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In times of open and distributed innovation, many innovation activities that are important for firms' products and services take place beyond the boundaries of the firm and thus beyond firms' direct control. A prime example for this phenomenon is open source software (OSS) development, where multiple actors contribute to a public good, which is also integrated into company-owned software products. Despite the importance of aligning community work on the public good with own in-house development efforts, firms have limited options to directly control the OSS project or the project's outcome. This research reflects on resource deployment control, a control mode in which firms assign own developers to work for an OSS project to influence the OSS project, and tests hypotheses on individual developer levels.

This research tests the effect of perceived resource deployment control on opinion leadership by analyzing employed Linux kernel developers.

The findings show that developers who perceive being assigned to an OSS project to enact control also exhibit opinion leadership. This research also investigates boundary conditions such as the OSS business model a firm operates and the reputation developers assign to the developers' employer.

This research is the first that is devoted to resource deployment control, and the research closes with a discussion of implications for control theory and the management of innovation beyond firm boundaries.

This research investigates how the value creation interests and activities of different stakeholder groups within one open source software (OSS) project influence the project's development over time.

The authors conducted a case study of OpenSimulator using textual and thematic analyses of the initial four years of OpenSimulator developer mailing list to identify each stakeholder group and guide our analysis of their interests and value creation activities over time.

The analysis revealed that while each stakeholder group was active within the OSS project's development, the different groups possessed complementary interests that enabled the project to evolve. In the formative period, entrepreneurs were interested in the software's strategic direction in the market, academics and SMEs in software functionality and large firms and hobbyists in software testing. Each group retained its primary interest in the maturing period with academics and SMEs separating into server- and client-side usability. The analysis shed light on how the different stakeholder groups overcame tensions amongst themselves and took specific actions to sustain the project.

The authors extend stakeholder theory by reconceptualizing the focal organization and its stakeholders for OSS projects. To date, OSS research has primarily focused on examining one project relative to its marketplace. Using stakeholder theory, we identified stakeholder groups within a single OSS project to demonstrate their distinct interests and how these interests influence their value creation activities over time. Collectively, these interests enable the project's long-term development.

The purpose of this study is to investigate the barriers that prevent workers in the software industry from experiencing flow in their work.

This study was conducted by using a qualitative critical incident technique-inspired questionnaire.

The findings suggest that workers in the software industry perceive that the most obvious obstacles to experiencing flow are related to work not presenting enough cognitive challenges and situational barriers related to the characteristics of the job (e.g. workdays having too many interruptions and distractions, timetables often being considered too tight for creative exploration and problem solving and having negative user experiences with development tools).

The findings provide insights into flow barriers, specifically barriers that prevent workers in the software industry from experiencing flow.

The purpose of this study is to examine the state of the literature on knowledge sharing in open source software (OSS) development communities by examining the existing research and identifying the knowledge gaps and opportunities that can inform areas for future research.

A systematic literature review was conducted of literature published between January 2011 and February 2023. A total of 24 papers were identified and reviewed.

The findings reveal that the literature on knowledge sharing in OSS development communities from developing countries are limited. Additionally, there exists a limited focus on the development of frameworks to support knowledge sharing in OSS communities. The transient nature of OSS development contributors’ results in knowledge loss; thus, knowledge retention needs further investigation.

This study only included papers whose titles, keywords or abstracts included the search keywords “knowledge sharing” and “Open Source Software”. While the keywords were carefully applied, when applying the search, it cannot be ruled that some relevant studies might have been missed. The study was also limited to conferences and journal papers published in English. Despite the limitations, the study provides a systematic review of knowledge sharing in OSS communities and presents findings that can be useful to researchers and practitioners interested in this area.

The study provides a systematic literature review of published papers and identifies themes and future research areas on knowledge sharing in OSS communities. Additionally, this review offers insights into future research avenues for theory, content and context on knowledge sharing in OSS development communities.

The purpose of the paper is to propose a semantic model for describing open source software (OSS) in a machine–human understandable format. The model is extracted to support source code reusing and revising as the two primary targets of OSS through a systematic review of related documents.

Conducting a systematic review, all the software reusing criteria are identified and introduced to the web of data by an ontology for OSS (O4OSS). The software semantic model introduced in this paper explores OSS through triple expressions in which the O4OSS properties are predicates.

This model improves the quality of web data by describing software in a structured machine–human readable profile, which is linked to the related data that was previously published on the web. Evaluating the OSS semantic model is accomplished through comparing it with previous approaches, comparing the software structured metadata with profile index of software in some well-known repositories, calculating the software retrieval rank and surveying domain experts.

Considering context-specific information and authority levels, the proposed software model would be applicable to any open and close software. Using this model to publish software provides an infrastructure of connected meaningful data and helps developers overcome some specific challenges. By navigating software data, many questions which can be answered only through reading multiple documents can be automatically responded on the web of data.

Digital platforms increase their function and scope by leveraging boundary resources and complementary add-on products from third-party developers to interact with external entities and producers. Application Programming Interfaces (APIs) are essential boundary resources developers use to connect applications, systems and platforms. This notwithstanding, previous API studies tend to focus more on the technical dimensions, with little on the social and cultural contexts underpinning API innovations. This study relies on the new (neo) institutional theory (focusing on regulative, normative and cultural-cognitive pillars) as an analytical lens to understand the institutional forces that affect API integration among digital firms.

The study adopts a qualitative case study methodology and relies on phone calls and a semi-structured in-depth interview approach of a Ghanaian digital music platform to uncover the institutional forces affecting API integration.

The findings reveal that regulative institutions such as excessive tax regimes mostly constrained API development and integration initiatives. However, other regulative institutions like the government digitalization agenda enabled API integration. Normative institutions, such as the growing use of e-payment options, enabled API integration in digital music platforms. Cultural-cognitive institutions like employee ego constrained the API integration process in music digital platforms.

This study primarily contributes to deepening understanding of the relevant literature by exploring the institutional forces that affect API integration among digital firms in a developing economy. The study also uncovered a new form of an institution known as motivational institution as an enabler for API development and integration in digital music platforms.

This paper aims to examine the process for estimation of efforts for software development and suggests a framework for estimating software development costs and ensuring quality of code in e-Government projects from the Indian state of Andhra Pradesh. With no established processes for estimation of efforts, the Government relied on open bids from the market to develop these e-Government applications.

The paper adopts an exploratory case study approach to analyze the e-Government applications in Andhra Pradesh. Using data from the information technology department of the Government of Andhra Pradesh, the paper evolves a framework to compute costs of software development, based on the software development life cycle.

The framework helps in arriving at a hurdle price before the tender process. The study has shown that an e-Government application in AP state would cost Rs. 224,000, or US$2,969.25, for a simple application, and Rs. 33,60,000, or US$44,538.71, for a complex application over a five-year period, depending on the complexity and size of the application. This information would be useful to the Government decision-makers for expanding e-Government.

Further research may assess the utility of this framework for e-Government support activities like automation of data centers, video conferencing facilities and ushering in financial technologies for encouraging cashless payments.

The paper provides information that could be of value at a national level (for India) and at the same time providing a guide for other countries that would like to adopt this framework.

The applications of Artificial Intelligence (AI) in various areas of professional and knowledge work are growing. Emotions play an important role in how users incorporate a technology into their work practices. The current study draws on work in the areas of AI-powered technologies adaptation, emotions, and the future of work, to investigate how knowledge workers feel about adopting AI in their work.

We gathered 107,111 tweets about the new AI programmer, GitHub Copilot, launched by GitHub and analysed the data in three stages. First, after cleaning and filtering the data, we applied the topic modelling method to analyse 16,130 tweets posted by 10,301 software programmers to identify the emotions they expressed. Then, we analysed the outcome topics qualitatively to understand the stimulus characteristics driving those emotions. Finally, we analysed a sample of tweets to explore how emotional responses changed over time.

We found six categories of emotions among software programmers: challenge, achievement, loss, deterrence, scepticism, and apathy. In addition, we found these emotions were driven by four stimulus characteristics: AI development, AI functionality, identity work, and AI engagement. We also examined the change in emotions over time. The results indicate that negative emotions changed to more positive emotions once software programmers redirected their attention to the AI programmer's capabilities and functionalities, and related that to their identity work.

Overall, as organisations start adopting AI-powered technologies in their software development practices, our research offers practical guidance to managers by identifying factors that can change negative emotions to positive emotions.

Our study makes a timely contribution to the discussions on AI and the future of work through the lens of emotions. In contrast to nascent discussions on the role of AI in high-skilled jobs that show knowledge workers' general ambivalence towards AI, we find knowledge workers show more positive emotions over time and as they engage more with AI. In addition, this study unveils the role of professional identity in leading to more positive emotions towards AI, as knowledge workers view such technology as a means of expanding their identity rather than as a threat to it.

Innovation is a process that enables organizations to sustain and prosper in a competitive business environment. This study aims to understand the key drivers of innovation within organizations from the lens of employees.

This study uses a grounded theory approach based on semi-structured in-depth interviews of 20 professionals working in information technology (IT) firms. Judgmental sampling was adopted to select the respondents. Open coding, inductive analysis was conducted on the interview transcripts to generate relevant themes.

Emerging themes indicate that innovation within organizations can be triggered as a response to client requirements or the employees’ inherent urge to innovate. Certain factors such as user engagement, formal organizational processes and practices, informal collaborative practices, the role played by experts and leaders and upskilling were seen to enable innovative outcomes within organizations.

Findings from this study will allow leaders to activate the identified drivers by designing suitable organizational processes and strategies to nurture a successful innovation culture within their teams.

This grounded theory-based study looks at drivers of innovation within IT organizations from the perspective of employees.

This paper aims to examine the role of Open Artificial Intelligence application (ChatGPT) to identify challenges faced by developers working on React.js libraries.

Scopus and Google Scholar databases were searched for the literature. In addition, ChatGPT application was accessed to extract contents regarding its potential role in identifying challenges and their solutions for developers.

This paper found that ChatGPT has potential in identifying challenges, faced by learners and developers. ChatGPT enables developers to navigate the projects’ libraries and overcome steep learning curve issue. ChatGPT excels in helping the developers by presenting a range of valuable strengths. These include offering tutorials and document support, providing comprehensive programming challenges solutions, assisting with the configuration and adding in debugging process of React.js application.

To the best of the authors’ knowledge, this is one of the first articles presenting the potential role of ChatGPT in identifying and offering solutions to the challenges of learners and programmers about React.js.