The authors develop a three-stage framework for strategic marketing planning, incorporating multiple artificial intelligence (AI) benefits: mechanical AI for automating repetitive marketing functions ...and activities, thinking AI for processing data to arrive at decisions, and feeling AI for analyzing interactions and human emotions. This framework lays out the ways that AI can be used for marketing research, strategy (segmentation, targeting, and positioning, STP), and actions. At the marketing research stage, mechanical AI can be used for data collection, thinking AI for market analysis, and feeling AI for customer understanding. At the marketing strategy (STP) stage, mechanical AI can be used for segmentation (segment recognition), thinking AI for targeting (segment recommendation), and feeling AI for positioning (segment resonance). At the marketing action stage, mechanical AI can be used for standardization, thinking AI for personalization, and feeling AI for relationalization. We apply this framework to various areas of marketing, organized by marketing 4Ps/4Cs, to illustrate the strategic use of AI.
Artificial Intelligence in Service Huang, Ming-Hui; Rust, Roland T.
Journal of service research : JSR,
05/2018, Volume:
21, Issue:
2
Journal Article
Peer reviewed
Artificial intelligence (AI) is increasingly reshaping service by performing various tasks, constituting a major source of innovation, yet threatening human jobs. We develop a theory of AI job ...replacement to address this double-edged impact. The theory specifies four intelligences required for service tasks—mechanical, analytical, intuitive, and empathetic—and lays out the way firms should decide between humans and machines for accomplishing those tasks. AI is developing in a predictable order, with mechanical mostly preceding analytical, analytical mostly preceding intuitive, and intuitive mostly preceding empathetic intelligence. The theory asserts that AI job replacement occurs fundamentally at the task level, rather than the job level, and for “lower” (easier for AI) intelligence tasks first. AI first replaces some of a service job’s tasks, a transition stage seen as augmentation, and then progresses to replace human labor entirely when it has the ability to take over all of a job’s tasks. The progression of AI task replacement from lower to higher intelligences results in predictable shifts over time in the relative importance of the intelligences for service employees. An important implication from our theory is that analytical skills will become less important, as AI takes over more analytical tasks, giving the “softer” intuitive and empathetic skills even more importance for service employees. Eventually, AI will be capable of performing even the intuitive and empathetic tasks, which enables innovative ways of human–machine integration for providing service but also results in a fundamental threat for human employment.
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This article develops a strategic framework for using artificial intelligence (AI) to engage customers for different service benefits. This framework lays out guidelines of how to use different AIs ...to engage customers based on considerations of nature of service task, service offering, service strategy, and service process. AI develops from mechanical, to thinking, and to feeling. As AI advances to a higher intelligence level, more human service employees and human intelligence (HI) at the intelligence levels lower than that level should be used less. Thus, at the current level of AI development, mechanical service should be performed mostly by mechanical AI, thinking service by both thinking AI and HI, and feeling service mostly by HI. Mechanical AI should be used for standardization when service is routine and transactional, for cost leadership, and mostly at the service delivery stage. Thinking AI should be used for personalization when service is data-rich and utilitarian, for quality leadership, and mostly at the service creation stage. Feeling AI should be used for relationalization when service is relational and high touch, for relationship leadership, and mostly at the service interaction stage. We illustrate various AI applications for the three major AI benefits, providing managerial guidelines for service providers to leverage the advantages of AI as well as future research implications for service researchers to investigate AI in service from modeling, consumer, and policy perspectives.
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bstract
In this paper, we consider the computation of charged moments of the reduced density matrix of two disjoint intervals in the 1+1 dimensional free compactified boson conformal field theory ...(CFT) by studying the four-point function of the fluxed twist fields. We obtained the exact scaling function of this four-point function and discussed its decompactification limit. This scaling function was used to obtain the charged moments of the partial transpose which we refer as charged Rényi negativity. These charged moments and the charged moments of the partial transpose are essential for the problem of symmetry decomposition of the corresponding entanglement measures. We test our analytic formula against exact numerical computation in the complex harmonic chain, finding perfect agreements.
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In this paper, we consider the time evolution of charge imbalance resolved negativity after a global quench in the 1+1 dimensional complex Klein-Gordon theory. We focus on two types of ...global quenches which are called boundary state quench and mass quench respectively. We first study the boundary state quench where the post-quench dynamic is governed by a massless Hamiltonian. In this case, the temporal evolution of charged imbalance resolved negativity can be obtained first by evaluating the correlators of the fluxed twist field in the upper half plane and then applying Fourier transformation. We test our analytical formulas in the underlying lattice model numerically. We also study the mass quench in the complex harmonic chain where the system evolves according to a massive Hamiltonian after the quench. We argue that our results can be understood in the framework of quasi-particle picture.
The capability of AI is currently expanding beyond mechanical and repetitive to analytical and thinking. A “Feeling Economy” is emerging, in which AI performs many of the analytical and thinking ...tasks, and human workers gravitate more toward interpersonal and empathetic tasks. Although these people-focused tasks have always been important to jobs, they are now becoming more important to an unprecedented degree. To manage more effectively in the Feeling Economy, managers must adapt the nature of jobs to compensate for the fact that many of the analytical and thinking tasks are increasingly being performed by AI, and, thus, human workers must place increased emphasis on the empathetic and emotional dimensions of their work.
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•AI advances from mechanical to thinking to feeling, changing how AI should be used.•AI and human intelligence (HI) complement best as collaborative teams.•Lower-level AI augments ...higher-level HI.•AI first augments and then replaces HI at a given intelligence level.•Move HI to a higher intelligence level when AI automates the lower level.
We develop a conceptual framework for collaborative artificial intelligence (AI) in marketing, providing systematic guidance for how human marketers and consumers can team up with AI, which has profound implications for retailing, which is the interface between marketers and consumers. Drawing from the multiple intelligences view that AI advances from mechanical, to thinking, to feeling intelligence (based on how difficult for AI to mimic human intelligences), the framework posits that collaboration between AI and HI (human marketers and consumers) can be achieved by 1) recognizing the respective strengths of AI and HI, 2) having lower-level AI augmenting higher-level HI, and 3) moving HI to a higher intelligence level when AI automates the lower level. Implications for marketers, consumers, and researchers are derived. Marketers should optimize the mix and timing of AI-HI marketing team, consumers should understand the complementarity between AI and HI strengths for informed consumption decisions, and researchers can investigate innovative approaches to and boundary conditions of collaborative intelligence.
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CEKLJ, GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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bstract
In this paper, we consider the dynamics of Rényi negativities after a quantum quench in the free-boson chain with homogeneous dissipation. Initially we prepare the system in the squeezed ...thermal state, and then let it evolves under the tight-binding bosonic Hamiltonian with local linear dissipation. We use the Lindblad equation to solve the time evolution of the covariance matrix, from which one can obtain the time dependence of Rényi negativities. We are interested in the weak dissipation hydrodynamic limit where a quasi-particle picture emerges. In this limit, exact results of non-equilibrium dynamics of Rényi negativities can be obtained using the stationary phase method. We consider the Rényi negativities between both adjacent and disjoint regions in a infinite chain. We numerically test our analytical predictions and perfect matches have found.
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•The status quo of inorganic nanoparticles in clinical trials and translation is highlighted and summarized.•The progress and paradigms on inorganic nanomaterials for clinical ...relevance and translation are elucidated systematically.•The challenges and perspectives in clinical translation of inorganic nanoparticles are discussed in depth.
The development and application of nanotechnology-related knowledge and tools in modern medicine has been showing great potentials in elevating human’s living standards and improving mankind’s healthcare conditions via the prevention, early detection, diagnosis, treatment and follow-up of various diseases. The significant progress of nanomedicine has been achieved by the exploration of nanoparticulate formulations for theranostic purposes in a living organism. Among abundant nanoparticles, inorganic nanoparticles feature distinctive physiochemical properties and biological effects, with which conventional organic counterparts are typically not endowed. In the past thirty years, to be true, very few inorganic nanomaterials have been made from bench to bedside translation. It is thus more vital than ever for the scientific community to make ever-greater efforts to realize their clinical translations. Therefore, this review highlights and discusses such a compelling topic on the clinical trials and translation of inorganic nanoparticles. We will provide an update of the current progresses in clinic-relevant applications in terms of inorganic nanoparticles being used as detecting tools, contrast agents as well as therapeutic vehicles. Especially, the crucial challenges and future prospects in translating inorganic nanoparticles into clinical practices are highlighted and outlooked. This review aims to bring the issues of clinical relevance and translatability of inorganic nanoparticles to the forefront, which is the primary impetus, and also critically important, for the development of inorganic nanoparticles-based nanobiotechnology and nanomedicine.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Direct electrocatalytic oxidation of ammonia was carried out using an open-pore structured nickel foam electrode via electrochemical formation of Ni(OH)2/NiOOH nano-flowers (theophrastite phase) on ...the nickel substrate at specific overpotentials. The electrode surface was analyzed by X-ray diffraction (XRD), scanning electron microscope (SEM), Raman spectrometer (RS), and X-ray photoelectron spectroscopy (XPS). Cyclic voltammograms gave information on the nature of electron transfer between nitrogen species and nickel foam electrode and revealed the potential dependence nature of ammonia oxidation over the potential window of +0.7 V to +0.85 V (vs. Hg/HgO). Batch controlled potential experiments using nickel foam as the working anode in a three-electrode system were conducted to study the oxidation of ammonia in solution containing 0.1 M of Na2SO4 electrolyte, at pH 11 and temperature of 25 °C. Based on the current efficiency and reaction kinetics, it was possible to establish the mechanism of selective ammonia conversion to gaseous nitrogen and nitrate.
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•Redox reaction of Ni(OH)2/NiOOH on Ni foam was characterized.•Onset of NH3 oxidation potential at pH 11 was around 0.65 V vs. Hg/HgO.•High N2 selectivity occurred at E < 0.79 V vs. Hg/HgO.•High selectivity NO3− and NO2− selectivity occurred at E > 0.79 V vs Hg/HgO.•Complete ammonia removal at applied potential 0.85 V vs Hg/HgO.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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