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Digitization of terrestrial television enables government to reallocate a portion of spectrum to satisfy the 5G low-band spectrum demand. To accelerate the digitization process, the Indonesian Government has distributed digital terrestrial television (DTT) decoders for households in several DTT trial areas so that the recipients are able to experience DTT broadcasts on their analogue television. To ensure that the DTT is adopted sustainably, this study aims to provide evidence-based policy recommendations by first understanding underlying factors of the intention to purchase a new DTT receiver, either a new DTT decoder or an integrated digital television (DTV).

This study uses 2018 survey data collected by Badan Aksesibilitas Telekomunikasi dan Informasi. The samples consist of 433 DTT decoder recipients in nine DTT trial locations in Indonesia. Two logistic models are used, one model for the DTT decoder and the other for integrated DTV. The two models have identical predictors, including respondents' demographics, television media use, technology cluster and DTT-related factors as innovation attributes.

The results indicate that the two models share some relevant variables but varying in sign and magnitude, namely, respondents' geographical location and the DTT picture and sound quality. The results also show that pay-television subscription, TV viewing and the difficulty of using the DTT decoder are other factors significantly associated with the intention to purchase a new DTT decoder.

This study has several limitations. First, the coefficients of determination are low, indicating that more independent variables should be included in the estimation models to obtain better insight about DTT adoption so that a better policy can be stipulated accordingly. Second, even though most of the predictors and proposed recommendations can be applied in general, all respondents of this study were DTT decoder recipients. Thus, future research can be more inclusive. Third, this study is designed based on the correlational model. This might cause the inability of the results to provide a conclusive direction of the relationship.

Demand-side and supply-side approaches are proposed to drive sustainable adoption of DTT, including the provision of subsidy or free DTT decoder for low-income households, increasing competition intensity among DTT devices manufacturers and distributors by allowing more players enter the Indonesian market, driving nationwide DTT infrastructure deployment and stipulating a national standard of the DTT devices.

This study enriches the understanding of the DTT adoption by incorporating geographical location variables for the proxy of infrastructure availability into the diffusion of innovation model, which has never been addressed by previous studies in the context of DTV adoption. In addition, this study focuses on a specific context in which all samples are free decoder recipients so that they have the same chance to experience DTT broadcasts.

This study aims to investigate the factors that influence the use of e-government services among male and female samples, aiming at gaining a deeper understanding of how to promote digital inclusion and maximize the benefits of digitalization.

This study uses binomial logistic regression modeling on two data sets: a nationwide survey at the individual level of 8,854 usable samples conducted in 2019 and village potential statistics.

The survey indicates low adoption and use of e-government services among both males and females. The statistical analysis further reveals that although there might be some variations in the influencing factors between the genders, the overall patterns are similar. These findings suggest that the low adoption and use of e-government services among males and females can be attributed to factors such as misperceptions about internet-based services, resulting in low motivation to use the services, inadequate internet connectivity, affordability, limited digital skills and exposure to harmful online content.

This study conducts a gender-disaggregated analysis to determine whether the antecedents of males’ decisions to adopt e-government services differ from those of females. Such a study is underrepresented in the extant literature, particularly in the context of e-government service use.

This study aims to establish an assessment model to measure big data readiness in the public sector, specifically targeting local governments at the provincial and city/regency levels. Additionally, the study aims to gain valuable insights into the readiness of selected local governments in Indonesia by using the established assessment model.

This study uses a mixed-method approach, using focus group discussions (FGDs), surveys and exploratory factor analysis (EFA) to establish the assessment model. The FGDs involve gathering perspectives on readiness variables from experts in academia, government and practice, whereas the survey collects data from a sample of selected local governments using a questionnaire developed based on the variables obtained in FGDs. The EFA is used on survey data to condense the variables into a smaller set of dimensions or factors. Ultimately, the assessment model is applied to evaluate the level of big data readiness among the selected Indonesian local governments.

FGDs identify 32 essential variables for evaluating the readiness of local governments to adopt big data. Subsequently, EFA reduces this number by five and organizes the remaining variables into four factors: big data strategy, policy and collaboration, infrastructure and human resources and data collection and utilization. The application of the assessment model reveals that the overall readiness for big data in the selected local governments is primarily moderate, with those in the Java cluster displaying higher readiness. In addition, the data collection and utilization factor achieves the highest score among the four factors.

This study offers an assessment model for evaluating big data readiness within local governments by combining perspectives from big data experts in academia, government and practice.