Bringing It All Together: The Digital Town Readiness Framework

Digital technologies are an increasingly important part of societies and economies. International benchmarks suggest that countries and cities worldwide are progressing in their digitalisation efforts. Unfortunately, some parts of society and the economy are under-represented in extant measurement frameworks and composite indices and are in danger of being left behind. This chapter presents an integrated framework for measuring and benchmarking the evolution and development of digital towns. The Digital Town Readiness Framework can be used to obtain an initial characterisation and understanding of key sectors and enabling infrastructure in smaller and rural towns, develop plans for the digital transformation of towns, and benchmark progress against regional, national and international indicators. Methodology and implementation considerations are also presented.


IntroductIon
In the previous chapters, we have explored the digital society and digital economy from seven different perspectives and discussed how international frameworks and composite indices have sought to measure key aspects of these dimensions, or not. In many respects, important aspects of society, and indeed the economy, are not considered adequately in these frameworks. Civil society, nonformal and informal education, new places of work and ways of working, and various cohorts of the population are just some of the aspects under-represented in these sets of indicators. While there is a burgeoning ecosystem of international indicators for digital progress (G20 Digital Economy Task force, 2020), smaller and rural towns are largely absent or under-represented. This chapter seeks to advance the way in which digital initiatives are measured and managed for and by smaller and rural towns. The proposed integrated framework combines both societal and economic perspectives through the seven dimensions discussed in previous chapters, established indicators used by intergovernmental and international organisations, and proposed indicators relevant to rural towns, to arrive at a measurement framework for digital towns. Our hope is that this Digital Town Readiness Framework (DTRF) can be used by town leaders, local authorities and associations, policymakers, and indeed scholars, to: • obtain an initial characterisation and understanding of the digital readiness of a town; • enable a dialogue between stakeholders on the potential for digitalisation and digital transformation within towns; • inform and assess progress of digital town initiatives, strategies and plans; and, • benchmark progress against other towns, and regional, national and international benchmarks.

desIgn PrIncIPles
This section outlines some of the major design principles informing the DTRF design, namely inclusiveness, commonality, context-sensitivity, modularity, multidirectionality, and once-only.
1. Inclusiveness (P1): the framework should be inclusive with respect to "the where", "the who", "the what", and "the how". Consideration should be given to all parts and actors in smaller and rural towns and their environs ("the where"), and particularly those in risk of social and digital exclusion ("the who"). The boundaries of rural communities are often blurry and may include citizens outside of the immediate townlands as defined by administrative authorities. Attention should be given to what infrastructure and activities those actors are excluded from ("the what") and policies or actions that can reduce the risk of exclusion ("the how"). 2. Commonality (P2): the framework should share features and attributes with other national and international measurement frameworks to ensure comparability. As such, where possible agreed definitions, standards and guidelines for data collection and analysis should be used. Where such statistical definitions and standards are not available from intergovernmental or international organisations, validated scales from academic literature should be used, if appropriate. 3. Context-sensitivity (P3): the framework should allow for local contexts and priorities. Towns are complex human and physical systems, made more complex by the inclusion of a digital layer. While general indicators remain important, relative importance may vary from town to town and similarly may change over time at different rates (Miller et al., 2013). By allowing for context-sensitivity, frictions between regional and national stakeholders and local stakeholders can be avoided. As well as geographic, social, and economic contexts, the administrative and financial resources available to collect and analyse data, and the ability to take action resulting from such an activity should be taken into account. 4. Modularity (P4): the framework should be designed in such a way that at least some dimensions and indicators are optional and there exists the ability to add or remove dimensions and indicators according to the needs and priorities of a given town or set of stakeholders. This provides stakeholders with greater choice and flexibility. Each dimension should provide value in its own right without the need to implement the whole framework. Modularity introduces greater reflexibility and can reduce both implementation complexity and cost. 5. Multidirectionality (P5): the framework should be designed in such a way that it can be implemented in top-down, bottom-up, or ideally a combination of both. As discussed throughout the book, notwithstanding this general principle, we believe digital town initiatives should, where possible, be primarily community-driven (i.e., bottom-up) with support from regional or national government. 6. Once-only (P6): where possible, data should be collected from actors in a community only where such data is not available through other sources e.g., public websites and databases, or existing government sources. This can reduce the administrative burden of implementing the framework and accelerate the speed of implementation.

the dIgItal town readIness Framework (dtrF)
The Digital Town Readiness Framework seeks to assess the state of preparedness for a town for full participation in a Digital Society, one whose social structures and activities, to a greater or lesser extent, are organised around digital information networks that connect people, processes, things, data and networks (Lynn et al., 2018). To support commonality and comparison (P2), we adapt a similar approach to the G20 framework design for measuring the digital economy (G20 DETF, 2020). This definition clarifies the context for which our framework has been designed and leads to the next step of the design i.e., determining what are the key elements that determine and affect the digital readiness of a town and how they relate to each other. The discussion regarding key elements of a digital town is ongoing and could not be otherwise given the continuous changes in the technological landscape and their impact on people's life. However, based on the literature presented in previous chapters, we propose that at least three enabling infrastructures-Digital Connectivity, Digital Education, and Digital Town Governance-and four sectors of the economy-Digital Citizens, Digital Public Services, Digital Business and Digital Civil Society-should be considered. In line with P3, additional sectors could also be added to reflect local priorities (e.g., digital tourism, smart agriculture etc.) or future technological developments.
For each enabling infrastructure and sector, a set of indicators needs to be agreed and weighted (P3) with consultation from stakeholders with regard to both horizontal and vertical integration. While it is important that indicators enable national and/or international comparison, it is particularly important that the selected indicators are logistically feasible to collect while (1) providing a comprehensive, meaningful and nuanced picture of the digital readiness of a town (P1), (2) sufficiently complete from a benchmarking perspective (P2), and (3) in line with local priorities and goals (P3).
Once indicators are agreed and data collected, the results of the assessment must be analysed and communicated appropriately to stakeholders. This dissemination stage enables evidence-based policy-making and community and stakeholders participation (P1; P6). The feedback gathered through dissemination will then feed into a development plan which outlines the town's journey to increase its digital readiness and will ultimately influence the town's future goals and priorities. In fact, a town's goals and corresponding drivers may change over time to reflect changing priorities and ambitions.

dIgItal town dImensIons, sub-dImensIons, and IndIcators
The Digital Town Readiness Framework comprises seven dimensions in its generic form: Each of these comprise a number of sub-dimensions and indicators. The following subsections present potential indicators and benchmarks, where available.

Digital Citizens
Access to digital connectivity is a pre-requisite for the widespread adoption and usage of digital technologies by citizens but it must be combined with the appropriate competences and skills to realise the full benefits of a digital society. The Digital Citizen dimension focuses on the competence and usage of digital technologies by citizens in a town. Table 9.1 presents a list of potential indicators for measuring the digital readiness of citizens.

Digital Public Services
As outlined in Chap. 3, we define Digital Public Services as the use and sophistication of digital technology by local government and health service providers, and the availability of local open data. E-Government is commonly defined as "the use of IT to enable and improve the efficiency with which government services are provided to citizens, employees, businesses and agencies" (Carter & Bélanger, 2005, p. 5). As Singh et al. (2020) point out, it is important to place the citizen at the centre of e-Government performance assessment. Our proposed framework follows this recommendation and applies a citizen-centric to Hiller and Bélanger's (2001) five-level maturity framework i.e., (1) information, (2) two-way communication, (3) transaction, (4) integration, and   (5) participation. In addition, we include mobile and desktop usability as an indicator of digital readiness. For comparability, we use similar indicators to Digital Economy and Skills Unit (2020). Table 9.2 presents a list of potential indicators for measuring e-Government digital readiness. e-Health can be defined as "the use of Information and Communication Technologies (ICT) across the whole range of healthcare functions" (European Commission, 2004). As such, e-Health comprises a wide range of applications that can generate significant benefits for citizens, healthcare professionals and organisations, and public authorities (Bodell et al., 2004;Delpierre et al., 2004;Kaushal et al., 2006;Øvretveit et al., 2007) (see Chap. 3 for a more extensive discussion). Existing frameworks that aim to assess the maturity of e-Health practices in different countries tend to focus on the adoption of these technologies by general practitioners (GPs) as they represent the main point of contact between the healthcare system and citizens and therefore play a central role in facilitating access to, and delivery of, care (Macinko et al., 2003;Atun, 2004). However, other healthcare service providers like pharmacies and specialised doctors (e.g., physiotherapists, orthodontists, etc.) may also play a critical role in promoting the adoption of e-Health services (Gregorio et al., 2013;Vorrink et al., 2017;Baines et al., 2018). For this reason, our proposed framework is based on a wider definition of health service provider that includes GPs, pharmacies and specialised doctors. Table 9.3 presents a list of potential indicators for measuring e-Health adoption in rural towns by health service providers. The use of e-Health by individuals is measured in Digital Citizen.
The last component of the Digital Public Services dimension is Open Data. This is commonly defined as "data that can be freely used, shared and built-on by anyone, anywhere, for any purpose" (James, 2013). More specifically, the focus of our framework is on Public Sector Information (PSI) which is specifically concerned with "making public sector information freely available in open formats and ways that enable public access and facilitate exploitation" (Kalampokis et al., 2011, p. 17). Open data in general and PSI in particular has the potential to deliver a wide range of political and social, economic, and operational and technical benefits (Janssen et al., 2012), and to bridge the gap between government and citizens therefore enhancing inclusion and social participation (European Commission, 2018).
Given the positive effects that open data can generate for the economy and the society as a whole, we include it as a component in our proposed framework to uncover evidence of local government availability of an open

Digital Business
As discussed in Chap. 4, the adoption and use of digital technologies provides clear benefits to businesses in rural towns. These benefits mostly relate to the exploitation of new revenue streams, new business models and faster time to market that are enabled by digital technologies. The assessment framework proposed in this book includes two sub-dimensions related to the availability of a documented plan to increase use of digital technologies by businesses in the town and the prevalence of firm-level plans for digital business. As per Digital Economy and Skills Unit (2020), the assessment should also include sub-dimensions on business digitisation and ecommerce but also the availability of digital equipment and next generation technologies. Table 9.5 presents a list of potential indicators for measuring digital business penetration in rural towns. The Digital Town Readiness Framework is a firm-level assessment. Town stakeholders may decide to focus on a local digital economy index by adapting existing digital economy frameworks/indexes.

Digital Civil Society
Civil society, often referred to as "the third sector", "the independent sector" or "the nonprofit sector", can be defined as the group of social institutions outside the confines of households, the market and the state (see Chap. 5 for a more in-depth discussion on the definition of civil society). These include charities, sports and social clubs, political parties etc. While there are indices to measure digital social innovation (e.g., Bone et al., 2018), they tend to focus on innovation or social entrepreneurship ecosystems rather than the use of digital technology more generally by civil society. Similarly to businesses, civil society organisations (CSOs) can generate value and exploit new opportunities enabled by digital technologies leading to lower costs, new revenue streams and higher quality of service (O'Grady & Roberts, 2019;Ehnold et al., 2020;Walker et al., 2020). The assessment framework proposed in this book includes similar sub-dimensions as those for businesses although adapted to the CSO context. Table 9.6 presents a list of potential indicators for measuring the adoption and use of digital technologies by civil society groups in rural towns.

Infrastructure for Digital Connectivity
Infrastructure for Digital Connectivity is the foundation for the digital society and digital economy. Based on extant literature, our framework includes a connectivity dimension with a number of sub-dimensions relating to the availability, quality, adoption and use of connectivity. Table 9.7 presents a list of potential indicators for assessing digital connectivity in rural towns.

Digital Education
It is well-established that digital technologies can radically change the nature of teaching and learning. This has become particularly evident in the backdrop of the COVID-19 pandemic. Digital Education, as interpreted in this book, relates to the support for use and sophistication of digital technology in education and the provision of digital skills training for all levels. While a number of measurement frameworks for digital education have been proposed over the years, they tend to either focus on Internet access and computer availability in formal education (e.g., Katz & Callorda, 2018) and therefore ignore all other education service providers (e.g., pre-primary or older citizens training initiatives) or do not consider digital adoption and usage in education at all (e.g., Digital Economy and Skills Unit, 2020). Our proposed framework includes the availability of documented plans at both a town-level and institution-level for digital skills provision and integration for all levels of education and age levels and a range of indicators to assess the actual adoption of digital technologies by education providers. Table 9.8 presents a list of potential indicators for assessing digital connectivity in rural towns.

Governance of Digital Town Initiatives
The experience of previous digital town projects clearly highlights that the delivery of complex and multifaceted policy objectives such as digitalisation requires significant coordination among a wide range of stakeholders. As such, it requires appropriate governance mechanisms that enable widespread participation while also guiding the implementation of the policy objectives. In Chap. 8 we identify two main types of governance mechanisms that are particularly relevant in the context of digital town initiatives i.e., horizontal and vertical integration. While horizontal integration refers  For more details on price baskets refer to OECD (2017) fFor a classification of digital hubs refer to Rundel et al. (2020)  % of education providers with a mobile responsive website or mobile app Education providers with a mobile friendly website % of education providers paying to advertise on the internet Education providers that use online advertisements (e.g., Google Ads, Facebook Ads etc.) % of education providers making sophisticated use of online advertising Education providers that use sophisticated online advertising (e.g., retargeting, tracking etc.) % of education providers using cloud computing services Education providers that use cloud hosting or other cloud services % of education providers selling or accepting payments online Education providers that have a website with e-Commerce functionalities and/or accept payments online % of education providers with social media presence Education providers with at least one social media page/ profile (e.g., Facebook, Twitter etc.)

Access % of education providers with a Virtual
Learning Environment (VLE) Education providers with a Virtual Learning Environment (VLE)  to integration across different elements of policy making, and across policy and other stakeholders, vertical integration is mostly concerned with integration between political, social, and economic institutions which may facilitate access to resources and coordination with higher level policy objectives. Table 9.9 presents a list of potential indicators for assessing digital town governance.

methodologIcal consIderatIons
As has been mentioned in previous chapters, data collected for national and international statistics are very rarely available at a town level. While secondary data may be available from other sources (detailed fixed and mobile broadband coverage, for example, tends to be available through national communication regulators-see, for example, ComReg, 2021), primary data collection is required for most (if not all) indicators included in a town's assessment. This poses significant challenges in the terms of resources required, accuracy, and national and international comparability.
In this section, we outline some basic principles and guidelines that should be considered when planning and rolling out data collection using the Digital Town Readiness Framework.

Selection of Indicators
Most of the intergovernmental and international frameworks discussed in previous chapters rely on data that is collected frequently by national or international agencies. In this respect, international benchmarking is easier due to the availability of data and widespread compliance with internationally accepted standards and practices set by relevant bodies. As discussed, data is unlikely to be available for most indicators for a specific town, therefore those seeking to assess a specific town (an assessor) needs to take into account the relevance, feasibility, and frequency of data collection. Where possible, indicators should be based on international standards and assessors should use extant standards and guidelines for designing data collection instruments and analysis to aid validity, interpretability, and comparability (P2, P6). To aid periodic comparison, typically yearly, indicators should be reviewed and updated regularly while optimising historic and external benchmark comparability (P2). Context-sensitivity (P3) and modularity (P4) are important design principles in the Digital Town Readiness Framework. For example, tourism is a national and local priority in many countries and rural communities. In an earlier work, a rapid Digital Town Readiness Framework was developed and implemented in five rural Irish towns with digital tourism as one of the dimensions reflecting Irish regional and national priorities (Lynn et al., 2020;.IE, 2021). Similarly, agriculture is a significant sector in many rural communities and the e-agriculture readiness may warrant additional emphasis (Trendov et al., 2019).

Data Collection
There are a number of challenges in collecting representative data in smaller and rural towns. Firstly, while the once-only principle (P7) is a central design principle of the Digital Town Readiness Framework, the full range of data is unlikely to be available from national sources due to the sampling strategies such sources employ. A multi-directional (P5) approach is needed because top-down methodologies often fail to capture local complexity (G20 Digital Economy Task Force, 2018). Secondly and relatedly, some local actors, for example those in schools and businesses, may be time-poor and suffer from survey fatigue. In these cases, one tactic may be to reduce the time and effort required by requesting their data submission for other studies or statistical exercises and then focusing only on missing data. Thirdly, some segments of society are difficult to survey e.g., the most vulnerable in society and those who are not currently digitally active. Consequently, online surveys may not be suitable and either face-to-face or telephone surveys may be more appropriate. These factors can result in relatively high data collection costs and lengthy data collection times particularly for the Digital Citizen dimension. A bottom-up community-driven initiative, combined with top-down secondary data, may be more cost efficient and effective due to local relationships and knowledge (P5). Online crawlers can be used in some cases for website-based data collection and may prove fruitful for rapid assessment of web-based activity, however these cannot be considered complete or authoritative. For example, a website may still be live while a company has closed.

Data Preparation and Cleaning
It is likely that raw data will be sourced from primary and secondary sources. Qualitative data will be subject to interpretation by coders.
To avoid bias and optimise objectivity, clear data coding guidelines and ideally multiple coders should be used. Even where quantitative data is sourced, it may be presented in different units, time periods, or spatial coordinates. Similarly, data quality and the level of granularity may vary over time. This data will need to be cleansed and normalised before aggregation. In addition, for multi-period comparison, a policy should be set for handling missing values. Where possible, follow data preparation methodologies similar to the framework you wish to benchmark against, see for example Digital Economy and Skills Unit (2020).

Weighting and Aggregation
Context sensitivity (P3) is an important consideration when assessing a town. As well as selecting relevant dimensions, sub-dimensions and indicators, the relative weighting of indicators, sub-dimensions, and dimensions can be weighted to reflect the priorities of the town or given equal weighting. For example, Digital Economy and Skills Unit (2020) uses differential weights at the dimension and sub-dimension level reflecting EU policy priorities whereas the IDI (ITU, 2016) uses a differential weighting at the sub-indices level and equal weights for indicators (see Tables 9.10 and 9.11). There are a variety of weighting techniques including simple additive weighting, weighted product, weighted displaced ideal and ordered weighted averaging methods. Similarly, there are a number of methods for determining weights. This will depend on the purpose and complexity of analysis one wishes to undertake. Once weighted, care needs to be taken that aggregation calculations are computed correctly and consistently.

Sensitivity Analysis
A sensitivity analysis may be carried out to assess the robustness of the assessment results to different aggregation methods or weighting. Potential differences in the final results may be due to, for example, selection of indicators, data normalisation procedures or weighting. The sensitivity analysis would reveal how changes in any of these processes would affect the final results of the assessment. In the absence of errors in the assessment design, data collection or aggregation, the conclusions reached following the assessment should not vary dramatically.

Stakeholder Support and Communication
Communicating with a wide range of stakeholders is a significant challenge characterised by varying degrees of interest and influence/power. Understanding the nature of these different stakeholders, how and what to communicate to them, is a critical success factor in driving participation and support for a digital town initiative but also gaining consensus. The Digital Town Readiness Framework can generate a lot of data on a town which can be complex to communicate in a positive way. Care needs to be taken in how results of digital town readiness assessments are communicated to avoid negative backlash, demotivation, and disengagement. Data interpretation is a key consideration. For example, the .IE Digital Town Blueprint (.IE, 2021) aggregates scores across each dimension and sub-dimension and presents them as a cobweb diagram across a spectrum readiness from non-existent to leading as outlined in Table 9.12. Identifying appropriate local digital champions for different stakeholders, dimensions and sub-dimensions may make data collection easier and less costly but will also ensure greater buy-in and support for subsequent actions. As well as local digital champions, there are a wide range of engagement methods including collaborative teams/task forces, town/ community meetings, and of course online methods including websites, email newsletters, and social media. Non-existent Digital Readiness is non-existent or at a very low level-The use and sophistication of digital technologies and capabilities likely do not exist. If they do exist, they are at very low levels of use and sophistication, largely informal and not documented, managed or measured at a town level. Key performance indicators (KPIs) are significantly below regional, national or EU averages 2 Ad Hoc Digital Readiness is ad hoc and mostly not Documented-Some evidence of digital readiness in the use and sophistication of digital technologies and capabilities. Most are not documented and not managed. Performance may be measured and reviewed periodically but mostly informally. KPIs are below regional, national or EU averages 3 Defined/competitive Digital Readiness is clearly defined and documented-There is clear evidence of digital readiness. Use and sophistication of digital technologies and capabilities are documented and planned. KPIs are competitive relative to peer towns and regional, national and EU averages 4 Significant/differentiating Digital Readiness is clearly differentiating and Significant-The use and sophistication of digital technologies and capabilities and levels of digitalisation are significant and clearly differentiating compared to peers. KPIs are higher relative to peer towns and regional, national and EU averages 5 Leading Digital Readiness is leading-The use and sophistication of digital technologies and sophistication and levels of digitalisation are best-in-class and approaching optimum states/full digitalisation with clear plans for further optimisation. KPIs are at the highest levels when compared to peers and regional, national and EU averages 9.6 conclusIon All towns are different -however they, by and large, face many of the same problems. Digital technologies offer a solution for some of these problems. Unfortunately, very little is known about the state of digitalisation in smaller and rural towns. While the COVID-19 pandemic accelerated use of digital technologies by many, it also highlighted not just one digital divide but many. To reap the social and economic benefits of digitalisation in rural communities requires improved access to digital infrastructure and more sophisticated use of digital technologies, underpinned by more advanced digital competences and skills. The Digital Town Readiness Framework offers local communities, policy makers, and scholars an initial set of indicators upon which to develop digital town initiatives, and measure progress. For those ready to embrace the opportunity, it is a pathfinder on the road to a more equitable and impactful digital society. reFerences