Human-computer interaction and value co-creation in electronic service

Li, Lei; Huang, Alex Q.; Yeung, K.W.; Jian, Zhaoquan

doi:10.1108/imds-03-2017-0095

Cited by 10 publications

(6 citation statements)

References 28 publications

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“…Customer recovery finds the solution to service failure by themselves. Firm recovery can provide some remedial measures to explain the firm's failure, and co-creation recovery can effectively promote the cocreated value between customers and companies (Li et al, 2018). However, the firms should not shift customers toward self-service completely, which is not beneficial (Scherer et al, 2015).…”

Section: Service Recoverymentioning

confidence: 99%

Are you willing to forgive AI? Service recovery from medical AI service failure

Chen

Pan

et al. 2022

IMDS

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PurposeAs an emerging technology, medical artificial intelligence (AI) plays an important role in the healthcare system. However, the service failure of medical AI causes severe violations to user trust. Different from other services that do not involve vital health, customers' trust toward the service of medical AI are difficult to repair after service failure. This study explores the links among different types of attributions (external and internal), service recovery strategies (firm, customer, and co-creation), and service recovery outcomes (trust).Design/methodology/approachEmpirical analysis was carried out using data (N = 338) collected from a 2 × 3 scenario-based experiment. The scenario-based experiment has three stages: service delivery, service failure, and service recovery. The attribution of service failure was divided into two parts (customer vs. firm), while the recovery of service failure was divided into three parts (customer vs. firm vs. co-creation), making the design full factorial.FindingsThe results show that (1) internal attribution of the service failure can easily repair both affective-based trust (AFTR) and cognitive-based trust (CGTR), (2) co-creation recovery has a greater positive effect on AFTR while firm recovery is more effective on cognitive-based trust, (3) a series of interesting conclusions are found in the interaction between customers' attribution and service recovery strategy.Originality/valueThe authors' findings are of great significance to the strategy of service recovery after service failure in the medical AI system. According to the attribution type of service failure, medical organizations can choose a strategy to more accurately improve service recovery effect.

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Section: Service Recoverymentioning

confidence: 99%

Are you willing to forgive AI? Service recovery from medical AI service failure

Chen

Pan

et al. 2022

IMDS

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“…One of the main reasons for the provision of electronic services is to provide accurate information to users. This means that the user expects correct and precise information ( Gracia-Tinedo et al, 2018 ; Li et al, 2018a ). Studies of mobile service quality have included the concept of accuracy as a construct to evaluate the dimension of IQ.…”

Section: Mobile Government Information Quality Modelmentioning

confidence: 99%

Exploring the information quality of mobile government services: a literature review

Desmal

Othman

Hamid

et al. 2022

PeerJ Computer Science

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This article aims to investigate the constructs that can be used to evaluate the information quality (IQ) of mobile government services. The dimension of IQ is one of the fundamental constructs that assesses the extent of information based on its accuracy, usefulness, and timeliness. Based on the review of previous studies, there is a lack of studies related to mGovernment service quality. It is not practical to measure the service quality of mGovernment by using other measurement scales such as e-service, e-commerce, or e-government. Therefore, it is necessary to understand each dimension that guides constructing a comprehensive framework to measure service quality at mGovernment. The constructs of information quality were extracted from previous literature in mobile government, mobile application service, and e-government to understand the development stages, structure, and unique features—this guide to conduct the systematic literature review to clarify the constructs belonging to the evaluation of information quality. The present article identified six constructs—understandability, timeliness, accuracy, completeness, availability, and usefulness—to measure the information quality of mobile government service. There is limited literature on mGovernment information service quality. With the development of government services on mobile devices, it is necessary to measure information quality at mGovernment service channel to understand users’ expectations. The mGovernment service provider benefits from measuring the service quality by improving the strategy and criteria of information at mGovernment portal. In addition, the end-users expect to perform the service with the best quality level of the information supplied and displayed on mGovernment platform.

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“…-Quel est l'effet de l'immédiateté perçue d'une plateforme digitale sur la VCDC pour les différents types de plateforme (Li et al, 2018) ? -Dans quelle mesure les plateformes à base d'automatisation des processus robotiques et d'apprentissage automatique/ en profondeur font-elles respectivement valoir la VCDC et la valeur codétruite (Smith, 2013) ?…”

Section: Propositionunclassified

Démystifier la valeur cocréée digitale du consommateur : cadre et propositions fondées sur la théorie de la présence sociale

Hollebeek

Clark

Macky³

2021

Recherche et Applications en Marketing (French Edition)

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Alors que la recherche sur la cocréation est prolifique, les travaux existants ne particularisent pas la manière dont elle se manifeste sur les plateformes digitales. De plus, ces travaux ont essentiellement examiné le processus de cocréation en lui-même, et non le résultat de ce processus, c’est-à-dire, la valeur cocréée. Un examen plus approfondi s’avère donc nécessaire, en particulier dans un contexte digital. A ce titre, nous nous focalisons dans cet article sur la Valeur Cocréée Digitale du Consommateur (ou « VCDC »), qui désigne la valeur perçue par le consommateur telle qu’elle résulte de l’interaction, de la collaboration ou de la communication avec ou via des plateformes digitales. Nous distinguons les plateformes digitales (i) homme-homme (H2HP ; par exemple, les médias sociaux) et (ii) homme-machine (H2MP), celles-ci comprenant (a) les plateformes à base d’automatisation des processus robotiques (par exemple, les centres d’appels) et (b) les plateformes à base d’apprentissage automatique/en profondeur (par exemple, les robots de service). Nous proposons en outre un cadre d’analyse fondé sur la théorie de la présence sociale qui examine l’effet de l’intimité et de l’immédiateté perçues sur la VCDC, et ce, pour chacun des types de plateformes identifiés. Enfin, nous formalisons nos réflexions dans des propositions de recherche et en discutons les implications.

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Human-computer interaction and value co-creation in electronic service

Cited by 10 publications

References 28 publications

Are you willing to forgive AI? Service recovery from medical AI service failure

Are you willing to forgive AI? Service recovery from medical AI service failure

Exploring the information quality of mobile government services: a literature review

Démystifier la valeur cocréée digitale du consommateur : cadre et propositions fondées sur la théorie de la présence sociale

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