Smart city technology is only considered in some cities depending on the resident requirements, whereas smart initiatives are adopted easily in others. One of the first critical steps toward understanding these aspects of Malaysian smart cities is to empirically study the citizens’ and government agencies’ aspirations to use smart city services. A Malaysia Smart Cities Stakeholders Adoption Model (MSCSA) as a case study based on the unified theory of acceptance and use of technology (UTAUT2) is being developed and evaluated in Kuala Lumpur, Malaysia. An in-depth interview with expert staff from the Plan Malaysia smart city department and Telekom Malaysia Berhad (TM one) was conducted using a mixed-methods approach. To determine the influence of seven parameters on behavioural intentions, specifically the choice to build a smart city, quantitative data were collected as questionnaires. These parameters were self-efficacy, expected effort, perceived security, perceived privacy, price value, trust in government, and trust in technology. Citizens’ intentions to use smart city services were significantly influenced by each of these characteristics. There is a definite association between perceived privacy and perceived security as a core aspect of trust in technology, as well as price value, a core aspect of trust in government. When the trust in both these is strong, stakeholders are more willing to adopt and pursue smart city services. These studies provide city officials with a technique for measuring citizen desire for smart city services, as well as outlining the components necessary for establishing a good smart city strategy that is successful.

In this paper we describe a real-time shadow generation with volume shadow algorithm in virtual

This paper examines the phenomena of the local government’s inadequate reaction to the national programme of geographical infrastructure for the effective sharing of spatial data in Malaysia. We investigate the determinants of sharing data for Malaysia’s spatial data infrastructure (SDI) and aim to define the model for spatial data-sharing of Malaysia’s local SDI. The main contribution of this paper is an explanation of the novel methodology to study factors that affect spatial data sharing including a new qualitative analysis method through an interview with people concerned in this field, including engineers, technicians and academics, which was undertaken in Kuala Lumpur, and a new methodology to identify the necessary approach that affects spatial data sharing. An interview and a questionnaire were used in this study as part of a sequential exploratory approach. Among land use, Plan Malaysia, and Telekom Malaysia Berhad TMOne, 15 participants were interviewed in-depth to obtain their responses, and 83 individuals took part in the survey questionnaires. Interview data were measured by content analysis, while questionnaire data were measured by partial least squares analysis. In the structural model analysis, Smart PLS was used to choose the fit items based on validity and reliability measurements. According to the hypothesis measurement, technology and organisation both significantly affect the practice of spatial data sharing, but human resources and spatial data do not significantly affect it. All R-Squared values represent a value above 56 per cent for the human resource aspect, technology aspect and spatial data aspect. However, the R-Square value for spatial data sharing is 47%. Spatial data and human resources have a less substantial impact on spatial data sharing; hence, this study proposes a national awareness programme and mentoring to improve local SDI support for spatial data sharing.

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