Shared Services Management

Wang, Shouhong; Wang, Hai

doi:10.4018/ijisss.2015040103

Cited by 3 publications

(2 citation statements)

References 46 publications

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“…Therearemanyfactorsthatshouldbetakenintoconsiderationswhenassessingtheimpactof visualanalyticsonusers'performanceandproductivity.Sincemanydesignandevaluationissues havebeenwidelydiscussedinvisualanalyticsliterature(Chinchoretal.,2012),itwouldbeusefulto unfoldtheinfluenceoftheorganizationalfactorssuchasorganizationalstrategy,structure,cultureand processonusers'acceptanceandadoptionofvisualanalyticstechnology (Kassem,R.,Ajmal,M.,& Khan,M.,2016;Zeba,F.,&Ganguli,S.,2016;Wang,S.,&Wang,H.,2015).Forawideradoption ofvisualanalyticssystems,itisalsocrucialtotakeintoconsiderationtheinfluenceofmarketand industrycharacteristics.Togainthemostvaluefromintroducingvisualanalytics,bothindividual andorganizationalfactorsshouldbeintegratedandinvestigated(Grublješič&Jaklič,2015),because usersaloneoftendonotrecognizethetrueeffectofvisualanalytics.Suchevaluationworkneedsto takeintoaccountdifferenttypesofdataanddifferenttypesofuserswithdifferentproblemstosolve.…”

Section: Limitationsmentioning

confidence: 99%

Visual Analytics Adoption in Business Enterprises

Daradkeh

2019

International Journal of Information Systems in the Service Sector

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Visual analytics is increasingly being recognized as a source of competitive advantage. Yet, limited research has examined the factors deriving it organizational adoption. By integrating the technology acceptance model (TAM) with the task-technology fit (TTF) model, this research developed a model for visual analytics adoption in business enterprises. To test the research model, data was collected through a questionnaire survey distributed to 400 business professionals working in a variety of industries in Jordan. Collected data were tested and analyzed using structural equation modeling (SEM) technique. Findings of this research confirmed the applicability of the integrated TAM/TTF model to explain the key factors that affect the adoption of visual analytics systems for work-related tasks. Specifically, the results of this research demonstrated that the task, technology, and user characteristics are fundamental and influential antecedents of TTF, which in turn has a significant positive effect on the perceived usefulness and perceived ease of use of visual analytics systems. Additionally, there are significant positive effects from perceived usefulness and perceived ease of use toward users' intention to adopt visual analytics systems, and a firm relationship between perceived ease of use and perceived usefulness of visual analytics systems. Together all these constructs explain 59.9% of the variance in user's intention to adopt visual analytics systems at the workplace. Findings of this research provide several important implications for research and practice, and thus should help in the design and development of more user-accepted visual analytics systems and applications.

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Section: Limitationsmentioning

confidence: 99%

Visual Analytics Adoption in Business Enterprises

Daradkeh

2019

International Journal of Information Systems in the Service Sector

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“…The effective operation is possible when all the stakeholders identify each other's value propositions and try to convert them into collective advantage. Then arises a need to adopt technologies for shared services while adhering to the group strategy and ethics (Wang & Wang, 2015). The objectives of edu-tourism are then better fulfilled by:…”

Section: Excellence Of Education Tourismmentioning

confidence: 99%

Supply Chain View of Tourism

Panda

2021

International Journal of Applied Management Theory and Research

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Tourism being observed as a supply chain, this article describe its practices under a conceptual research framework with a special reference to education tourism. The author projects the education tourism as a continuum where both service supply chains of education and tourism are integrated. The research implication is directed towards the cross-sectoral objectives of communities involving the tourists, students and destination communities. The original thoughts and value propositions in this research are portrayed as a supply chain framework. Unlike goods supply chain management, the service supply chain of education tourism grows complex due to the coexistence of the overlapping service objectives for education and tourism. Education tourism deals with students and tourists frequently interchanging their roles; leveraging the services of the vendors and outsourced partners. The increasing complexity of education tourism demands smart technology applications to manage it as an integrated total supply chain.

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