E-participation initiatives help combat corruption in nations, but variations in urban–rural distribution of political power and the spread of social media disinformation by governments threaten their effectiveness. Through a cross-country analysis spanning 141 countries, we demonstrate the importance of a pro-rural approach in boosting the impact of e-participation initiatives on reducing corruption. Furthermore, we show that increased transparency and accountability from e-participation discourage governments from engaging in social media disinformation campaigns, ultimately lowering corruption levels. A configurational perspective shows that tackling corruption requires a multifaceted approach, with control of disinformation playing a key role. This study advances our understanding of general deterrence and urban bias theories, emphasizes the need for a multi-pronged approach to fight corruption, and identifies potential obstacles in fully realizing the benefits of e-participation initiatives.

ABSTRACT Many programming languages and technologies have appeared for the purpose of software development. When choosing a programming language, the developers' cognitive attributes, such as the Big5 personality traits (BPT), may play a role. The developers' personality traits can be reflected in their social media content (e.g., tweets, statuses, Q&A, reputation). In this article, we predict the developers' programming language preferences (i.e., the pattern of picking up a language) from their BPT derived from their content produced on social media. We randomly collected data from a total of 820 Twitter (currently X) and Stack Overflow (SO) users. Then, we collected user features (i.e., BPT, word embedding of tweets) from Twitter and programming preferences (i.e., programming tags, reputation, question, answer) from SO. We applied various machine learning (ML) and deep learning (DL) techniques to predict their programming language preferences from their BPT. We also investigated other interesting insights, such as how reputation and question‐asking/replying are associated with the users' BPT. The findings suggest that developers with high openness, conscientiousness, and extraversion are inclined to mobile applications, object‐oriented programming, and web programming, respectively. Furthermore, developers with high openness and conscientiousness traits have a high reputation in the SO community. Our ML and DL techniques classify the developers' programming language preferences using their BPT with an average accuracy of 78%.

DevOps is a methodology that seeks to unify development and operations teams in organizations, aiming to facilitate faster software delivery and promote collaboration to build a positive company culture. Our research aims to investigate the current state-of-the-art of DevOps, align academic research with industry practices, and identify critical success factors. We conducted a comprehensive literature review using a variety of databases and search engines, which revealed that several factors are essential to the success of DevOps, including DevOps culture, automation processes, continuous integration, and deployment, monitoring, and feedback, standardization with tools, team leadership, and DecSecOps for security issues. While DevOps has gained significant attention, it remains essential to understand practitioners’ perspectives. Our research has the potential to strengthen the concepts and ideas of critical success factors, broaden DevOps practices and perspectives for professionals, and enhance academic knowledge in this area.

DevOps is a set of software development and operation practices and a recent addition to a large family of different kinds of software process models. The model emerged out of the observation that information systems operations and developments should be closely integrated activities to ensure the success of any organization. Thus, DevOps methods are an additive tool for companies to improve overall performance in their software development processes and operations. This paper aims to identify the various critical success factors (CSFs) of DevOps projects that have been discussed in prior research. In addition, this study proposes a comprehensive framework for depicting how these CSFs impact or drive DevOps success. This study consists of a systematic literature review to collect the primary articles for the analysis. After searches in four major publication databases and snowballing, we selected 38 primary studies for the analysis. Nearly 100 different CSFs were identified, which were then categorized into Technical, Organizational, and Social & Cultural dimensions. Based on the results of the literature analysis, a comprehensive framework is proposed that depicts how the CSFs impact or drive DevOps success. This paper presents a DevOps framework with various CSFs based on prior literature. The proposed framework will provide collective knowledge of DevOps success factors, which will allow researchers and practitioners to enhance their understanding of CSFs and learn how to handle DevOps issues in organizations. In particular, the paper highlights a number of future research directions related to CSFs.