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This study aims to explore how project-based firms, which generally organize most of their work around temporary projects in discontinuous and fragmented types of business contexts, proactively formulate and implement digital transformation strategies under institutional pressures in a predigital era.

An exploratory case study was conducted in a large-scale construction company in China using multiple data collection methods, including semistructured interviews, documentation collection and observation.

An integrated framework is developed to conceptualize three key dimensions of digital transformation strategies of project-based firms: strategic adaptation for organization-environment fit through balancing the internal efficiency needs with the external legitimacy pressures; proactive business transformation through comprehensively managing the roles of digital technologies in optimizing defined business processes and fostering new business models; and delicate organizational transformation to integrate temporary project-level operation processes with ongoing firm-level business processes.

This study represents an exploratory effort to empirically investigate how project-based firms strategically organize complex digital transformation imperatives in their discontinuous and fragmented business contexts. The findings contribute to deepened understandings of how complex organizational and environmental contexts can be comprehensively managed for systemic business and organizational transformations to leverage the value of emerging digital technologies for project-based organizations.

This study aims to establish a comprehensive framework for adopting mobile-based artificial intelligence (AI) services in Tanzanian manufacturing small and medium enterprises (SMEs).

The methodology involved conducting a literature review and using the combination of Mobile Services Acceptance Model and Innovation Diffusion Theory (IDT) as a theoretical foundation. This synthesis delves into the current knowledge on technology adoption, organizational behavior and innovation diffusion, creating a solid conceptual basis. Expert review was used for framework validation to ensure the framework's accuracy.

This study shows that the factors influencing the adoption of mobile-based AI services in Tanzanian manufacturing SMEs include perceived usefulness, perceived ease of use, context, personal initiatives and characteristics, trust, infrastructure, cost, mobility, power distance, compatibility, observability and trialability.

The framework provides valuable insights tailored to Tanzanian sociocultural and economic nuances. However, its generalizability is limited due to its specificity to Tanzanian manufacturing SMEs.

The framework outlined in this research provides SME leaders, policymakers and technology implementers with valuable guidance to make informed decisions during the adoption process.

This study introduces a novel lens for understanding technology adoption. This study's focus on the Tanzanian context and its nuanced examination of contributing factors add to its originality and practical significance.

Optimal application and commitment toward financial management practices enhance organization performance. This study aims to assess the influence of financial management practices on the organizational performance of small- and medium-scale enterprises.

Data were collected from 45 small-sized and 72 medium-sized firms. Data supported the hypothesized relationships. Construct reliability and validity were established through confirmatory factor analysis. The conceptual model and hypotheses were evaluated by using structural equation modeling.

The results indicate that working capital significantly influenced organizational performance. Capital budget management significantly influenced organizational performance. A non-significant influence of asset management on organizational performance was observed.

The generalizability of the findings will be constrained due to the research’s SMEs focus and cross-sectional data.

The study’s findings will serve as valuable pointers for stakeholders and decision-makers of SMEs in developing well-articulated and proactive financial management systems to ensure competitiveness, sustainability, viability, and financial competencies.

The study adds to the corpus of literature by evidencing empirically that financial management practices significantly influenced SMEs’ performance.

The objective of this paper is to increase understanding of social media in international business context. To this end, the authors make an attempt to integrate the existing, still somewhat limited views in a framework that advances the knowledge of scholars and decision-makers on this topic.

The authors conduct a conceptual study supported by use of a systematic literature review method.

This study shows marketing as a dominant area of discussion and reveals that many firm functions where social media plays a role have received relatively little attention. Furthermore, the study shows that the positive features of social media in international activity tend to be more widely acknowledged and better understood than the potentially problematic aspects.

The number of articles analyzed in this study was relatively small, resonating with the nature of an emerging research area. Research on social media has only taken off over the last years, and it is understandable that there is limited research that connects it specifically to phenomena of international business.

This study reminds managers to be cautious when using social media in international markets. The relationship between social media and international business exhibits dynamism and is dependent on a variety of factors. Social media does not come without costs, nor is easily transferred from one market to another. Efficient use of this media in the international context may increase the need of specific and qualified human resources, and it may necessitate having the whole process from R&D to delivery, and beyond, ready for adaptation.

It can be argued that we know too little about the relevant factors and relationships between social media and international business. The authors hope that this study revealing the scarcely studied aspects and suggesting a tentative framework for capturing the dynamics of social media and international business can guide subsequent research and accelerate its emergence.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.