Is big data used by cities? Understanding the nature and antecedents of big data use by municipalities

Ali, Hamza; Titah, Ryad

doi:10.1016/j.giq.2021.101600

Cited by 8 publications

(8 citation statements)

References 87 publications

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“…Organizational factors refer to an organization’s structure, resources and internal communication, such as linking structures, financial resources and communication processes (Lorente-Martínez et al , 2020; Srivastava et al , 2022). Environmental factors refer to external pressures and support like competitive pressure, partner pressure, regulatory support and partner support (Ali and Titah, 2021; Chatterjee et al , 2021a; Yang et al , 2015). According to Enholm et al (2021), organizational AI use is influenced by technological, organizational and environmental factors, and subsequently influences the process- and firm-level performance.…”

Section: Theoretical Background and Hypothesesmentioning

confidence: 99%

“…This capability depends on not only the company’s absorption of new technologies but also the guidance, encouragement and investment from top management. Management support is defined as the degree to which management members understand and value the functionality of new technologies (Ali and Titah, 2021). Managers can not only provide resources to support the implementation of innovative projects but also provide strategic directions for organizations to achieve competitive advantages (Hsu et al , 2019).…”

Section: Theoretical Background and Hypothesesmentioning

confidence: 99%

“…Perceived AI risk was measured using two items adopted from Cao et al (2021). Management support was measured using four items from Ali and Titah (2021) and Alam et al (2016). Innovativeness was measured using three items adopted from Kim et al (2018).…”

Section: Measurement Scalesmentioning

confidence: 99%

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Investigating the determinants of performance of artificial intelligence adoption in hospitality industry during COVID-19

Chen

Zhou

et al. 2022

IJCHM

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Purpose Drawing on the technology-organization-environment (TOE) framework, this study aims to investigate determinants of performance of artificial intelligence (AI) adoption in hospitality industry during COVID-19 and identifies the relative importance of each determinant. Design/methodology/approach A two-stage approach that integrates partial least squares structural equation modeling (PLS-SEM) with artificial neural network (ANN) is used to analyze survey data from 290 managers in the hospitality industry. Findings The empirical results reveal that perceived AI risk, management support, innovativeness, competitive pressure and regulatory support significantly influence the performance of AI adoption. Additionally, the ANN results show that competitive pressure and management support are two of the strongest determinants. Practical implications This research offers guidelines for hospitality managers to enhance the performance of AI adoption and presents policy-making insights to promote and support organizations to benefit from the adoption of AI technology. Originality/value This study conceptualizes the performance of AI adoption from both process and firm levels and examines its determinants based on the TOE framework. By adopting an innovative approach combining PLS-SEM and ANN, the authors not only identify the essential performance determinants of AI adoption but also determine their relative importance.

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Section: Theoretical Background and Hypothesesmentioning

confidence: 99%

Section: Theoretical Background and Hypothesesmentioning

confidence: 99%

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Investigating the determinants of performance of artificial intelligence adoption in hospitality industry during COVID-19

Chen

Zhou

et al. 2022

IJCHM

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“…Big Data as an OGD practice also premises positive impact on the functioning of the cities such as significant effects on economic growth and cost savings. Ali and Titah (2021) report that the value of Big Data for the European public sector is approximately 250 billion US Dollars per year (Ali and Titah, 2021).…”

Section: -The Institutional Applications Of Ogdmentioning

confidence: 99%

Bir Yerel Hizmet Olarak Açık Yönetişim Veri Uygulamaları: Türkiye’de Büyük Şehir Belediyelerinden Örnekler

GÜNDEM

2022

Kent Akademisi

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Municipalities are one of the most important stakeholders of the civic engagement between the local authorities and society in terms of databased governance. That's why it is important to measure the efficiency of Open Government Data (OGD hereinafter) practices at the local level. This study aims to investigate the extent to which OGD practices as a part of local services provided by metropolitan municipalities in Turkey. Supporting local authorities in terms of the OGD practices in the United States in 2009 has caused significant change not only in local governments of the United States but also in various municipalities all over the world. These caused further debate about the contents of data that has been disclosed by local authorities. Although the debate about the transparency, participation, and collaboration between the municipalities and society kept the interest alive for the OGD practices, there is not much to say for Turkey's metropolitan municipalities. Therefore, this study fills an important gap in OGD practices in Turkey. Currently, there are only four metropolitan municipalities consisting of Istanbul, Izmir, Balikesir, and Konya Metropolitan Municipalities that have open data portals. In that context, this study attempts to take a

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“…It is necessary to use the status quo as the research basis, but also to evaluate the future development of the curriculum to ensure that the evaluation indicators are still consistent with the future development and are at the forefront of curriculum development. [28][29][30][31]. The first is to reasonably determine the proportion of each project in the evaluation template, so as to realize the overall planning of the index input.…”

Section: Principles Of Feasibility and Developmentmentioning

confidence: 99%

The Evaluation of University Course Quality under the Background of Wireless Communication and Big Data

Bo-en

2022

Wireless Communications and Mobile Computing

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In recent years, education issues have been the focus of attention from all walks of life. An important indicator for measuring the level of education in colleges and universities is the quality of teaching. It determines the level of the students' basic quality that is the target of training. Curriculum is the core of forming teaching quality and the core element of cultivating talents. Curriculum evaluation is an important means to detect and diagnose the teaching quality of schools and the source of talent training quality.The purpose of this article is to study the quality evaluation system of college courses under the background of wireless communication and big data, taking students as the initiators of evaluation activities, positioning the factors that they are interested in, and referring to the selection of evaluation indicators in other research results to determine the evaluation system of this study. Through students’ evaluation of Japanese MOOC courses, the evaluation system constructed by the laboratory is evaluated. The method of collecting evaluation data is to issue electronic questionnaires and then perform statistical analysis on the results of the questionnaires after collection, to understand the current status of MOOC course learning and the degree of recognition between learners and evaluation indicators. Through the analysis of the questionnaire data, the reliability and validity of the questionnaire are tested to ensure the validity and reliability of the questionnaire data. The evaluation indicators are screened by factor analysis, and the entropy method is used to determine the weight of the evaluation indicators, thus forming the final MOOC course evaluation. Reorganizing and constructing the Japanese curriculum quality evaluation index system conforms to the general law of the construction of the index system.

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Is big data used by cities? Understanding the nature and antecedents of big data use by municipalities

Cited by 8 publications

References 87 publications

Investigating the determinants of performance of artificial intelligence adoption in hospitality industry during COVID-19

Investigating the determinants of performance of artificial intelligence adoption in hospitality industry during COVID-19

Bir Yerel Hizmet Olarak Açık Yönetişim Veri Uygulamaları: Türkiye’de Büyük Şehir Belediyelerinden Örnekler

The Evaluation of University Course Quality under the Background of Wireless Communication and Big Data

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