Web 2.0 is a technology that enables collaboration between citizens and the government to actualise the concept of open government. The adoption of technology in the public sector is known to have positive impacts in fostering public sector innovation, including in developing countries with various problems that require collaboration between citizens and the government. However, currently studies concerning open government technology adoption in developing countries are limited. Indonesia as an example of a developing and democratic country provides a suitable context to explore this phenomenon. Moreover, there are many local government institutions in Indonesia, especially on Java Island, that have implemented Web 2.0 to support open government initiatives. Therefore, this research aims to explore key factors influencing the adoption of the Web 2.0 platform by local government institutions in Indonesia. Multiple theories are combined to guide the exploration of the influencing factors related to technology, organisations, management, and the environment. Based on a multiple case study involving five local government institutions in Indonesia, we identified fifteen factors affecting the adoption of Web 2.0 technology. This study offers both research and practical implications that can be considered by government and other key stakeholders to optimise public participation and information access through the adoption of open government initiatives.

Despite the plethora of literature in sustainability and supply chain management in the recent years, a quantitative tool that measures the sustainability performance of an industrial supply network, considering the uncertainties of existing data, is hard to find. This conceptual paper is aimed at establishing a quantitative measure for the sustainability performance of industrial supply networks that considers aleatory and epistemic uncertainties in its environmental performance evaluation. The measure is built upon economic, environmental and social performance evaluation models. These models address a number of shortcomings in the literature, such as incomplete and inaccurate calculation of environmental impacts, as well as the disregard for aleatory and epistemic uncertainties in the input data and, more importantly, the scarce number of quantitative social sustainability measures. Dyadic interactions are chosen for the network, while the network members have a revenue-sharing relationship. This relationship promotes sharing of the required information for the use of the proposed model. This measure provides an approach to quantify the environmental, social and economic sustainability performances of a supply network. Moreover, as this measure is not specifically designed for an industrial sector, it can be employed over an evolving and diverse industrial network.

Enterprise Architecture (EA) allows firms to create value on the firm and operational levels. This paper argues that firms’ EA-driven dynamic capabilities lead to innovative value-creating actions and, ultimately, improve organizational benefits. Hence, we propose a theoretical model that explains how these dynamic capabilities enable the innovativeness of firms. Moreover, we explain the contingent role of an organic firm structure and its relation to firm innovativeness. Data within this study is collected from 299 CIOs and IT managers. This study uses a variance-based approach and a complementary fuzzy-set qualitative comparative analysis (fsQCA) to analyze the model’s hypothesized relationships. Our study outcomes demonstrate a positive relationship between EA-driven dynamic capabilities and firms’ innovativeness as well as between innovation and organizational benefits. Our post-hoc analyses using fsQCA reveal various circumstances in which organic firm structure and valuable, rare, inimitable, and non-substitutional (VRIN) firm resources are particularly relevant for firms to obtain high levels of firm innovativeness.

This study employs the critical hermeneutic approach to identifying current knowledge limitations and propose future research directions. Through five hermeneutic cycles of review, analysis, synthesis and interpretation of the existing literature and success stories reported by 30 small-and-medium enterprises (SMEs), this study identifies critical success factors (CSFs) that are unique to SMEs, frequently cited in the literature, and influential as perceived by SMEs. The study offers contributions by providing a synthesis of CSFs for SMEs; highlighting current knowledge gaps; proposing avenues for future research; and demonstrating the suitability of the critical hermeneutic approach to studying CSFs for ES implementation.

The concept of smart cities has gained significant attention due to the potential of smart cities to optimize city services and enhance citizens’ quality of life. Cities are investing in digital transformation to become smarter, sustainable, and resilient. Therefore, there is a need to build a comprehensive and holistic model to assess smart city initiatives. This paper aims to develop a model that can capture the maturity of smart city adoption across various functional domains. These domains are divided into focus areas that capture different dimensions of a smart city and grouped into seven groups: ICT, economy, environment, social, resources, services, and governance. Each focus area has a set of maturity levels that describe the capabilities and outcomes of the city at different stages of development. To develop the model, the focus areas were extracted from the literature based on 16 models that have been reviewed. Assessing these models helped in identifying gaps and building the foundation of the model. Using the information extracted from the literature, a focus area model was designed and developed. The model development included seven main phases, which were: scope, design, populate, test, deploy, and maintain. The current paper validates the proposed model using the Delphi method, which involves the participation of a panel of sixty field experts. The experts evaluated the model’s correctness and completeness based on their experience and provided feedback. This feedback was used to revise and finalize the model. The smart city maturity model provides a framework for benchmarking, planning, and improving smart city initiatives. Cities can use the model to measure their performance and evaluate their weaknesses and strengths. The model is also the most comprehensive in terms of the scope of the focus areas included, and the results show that the model has a high level of accuracy and consistency and can effectively assess smart city adoption.