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1 – 10 of over 6000Weifei Hu, Tongzhou Zhang, Xiaoyu Deng, Zhenyu Liu and Jianrong Tan
Digital twin (DT) is an emerging technology that enables sophisticated interaction between physical objects and their virtual replicas. Although DT has recently gained significant…
Abstract
Digital twin (DT) is an emerging technology that enables sophisticated interaction between physical objects and their virtual replicas. Although DT has recently gained significant attraction in both industry and academia, there is no systematic understanding of DT from its development history to its different concepts and applications in disparate disciplines. The majority of DT literature focuses on the conceptual development of DT frameworks for a specific implementation area. Hence, this paper provides a state-of-the-art review of DT history, different definitions and models, and six types of key enabling technologies. The review also provides a comprehensive survey of DT applications from two perspectives: (1) applications in four product-lifecycle phases, i.e. product design, manufacturing, operation and maintenance, and recycling and (2) applications in four categorized engineering fields, including aerospace engineering, tunneling and underground engineering, wind engineering and Internet of things (IoT) applications. DT frameworks, characteristic components, key technologies and specific applications are extracted for each DT category in this paper. A comprehensive survey of the DT references reveals the following findings: (1) The majority of existing DT models only involve one-way data transfer from physical entities to virtual models and (2) There is a lack of consideration of the environmental coupling, which results in the inaccurate representation of the virtual components in existing DT models. Thus, this paper highlights the role of environmental factor in DT enabling technologies and in categorized engineering applications. In addition, the review discusses the key challenges and provides future work for constructing DTs of complex engineering systems.
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Carlos Orús, Raquel Gurrea and Sergio Ibáñez-Sánchez
This purpose of this paper is to analyze how consumers’ online recommendations affect the omnichannel webrooming experience based on the internet, physical and mobile channels.
Abstract
Purpose
This purpose of this paper is to analyze how consumers’ online recommendations affect the omnichannel webrooming experience based on the internet, physical and mobile channels.
Design/methodology/approach
Two experimental studies are implemented. Study 1 analyzes the impact of an online review on the physical interaction with the product. Study 2 modifies the moment of receiving the online recommendation and its social tie.
Findings
Webrooming improves the shopping experience. Online recommendations from anonymous customers increase confidence in the product’s adequacy, although this effect depends on the moment of receiving the recommendation and the level of confidence before interacting physically with the product. Friend recommendations reinforce preferences regardless of previous online experiences.
Research limitations/implications
This research examines the effects of different types of online recommendations on offline shopping experiences, choice and confidence. Confidence is stressed as a key variable in omnichannel behavior.
Practical implications
The findings offer practical value for electronic word-of-mouth marketing, omnichannel marketing, as well as online and physical channel management.
Originality/value
This is one of the first studies that examine the impact of online consumer recommendations on shopping experiences combining online, mobile and physical channels. The results reveal the importance of recommendations’ source and moment of reception for determining consumers’ preferences, choice and confidence.
Propósito
La presente investigaciĂłn analiza cĂłmo las recomendaciones online afectan a la experiencia webrooming omnicanal, basada en el canal fĂsico, online, y mĂłvil.
Diseño/metodología/enfoque
Se llevaron a cabo dos experimentos. El Estudio 1 analiza el impacto de una revisiĂłn online positiva en la interacciĂłn posterior con el producto. El Estudio 2 modifica el momento de recibir la recomendaciĂłn y el vĂnculo social entre emisor y receptor.
Hallazgos
El proceso webrooming mejora la experiencia de compra. Las recomendaciones online de clientes anĂłnimos incrementan la auto-confianza sobre la adecuaciĂłn del producto, aunque este efecto depende del momento de recibir la recomendaciĂłn y del nivel de auto-confianza previo a la interacciĂłn fĂsica con el producto. Las recomendaciones de amigos refuerzan las preferencias, independientemente de la experiencia online previa.
Limitaciones/implicaciones
Esta investigaciĂłn examina los efectos de diferentes tipos de recomendaciones online en experiencias offline, le elecciĂłn y la auto-confianza. La auto-confianza se revela como una variable clave del comportamiento omnicanal.
Implicaciones prácticas
Los resultados ofrecen implicaciones para la gestiĂłn del marketing boca-oĂdo y omnicanal, asĂ como la gestiĂłn de la experiencia en el canal fĂsico y el online.
Originalidad/valor
Este es uno de los primeros estudios que analizan el impacto de recomendaciones online en experiencias de compra que combinan canales online, offline y mĂłvil. Los resultados revelan que la importancia de la fuente y del momento de recibir la recomendaciĂłn determinan las preferencias, elecciĂłn, y auto-confianza de los consumidores.
Palabras clave
Comercio minorista, Omnicanal, Webrooming, Auto-confianza, Boca-oĂdo electrĂłnico, VĂnculo social
Tipo de artículo
Trabajo de investigaciĂłn
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Christian Kowalkowski, Jochen Wirtz and Michael Ehret
Technology-enabled business-to-business (B2B) services contribute the largest share to GDP growth and are fundamental for an economy’s value creation. This article aims to…
Abstract
Purpose
Technology-enabled business-to-business (B2B) services contribute the largest share to GDP growth and are fundamental for an economy’s value creation. This article aims to identify key service- and digital technology-driven B2B innovation modes and proposes a research agenda for further exploration.
Design/methodology/approach
This conceptual paper adopts a techno-demarcation view on service innovation, encompassing three core dimensions: service offering (the service product, or the “what”), service process (the “how”) and service ecosystem (the “who/for whom”). It delineates the implications of three digital technologies – the internet-of-things (IoT), intelligent automation (IA) and digital platforms – for service innovation across these core dimensions in B2B markets.
Findings
Digital technology has immense potential ramifications for value creation by reshaping all three core dimensions of service innovation. Specifically, IoT can transform physical resources into reconfigurable service products, IA can augment and automate a rapidly expanding array of service processes, while digital platforms provide the technical and organizational infrastructure for the integration of resources and stakeholders within service ecosystems.
Originality/value
This study suggests an agenda with six themes for further research, each linked to one or more of the three service innovation dimensions. They are (1) new recurring revenue models, (2) service innovation in the metaverse, (3) scaling up service innovations, (4) ecosystem innovations, (5) power dependency and lock-in effects and (6) security and responsibility in digital domains.
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The purpose of this paper is to construct a digital collection and database of traditional clothing that is convenient for the digital dissemination and application of traditional…
Abstract
Purpose
The purpose of this paper is to construct a digital collection and database of traditional clothing that is convenient for the digital dissemination and application of traditional clothing and provide resources for research on clothing fashion, traditional clothing techniques, clothing culture, history and clothing teaching.
Design/methodology/approach
A real object analysis method was used in this paper, based on 15 core elements of the internationally common DC metadata standard, and with consideration to the characteristics of clothing products and clothing industry application specifications, the core elements of DC are expanded to facilitate the detailed record of the characteristic information of clothing, especially the implicit clothing culture. A code symbol compilation method was developed to give each piece of clothing a unique number, facilitating identification, classification and recording. At last, a metadata construction scheme for traditional clothing was developed. A traditional embroidered children's hat and Mamianqunt serve as examples to demonstrate the metadata elements.
Findings
The clothing meta-database provides a main body of traditional clothing while also paying attention to the collection of cultural elements. It is composed of five layers of classified data, source data, characteristic data, connotation data and management data, as well as 28 data elements, providing ease of sharing and interoperation.
Originality/value
This paper expands the subset of fashion metadata by describing traditional clothing metadata, especially the excavation of clothing cultural elements, and developing code compilation methods so that each clothing product can obtain a unique identification number, thereby building a traditional clothing metadata construction scheme consisting of five data layers and containing 28 data elements. This scheme records the information about each layer of traditional clothing in detail and provides shared data for discipline research and industry applications.
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Friso van Dijk, Joost Gadellaa, Chaïm van Toledo, Marco Spruit, Sjaak Brinkkemper and Matthieu Brinkhuis
This paper aims that privacy research is divided in distinct communities and rarely considered as a singular field, harming its disciplinary identity. The authors collected…
Abstract
Purpose
This paper aims that privacy research is divided in distinct communities and rarely considered as a singular field, harming its disciplinary identity. The authors collected 119.810 publications and over 3 million references to perform a bibliometric domain analysis as a quantitative approach to uncover the structures within the privacy research field.
Design/methodology/approach
The bibliometric domain analysis consists of a combined directed network and topic model of published privacy research. The network contains 83,159 publications and 462,633 internal references. A Latent Dirichlet allocation (LDA) topic model from the same dataset offers an additional lens on structure by classifying each publication on 36 topics with the network data. The combined outcomes of these methods are used to investigate the structural position and topical make-up of the privacy research communities.
Findings
The authors identified the research communities as well as categorised their structural positioning. Four communities form the core of privacy research: individual privacy and law, cloud computing, location data and privacy-preserving data publishing. The latter is a macro-community of data mining, anonymity metrics and differential privacy. Surrounding the core are applied communities. Further removed are communities with little influence, most notably the medical communities that make up 14.4% of the network. The topic model shows system design as a potentially latent community. Noteworthy is the absence of a centralised body of knowledge on organisational privacy management.
Originality/value
This is the first in-depth, quantitative mapping study of all privacy research.
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Briony Anderson and Mark A. Wood
This chapter examines the phenomenon of doxxing: the practice of publishing private, proprietary, or personally identifying information on the internet, usually with malicious…
Abstract
This chapter examines the phenomenon of doxxing: the practice of publishing private, proprietary, or personally identifying information on the internet, usually with malicious intent. Undertaking a scoping review of research into doxxing, we develop a typology of this form of technology-facilitated violence (TFV) that expands understandings of doxxing, its forms and its harms, beyond a taciturn discussion of privacy and harassment online. Building on David M. Douglas's typology of doxxing, our typology considers two key dimensions of doxxing: the form of loss experienced by the victim and the perpetrator's motivation(s) for undertaking this form of TFV. Through examining the extant literature on doxxing, we identify seven mutually non-exclusive motivations for this form of TFV: extortion, silencing, retribution, controlling, reputation-building, unintentional, and doxxing in the public interest. We conclude by identifying future areas for interdisciplinary research into doxxing that brings criminology into conversation with the insights of media-focused disciplines.
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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.
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Jochen Wirtz, Paul G. Patterson, Werner H. Kunz, Thorsten Gruber, Vinh Nhat Lu, Stefanie Paluch and Antje Martins
The service sector is at an inflection point with regard to productivity gains and service industrialization similar to the industrial revolution in manufacturing that started in…
Abstract
Purpose
The service sector is at an inflection point with regard to productivity gains and service industrialization similar to the industrial revolution in manufacturing that started in the eighteenth century. Robotics in combination with rapidly improving technologies like artificial intelligence (AI), mobile, cloud, big data and biometrics will bring opportunities for a wide range of innovations that have the potential to dramatically change service industries. The purpose of this paper is to explore the potential role service robots will play in the future and to advance a research agenda for service researchers.
Design/methodology/approach
This paper uses a conceptual approach that is rooted in the service, robotics and AI literature.
Findings
The contribution of this paper is threefold. First, it provides a definition of service robots, describes their key attributes, contrasts their features and capabilities with those of frontline employees, and provides an understanding for which types of service tasks robots will dominate and where humans will dominate. Second, this paper examines consumer perceptions, beliefs and behaviors as related to service robots, and advances the service robot acceptance model. Third, it provides an overview of the ethical questions surrounding robot-delivered services at the individual, market and societal level.
Practical implications
This paper helps service organizations and their management, service robot innovators, programmers and developers, and policymakers better understand the implications of a ubiquitous deployment of service robots.
Originality/value
This is the first conceptual paper that systematically examines key dimensions of robot-delivered frontline service and explores how these will differ in the future.
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Tamara Vanessa Leiß and Andreas Rausch
This paper aims to examine the impact of problem-solving activities, emotional experiences and contextual and personal factors on learning from dealing with software-related…
Abstract
Purpose
This paper aims to examine the impact of problem-solving activities, emotional experiences and contextual and personal factors on learning from dealing with software-related problems in everyday office work.
Design/methodology/approach
To measure the use of problem-solving activities, emotional experiences and the contextual factors of problem characteristics and learning in situ, a research diary was used. To measure team psychological safety (contextual factor) and personal factors, including the Big Five personality traits, occupational self-efficacy and technology self-efficacy, the authors administered a self-report questionnaire. In sum, 48 students from a software company in Germany recorded 240 diary entries during five working days. The data was analysed using multilevel analysis.
Findings
Results revealed that asking others and using information from the internet are positive predictors of self-perceived learning from a software-related problem, while experimenting, which was the most common activity, had a negative effect on learning. Guilt about the problem was positively related to learning while working in the office (as opposed to remote work), and feeling irritated/annoyed/angry showed a negative effect. Surprisingly, psychological safety had a negative effect on perceived learning.
Research limitations/implications
Major limitations of the study concern the convenience sample and the disregard for the sequence of the activities.
Originality/value
This study contributes to the limited empirical evidence on employees’ problem-solving activities and informal workplace learning in the software context. To overcome the shortcomings of previous studies using retrospective assessments and in-lab observations, this study uses the diary method to investigate in situ.
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Tonderai Washington Shumba, Desderius Haufiku and Hans Amukugo
Qualitative participatory methods are needed to measure the effectiveness of the community-based rehabilitation (CBR) program in Namibia. The study explored the experiences of CBR…
Abstract
Purpose
Qualitative participatory methods are needed to measure the effectiveness of the community-based rehabilitation (CBR) program in Namibia. The study explored the experiences of CBR volunteers in evaluating CBR program in Namibia through the use of photovoice. Further the study assessed the strengths and limitations of utilizing photovoice method as an assessment tool for CBR evaluation.
Design/methodology/approach
The study employed a qualitative, explorative, descriptive and contextual design. Data was collected through the photovoice method. Two CBR sites and 16 participants who were CBR volunteers were purposively selected. Data was collected and analysis was conducted simultaneously utilizing the photovoice method and themes were determined using WHO CBR matrix.
Findings
Various experiences were elicited regarding participants' experiences in line with the five components of the CBR matrix. Most experiences were reported regarding the health component, and the education component had the least experiences reported. Methodological strength and weaknesses as well as implications for practice are revealed. Further research can explore the benefits of combining photovoice with other data collection methods.
Originality/value
Sustainability of CBR programs depends on community ownership, empowerment and government funding. Photovoice is participatory and hence gives community ownership and empowerment. Evidence from photovoice can enable persons with disabilities to formulate action plans that can advocate their concerns with policymakers and justify more funding for CBR programs.
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