AI Affordance Actualisation: Empirical Evidence from Mobility Ecosystem Organisations

One of the UN Sustainable Development Goals (SDGs) is to transform urban mobility to be more accessible, efficient, safe, and sustainable. Artificial Intelligence (AI) can be applied to address some critical urban mobility issues and facilitate the achievement of SDGs. However, there is a need to understand how mobility ecosystem organisations use AI in alignment with their organisational goals to contribute to SDGs. To address this puzzle, this study draws on the affordance theory and preliminary interviews with ten key informants from mobility organisations in Australia. The preliminary findings show that mobility organisations’ exploitation of AI systems and technologies leads to the emergence of decarbonising, optimising, conditioning asset management, and provisioning customer-centric services. To do so, they develop AI literacy, business-IT collaboration, change management, and technology and data foundation. The paper contributes a tentative framework linking AI affordances with mobility-related SDGs, serving as a guide for future research and practice

Evolution of Chinese Ghost Cities

In the late 2000s, the phenomenon of ghost cities emerged in China, including not only boomtowns such as Ordos but also “ordinary” third‑ and fourth-tier cities such as Changzhou. Based on a conceptual framework of China’s land-driven growth machine under entrepreneurial governance, we update the ghost city phenomenon through an in-depth empirical study of a third‑tier city, Changzhou. The objective of this paper is to expand our understanding of how excessive accumulation of real estate assets has come to dominate the landscape of this type of city against the background of China’s economic slowdown. The author argues that overbuilding is due to the malfunction of the classic urban expansion model under entrepreneurial governance. In the case of Changzhou, the local government continued massive “sales” of residential and commercial land while effective housing demand was declining due to slowdowns in the local manufacturing industry and in population growth. In response to the “New Normal” advocated by the central government, the government of Changzhou redirected its land and housing policy. Nevertheless, more profound reforms are needed to change the paradigm of growth-oriented urbanism

L’évolution des villes fantômes chinoises

Le phénomène des villes fantômes est apparu en Chine à la fin des années 2000. Il concerne non seulement des villes-champignons telles qu’Ordos, mais également des villes de troisième et quatrième rang « ordinaires » comme Changzhou. Nous fondant sur un cadre conceptuel envisageant la Chine comme une machine à croissance alimentée par le foncier et sous gouvernance entrepreneuriale, nous dressons un bilan actualisé du phénomène des villes fantômes en Chine à travers une étude empirique approfondie d’une ville de troisième rang, Changzhou. L’objectif de cet article est d’élargir nos connaissances quant à la question de comprendre comment l’accumulation excessive de biens immobiliers a fini par dominer le paysage de ce type de villes dans le contexte d’un ralentissement de l’économie chinoise. L’auteur démontre que la sur-construction est due au dysfonctionnement du modèle d’expansion urbaine classique sous la gouvernance entrepreneuriale. Dans le cas de Changzhou, le gouvernement local a poursuivi ses « ventes » massives de terrains résidentiels et commerciaux alors que la demande réelle de logement déclinait à cause de ralentissements de l’industrie manufacturière locale et de la croissance démographique. En réponse à la « Nouvelle normalité » promue par le gouvernement central, le gouvernement de Changzhou a réorienté ses politiques foncières et de logement. Néanmoins, des réformes plus profondes sont nécessaires pour transformer le paradigme de l’urbanisme orienté vers la croissance

AI Affordances Perception for the Transformation of Mobility Ecosystems

Artificial Intelligence (AI) can transform organisations, industries, and ecosystems. However, how different organisations in a given ecosystem perceive the action potentials of AI (i.e., AI affordances) has not been researched. To advance the AI affordances research and develop a nomological net of organisational and ecosystem factors that influence the AI affordances perception, this paper contributes a conceptual framework with the context of the mobility ecosystem transformation. The framework draws from two theories: the affordances theory and the social cognitive theory. The paper presents an in-depth interpretation of these theories for the perception of AI affordances and develops propositions to explain two distinct types of affordances perceptions: vicarious and autonomous. Our conceptual work offers a foundation for developing models for prediction and opens new avenues of investigating AI affordances perception. Future research could further test and validate the framework

Explaining Consumers’ Intention to Use Omni-channel Shopping

Retail businesses are increasingly merging online and offline channels into integrated omni-channel services. However, without an in-depth understanding of why consumers oscillate between online and offline channels, the future of omni-channel retailing remains uncertain. This paper aims to promote a greater understanding of the demand and supply side factors that contribute to omni-channel use. We developed a research model drawing from UTAUT2 and the security, inconsistency, and service quality attributes of omni-channel contexts. We tested both the direct and moderated effects of the constructs on the intention to use omni-channel shopping services with a sample of 362 Chinese survey participants. The results show that besides UTAUT2 variables, perceived inconsistency, and perceived service quality show significant effects on consumers’ intention to use omni-channel services. Furthermore, our results show that age, gender, and online shopping frequency moderate the relationship between perceived service quality and use intention

Online near-infrared analysis coupled with MWPLS and SiPLS models for the multi-ingredient and multi-phase extraction of licorice (Gancao)

Additional file 1. Table S1. The sampling intervals in different extraction phases. Table S2. The HPLC results of different indicators. Table S3. The evaluation parameters of PLS and SiPLS models

Cost-effectiveness analysis of atezolizumab in patients with non-small-cell lung cancer ineligible for treatment with a platinum-containing regimen: a United Kingdom health care perspective

BackgroundCost-effectiveness of atezolizumab, as a treatment for advanced non-small-cell lung cancer (NSCLC) patients who cannot receive a platinum-containing regimen,was still unknown. Our objective was to evaluate the cost-effectiveness of atezolizumab vs. chemotherapy in this indication from the perspective of UK healthcare system.MethodsFrom the global, randomised, open-label, phase III IPSOS trial, clinical inputs and patient characteristics were obtained. A partitioned survival model with three health states was built: Progression-free survival, progressed disease and death. A lifetime time horizon was applied, with an annual discount rate of 3.5%. Additionally, the willingness-to-pay threshold of £50,000/QALY was utilized. Primary outcomes were quality-adjusted life-year (QALY), costs, and incremental cost-effectiveness ratio (ICER). Sensitivity, scenario, and subgroup analyses were used to assess the reliability of base-case results. Price simulations were carried out in order to provide information for the pricing strategy at specific willingness-to-pay threshold.ResultsIn the base-case analysis, atezolizumab resulted in a gain of 0.28 QALYs and an ICER of £94,873/QALY compared to chemotherapy, demonstrating no cost-effectiveness. Price simulation results revealed that atezolizumab would be preferred at a price lower than £2,215 (a reduction of 41.8%) at the willingness-to-pay threshold of £50,000. Sensitivity, scenario and subgroup analyses revealed these conclusions were generally robust, the model was most sensitive to the price of atezolizumab and subsequent medication. Furthermore, atezolizumab was found to be more cost-effective for patients displaying a positive PD-L1 expression, with an ICER of £72,098/QALY as compared to chemotherapy.ConclusionAtezolizumab is not cost-effective for patients with advanced NSCLC ineligible for platinum-containing regimen, potential price reduction is necessary

Affordable Housing in Urban China

International audienc

Directional Difference Convolution and Its Application on Face Anti-Spoofing

In practical application, facial image recognition is vulnerable to be attacked by photos, videos, etc., while some currently used artificial feature extractors in machine learning, such as activity detection, texture descriptors, and distortion detection, are insufficient due to their weak detection ability in feature extraction from unknown attack. In order to deal with the aforementioned deficiency and improve the network security, this paper proposes directional difference convolution for the deep learning in gradient image information extraction, which analyzes pixel correlation within the convolution domain and calculates pixel gradients through difference calculation. Its combination with traditional convolution can be optimized by a parameter θ. Its stronger ability in gradient extraction improves the learning and predicting ability of the network, whose performance testing on CASIA-MFSD, Replay-Attack, and MSU-MFSD for face anti-spoofing task shows that our method outperforms the current related methods