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In the present article, the authors tackle the problem of IT documentation, which plays an important role in information technology (IT) project management.

They provide a simple tool based on five complementary views, which should be detailed by the project team using a classic source code management platform.

The proposed tool is open source and may be reused by any IT team in various project contexts and heterogeneous development methods.

This research provides an operational framework, which facilitates IT project management and documentation. The framework is open source and may be easily downloaded by any other IT team.

This research analyses challenges faced by users at various levels in planning and designing participatory simulation models of cities. It aims to identify issues that hinder experts from maximising the effectiveness of the SUMO tool. Additionally, evaluating current methods highlights their strengths and weaknesses, facilitating the use of participatory simulation advantages to address these issues. Finally, the presented case studies illustrate the diversity of user groups and emphasise the need for further development of blueprints.

In this research, action research was used to assess and improve a step-by-step guideline. The guideline's conceptual design is based on stakeholder analysis results from those involved in developing urban logistics scenarios and feedback from potential users. A two-round process of application and refinement was conducted to evaluate and enhance the guideline's initial version.

The guidelines still demand an advanced skill level in simulation modelling, rendering them less effective for the intended audience. However, they have proven beneficial in a simulation course for students, emphasising the importance of developing accurate conceptual models and the need for careful implementation.

This paper introduces a step-by-step guideline designed to tackle challenges in modelling urban logistics scenarios using SUMO simulation software. The guideline's effectiveness was tested and enhanced through experiments involving diverse groups of students, varying in their experience with simulation modelling. This approach demonstrates the guideline's applicability and adaptability across different skill levels.

This paper aims to examine the key challenges experienced and lessons learned when organizations undergo large-scale agile transformations and seeks to answer the question of how incumbent firms achieve agility at scale.

Building on a case study of a multinational corporation seeking to scale up agility, the authors combined 36 semistructured interviews with secondary data from the organization to analyze its transformation since the early planning period.

The results show how incumbent firms develop and successfully integrate agility-enhancing capabilities to sense, seize and transform in times of digital transformation and rapid change. The findings highlight how agility can be established initially at the divisional level, namely with a key accelerator in the form of a center of competence, and later prepared to be scaled up across the organization. Moreover, the authors abstract and organize the findings according to the dynamic capabilities framework and offer propositions of how companies can achieve organizational agility by scaling up agility from a divisional to an organizational level.

Along with in-depth insights into agile transformations, this article provides practitioners with guidance for developing agility-enhancing capabilities within incumbent organizations and creating, scaling and managing agility across them.

Examining the case of a multinational corporation's exceptional, pioneering effort to scale agility, this article addresses the strategic importance of agility and explains how organizational agility can serve incumbent firms in industries characterized by uncertainty and intense competition.

The purpose of this study is to examine the role of artificial intelligence (AI) in transforming the healthcare sector, with a focus on how AI contributes to entrepreneurship and value creation. This study also aims to explore the potential of combining AI with other technologies, such as cloud computing, blockchain, IoMT, additive manufacturing and 5G, in the healthcare industry.

Exploratory qualitative methodology was chosen to analyze 22 case studies from the USA, EU, Asia and South America. The data source was public and specialized podcast platforms.

The findings show that combining technologies can create a competitive advantage for technology entrepreneurs and bring about transitions from simple consumer devices to actionable healthcare applications. The results of this research identified three main entrepreneurship areas: 1. Analytics, including staff reduction, patient prediction and decision support; 2. Security, including protection against cyberattacks and detection of atypical cases; 3. Performance optimization, which, in addition to reducing the time and costs of medical procedures, includes staff training, reducing capital costs and working with new markets.

This study demonstrates how AI can be used with other technologies to cocreate value in the healthcare industry. This study provides a conceptual framework, “AI facilitators – AI achievers,” based on the findings and offer several theoretical contributions to academic literature in technology entrepreneurship and technology management and industry recommendations for practical implication.

Capital structure is an important factor for the company because it will be directly related to the financial condition of the company. This study aims to determine the effect of asset structure, earning volatility, and financial flexibility on capital structure.

The population in this study was 52 companies in the consumer goods industry sector on the Indonesia stock exchange (IDX) and a sample of 39 companies obtained by purposive sampling method. The research method used in this study is multiple linear regression analysis using Eviews software.

The test results in the study show that asset structure and financial flexibility have a positive effect on capital structure, while earning volatility does not affect capital structure in companies in the consumer goods industry sector on the IDX.

The results of this research can contribute to the addition of knowledge in the field of accounting, especially regarding the capital structure. Company management can use the results of this research as a reference and consideration to find out the factors that affect the capital structure so that company management can still maintain the company's survival and improve company performance.

The results of this study can contribute to the addition of knowledge in the field of accounting, especially regarding capital structure. Company management can use the results of this research as a reference and consideration to determine the factors that affect the capital structure so that company management can still maintain the survival of the company and improve company performance.

This study only uses the variables of asset structure, financial flexibility and earning volatility as independent variables. Further research is recommended to consider the use of other variables that can affect capital structure and if using the same variable is expected to use research objects that have stable or increasing asset and income values, so that asset structure variables and profit volatility can show significant results and influences.

This study is one of the few studies that examines how the effect of asset structure, profit volatility and financial flexibility on capital structure in companies in the consumer goods industry sector on the IDX. Company management must pay attention to the composition of the capital structure as well as possible and make careful planning and the right decisions so as to produce a capital structure that can provide profits.

Machine learning (ML) analytical tools are increasingly being considered as an alternative quantitative methodology in management research. This paper proposes a new approach for uncovering the antecedents behind product and product–service innovation (PSI).

The ML approach is novel in the field of innovation antecedents at the country level. A sample of the Equatorian National Survey on Technology and Innovation, consisting of more than 6,000 firms, is used to rank the antecedents of innovation.

The analysis reveals that the antecedents of product and PSI are distinct, yet rooted in the principles of open innovation and competitive priorities.

The analysis is based on a sample of Equatorian firms with the objective of showing how ML techniques are suitable for testing the antecedents of innovation in any other context.

The novel ML approach, in contrast to traditional quantitative analysis of the topic, can consider the full set of antecedent interactions to each of the innovations analyzed.

This article aims to understand where industry is in terms of digitalizing their operations, what features of this transformation are essential for practitioners, and what barriers they are facing during their journey. In addition, the authors aim to provide recommendations for organization to start their digital transformation.

Through literature review, the authors summarize the emerging tools and technologies in operations and supply chains to inform the practitioners. Then, the authors use surveys conducted on 183 operations and supply chain professionals, and use statistical tools to examine the association between variables of the data set. The authors present real-life case studies to explain important steps of a digital transformation project.

The survey results indicate that real-time monitoring and data analytics are viewed as the most important and needed tools for organizations. High cost, lack of stakeholder buy-in and lack of successful business use cases are major barriers for companies when starting a digital transformation.

The authors provide recommendations for practitioners based on the survey responses, and outline that starting small, focusing on stakeholder buy-in and implementation of software are the three key steps for a successful transformation journey.

Main contributions of this article are to understand practitioner perspectives in digitalization and provide guidelines for organizations to follow when transforming their operations. This research closes the gap between academic research and practice by collaborating with operations and supply chain professionals.

This study investigates the implementation of a sustainable circular business model from an accounting perspective. Its goal is to understand if and how decision- makers use management accounting systems, and what changes are needed if these systems are to support the transition toward a circular economy.

Dialogic accounting theory frames the case study of six companies that built a value network to develop and implement an innovative packaging solution consistent with circular economy principles. Content analysis was utilised to investigate the accounting tools used.

The findings indicate that circular solutions generate new organisational configurations based on value networks. Interestingly, managers’ decision-making process largely bypassed the accounting function; they relied on informal accounting and life cycle analysis, which stimulated a multi-stakeholder dialogue in a life cycle perspective.

The research provides theoretical and practical insights into the capability of management accounting systems to support companies seeking circular solutions.

The authors offer implications for accounting practice, chief financial officers (CFOs) and accounting educators, suggesting that a dialogic approach may support value retention of resources, materials and products, as required by the circular economy.

The research contributes to the debate about the role of accounting in sustainability, specifically the need for connecting for resource efficiency at the corporate level with the rationalisation of resource use within planetary boundaries.

The study contributes to the limited research into the role of management accounting in a company’s transition to circular business models. Dialogic accounting theory frames exploration of how accounting may evolve to help businesses become accountable to all stakeholders, including the environment.

This paper discusses the effects of enabling conditions of project knowledge management in building volatile organizational memory. The theoretical rationale underlies a recursive relationship among enabling conditions of project knowledge management, organizational learning and memory.

This research employs a qualitative descriptive single case study approach to examine a mobile application development project undertaken by a major software company in Brazil. The analysis focuses on the project execution using an abductive analytical framework. The study data were collected through in-depth interviews and company documents.

Based on the research findings, the factors that facilitate behavior and strategy in managing project knowledge pose a challenge when it comes to fostering organizational learning. While both these factors play a role in organizational learning, the exchange of information from previous experience could be strengthened, and the feedback from the learning process could be improved. These shortcomings arise from emotional tensions that stem from power struggles within knowledge hierarchies.

Based on the research, it is recommended that project-structured organizations should prioritize an individual’s professional experience to promote organizational learning. Organizations with well-defined connections between their projects and strategies can better establish interconnections among knowledge creation, sharing and coding.

The primary contribution is to provide a comprehensive view that incorporates the conditions required to manage project knowledge, organizational learning and memory. The findings lead to four propositions that relate to volatile memory, intuitive knowledge, learning and knowledge encoding.

This paper explores how adaptive organizations, companies capable of continuously adapting their organizational model, dynamically solve the universal problems of organizing.

The authors applied grounded theory to data acquired from six interpretative case studies, collected in two rounds of interviews (15 in total), then completing and validating the study’s evidence through triangulation with several secondary data sources.

In adaptive organizations, polyarchies and intrapreneurial employees are essential to shape the division of labour, leading to high levels of autonomy and empowering individuals and teams, while reducing bureaucracy and hierarchy. In terms of the integration of effort, digital solutions are preferred to social proof in the provision of information, while the authors note that incentives are always geared towards developing strong higher-order dynamic capabilities.

This paper has some limitations that could be addressed in future research, including longitudinal studies to analyse the link between the universal problems of organizing and a company's dynamic capabilities.

Adaptive organizations go beyond tech firms in responding to the universal problems of organizing work by making specific use of digital technologies.

The paper studies how companies should organize themselves so that they continuously adapt to an ever-changing competitive environment.