their complexity while steering them toward desired outcomes. Complexity properties are summarized in four inter-dependent categories: Structural, Dynamic, Behavioral and Decision making, which together enable the assessment of supply chains as complex systems. Furthermore, five mechanisms emerged for dealing with the complexity of supply chains: classification, modeling, measurement, relational analysis and handling.

Recognizing that supply chains are complex systems allows for a better grasp of the effect of positive feedback on change and transformation, and also interactions leading to dynamic equilibria, nonlinearity and the role of inter-organizational learning, as well as emerging capabilities, and existing trade-offs and paradoxical tensions in decision-making. It recognizes changing dynamics and the co-evolution of supply chain phenomena in different scales and contexts.

Although networked hospitality businesses as Airbnb are a recent phenomenon, a rapid growth has made them a serious competitor for the hospitality industry with important consequences for tourism and for tourist destinations. The purpose of this paper is to analyse the nature of the phenomenon, its potential further development in the next five years and the impact this developments will have on tourism, on hotels and on city destinations.

A literature study, combined with scenario workshops and a Delphi panel, were used to map current trends and uncertainties. With this input, future scenarios were elaborated using the Global Business Network (“scenario cross”) method.

Network platforms as Airbnb are often classified under something called the “Sharing Economy”, a denomination that obscures their true nature. Airbnb is a challenging innovation to which traditional hospitality will have to respond. Its impact has at the same time led to a call for regulatory policies. The definition of these policies and the evolution of tourism are variables that determine future scenarios. Attempts to ban the phenomenon mean a disincentive to innovation and protect oligopolistic markets; more receptive policies may have the desired results if tourism grows moderately but in booming destinations they may lead to a harmful commercialization.

Until now, Airbnb has been described in conceptual studies about the so-called “Sharing economy”, or more recently in empirical studies about isolated effects of holiday rentals. This paper contextualizes the evolution of networked hospitality and seeks to synthesize the sum of its impacts, thus enabling businesses and local governments to define positions and strategies.

Perpetrators of technology-facilitated gender-based violence are taking advantage of increasingly automated and sophisticated privacy-invasive tools to carry out their abuse. Whether this be monitoring movements through stalkerware, using drones to nonconsensually film or harass, or manipulating and distributing intimate images online such as deepfakes and creepshots, invasions of privacy have become a significant form of gender-based violence. Accordingly, our normative and legal concepts of privacy must evolve to counter the harms arising from this misuse of new technology. Canada's Supreme Court recently addressed technology-facilitated violations of privacy in the context of voyeurism in R v Jarvis (2019) . The discussion of privacy in this decision appears to be a good first step toward a more equitable conceptualization of privacy protection. Building on existing privacy theories, this chapter examines what the reasoning in Jarvis might mean for “reasonable expectations of privacy” in other areas of law, and how this concept might be interpreted in response to gender-based technology-facilitated violence. The authors argue the courts in Canada and elsewhere must take the analysis in Jarvis further to fully realize a notion of privacy that protects the autonomy, dignity, and liberty of all.

This article revisits some theories and concepts of public administration, including those related to public value, transaction costs and social equity, to analyze the advantages and disadvantages of using artificial intelligence (AI) algorithms in public service delivery. The author seeks to mobilize theory to guide AI-era public management practitioners and researchers.

The author uses an existing task classification model to mobilize and juxtapose public management theories against artificial intelligence potential impacts in public service delivery. Theories of social equity and transaction costs as well as some concepts such as red tape, efficiency and economy are used to argue that the discipline of public administration provides a foundation to ensure algorithms are used in a way that improves service delivery.

After presenting literature on the challenges and promises of using AI in public service, the study shows that while the adoption of algorithms in public service has benefits, some serious challenges still exist when looked at under the lenses of theory. Additionally, the author mobilizes the public administration concepts of agenda setting and coproduction and finds that designing AI-enabled public services should be centered on citizens who are not mere customers. As an implication for public management practice, this study shows that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.

As a fast-growing subject, artificial intelligence research in public management is yet to empirically test some of the theories that the study presented.

The paper vulgarizes some theories of public administration which practitioners can consider in the design and implementation of AI-enabled public services. Additionally, the study shows practitioners that bringing citizens to the forefront of designing and implementing AI-delivered services is key to reducing the reproduction of social biases.

The paper informs a broad audience who might not be familiar with public administration theories and how those theories can be taken into consideration when adopting AI systems in service delivery.

This research is original, as, to the best of the author’s knowledge, no prior work has combined these concepts in analyzing AI in the public sector.

Digital contact tracing technologies are critical to the fight against COVID-19 in many countries including the UK. However, a number of ethical, legal and socio-economic concerns that can affect uptake of the app have been raised. The purpose of this research is to explore the perceptions of the UK digital contact tracing app in the Black, Asian and Minority Ethnic (BAME) community in Leicester and how this can affect its deployment and implementation.

Data was collected through virtual focus groups in Leicester, UK. A total of 28 participants were recruited for the study. All participants are members of the BAME community, and data was thematically analysed with NVivo 11.

A majority of the participants were unwilling to download and use the app owing to legal and ethical concerns. A minority were willing to use the app based on the need to protect public health. There was a general understanding that lack of uptake will negatively affect the fight against COVID-19 in BAME communities and an acknowledgement of the need for the government to rebuild trust through transparency and development of regulatory safeguards to enhance privacy and prevent misuse.

To the best of the authors’ knowledge, the research makes original contributions being the first robust study conducted to explore perceptions of marginalised communities, particularly BAME which may be adversely impacted by the deployment of the app. By exploring community-based perceptions, this study further contributes to the emerging citizens’ perceptions on digital contact tracing which is crucial to the effectiveness and the development of an efficient, community-specific response to public attitudes towards the app. The findings can also help the development of responsible innovation approaches that balances the competing interests of digital health interventions with the needs and expectations of the BAME community in the UK.

The purpose of this paper is to aim mainly at social public decision-making problems, studies the corresponding relationship between different voting rule combinations and the final results, and discusses the quantitative relationships between group intelligence (final votes) and individual intelligence (everyone) to defend democracy under the circumstance of rapid development of network technology, and crowd intelligence becomes more complicated and universal.

After summarizing the crowd co-decisions of related studies, the standards, frameworks, techniques, methods and tools have been discussed according to the characteristics of large-scale simulations.

The contributions of this paper will be useful for both academics and practitioners for formulating VV&A in large-scale simulations.

This paper will help researchers solve the social public decision-making problems in large-scale simulations.

Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.

The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.

To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.

This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

The paper aims to expand on the works well documented by Joy Boulamwini and Ruha Benjamin by expanding their critique to the African continent. The research aims to assess if algorithmic biases are prevalent in DALL-E 2 and Starry AI. The aim is to help inform better artificial intelligence (AI) systems for future use.

The paper utilised a desktop study for literature and gathered data from Open AI’s DALL-E 2 text-to-image generator and StarryAI text-to-image generator.

The DALL-E 2 significantly underperformed when it was tasked with generating images of “An African Family” as opposed to images of a “Family”. The pictures lacked any conceivable detail as compared to the latter of this comparison. The StarryAI significantly outperformed the DALL-E 2 and rendered visible faces. However, the accuracy of the culture portrayed was poor.

Because of the chosen research approach, the research results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further. The implications, however, are that more inclusion is warranted to help address the issue of cultural inaccuracies noted in a few of the paper’s experiments.

The paper is useful for advocates who advocate for algorithmic equality and fairness by highlighting evidence of the implications of systemic-induced algorithmic bias.

The reduction in offensive racism and more socially appropriate AI can be a better product for commercialisation and general use. If AI is trained on diversity, it can lead to better applications in contemporary society.

The paper’s use of DALL-E 2 and Starry AI is an under-researched area, and future studies on this matter are welcome.

This paper aims to critically assess approaches to sex and gender in the Human Brain Project (HBP) as a large information and communication technology (ICT) project case study using intersectionality.

The strategy of the HBP is contextualised within the wider context of the representation of women in ICT, and critically reflected upon from an intersectional standpoint.

The policy underpinning the approach deployed by the HBP in response to these issues parallels Horizon 2020 wording and emphasises economic outcomes, productivity and value, which aligns with other “equality” initiatives influenced by neoliberalised versions of feminism.

Limitations include focussing on a single case study, the authors being funded as part of the Ethics and Society Subproject of the HBP, and the limited temporal period under consideration.

The frameworks underpinning the HBP approach to sex and gender issues present risks with regard to the further entrenchment of present disparities in the ICT sector, may fail to acknowledge systemic inequalities and biases and ignore the importance of intersectionality. Shortcomings of the approach employed by the HBP up to March, 2018 included aspects of each of these risks, and replicated problematic understandings of sex, gender and diversity.

This paper is the first to use an intersectional approach to issues of sex and gender in the context of large-scale ICT research. Its value lies in raising awareness, opening a discursive space and presenting opportunities to consider and reflect upon potential, contextualised intersectional solutions to such issues.

The purpose of this study is, first, to determine which developments have shaped official hotel classification systems over recent years (including the impact of guest-review platforms) and second to establish the future of those systems through the eyes of the people who are actually in charge of operating them.

Semi-structured interviews were chosen as the most suitable method for approaching hotel classification system administrators. This method is in line with previous research on approaching key informants in their respective fields. Sixteen people representing 12 different official national hotel classification systems from across the world as well as one commercial hotel star rating system participated in the online interviews.

The first main conclusion is that hotel classification systems – especially voluntary ones – would not have survived the enormous impact of guest-review platforms without quickly adjusting to the ever-changing hotel industry landscape. The frequent review of classification criteria and procedures has become the main survival strategy of classification systems. The second conclusion is that system operators are strongly optimistic about the future outlook of hotel classification based on their proven flexibility to swiftly adapt to new market conditions.

Research about hotel classification systems is usually based on the views of the systems' users, i.e. hotels or hotel guests, whereas the present paper reflects the perspective of the systems' operators, an angle rarely analyzed in the literature.