This study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines the advantages of the complementary use of cross-correlation analysis and machine learning classification algorithms; (ii) applying the multi-class HPI values classifier which allows predicting the housing price increase, decrease or relative stability; (iii) exploiting the SVI that relates to interests in both ‘real estate’ and ‘credit to buy real estate’; (iv) evaluation of the introduced approach in the context of the Polish real estate market. The main theoretical contribution of our work is a confirmation that the freely available information regarding Google user searches can provide an in-depth insight into enriching the generally accepted statistics on supply and demand in the real estate market. From the practical perspective, this research confirms that SVI can be associated as a sole determinant to anticipate the housing price change with time-lag sufficient for making decisions regarding the purchase (sale) of individual property or the real estate market control. Such findings can be also helpful for researchers who intend to use Google Trends data as an extra variable from demand side to improve the prediction accuracy if it is included in the model which is based on the existing housing prices determinants.

Purpose: It has been underscored in the extant literature that open government data (OGD) has not percolated across the length and breadth of any country, let alone the awareness of the OGD among the stakeholders themselves. In this vein, this study aims to underline the reasons as to why OGD promotion merits consideration apart from underlining the manner in which OGD promotion may be done. Design/methodology/approach: Based on literature review on the OGD conceptual models and government promotion initiatives, the study further sketches an OGD model across four quadrants: beginners, followers, fast-trackers, trend-setters on the basis of the progress made in their OGD initiatives besides underlining the four elements of OGD promotional strategy as media, arena, substance and stakeholders. Also, the study explores the drivers and barriers to OGD promotional initiatives. Findings: The study shows that across the OGD quadrants, the promotional strategies vary in terms of the 4As (acceptability, affordability, accessibility and awareness), and the same get reflected across MASS. Further, the drivers for OGD promotional initiatives are building citizens’ trust and forging stakeholder participation and collaboration in administration, thereby furthering transparency in administration, meeting the needs of the stakeholders, providing the desired impetus to value creation and innovation by the stakeholders and the need for furthering economic growth. Likewise, the barriers toward OGD promotion are linked with the lack of political will, lack of organizational leadership, mission and vision, lack of involvement of government departments, lack of budget and lack of requisite infrastructure for promotion. Originality/value: Hitherto, OGD research has underscored the need to make the users aware of the potential of OGD initiative; however, no study has been undertaken to understand the manner in which the awareness may be driven among the users – the present study is a first step in this direction.