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This study aims to analyse the influence of digitalisation on the management control function of small and medium-sized enterprises (SMEs). In particular, it aims to illuminate how digitalisation influences management control elements, organisation and roles/competencies and to identify obstacles to digitalisation of management control in SMEs and measures taken to overcome them.

The study is based on guideline-supported expert interviews conducted with 14 financial managers from SMEs in Germany, Austria and Switzerland.

This study reveals the influence of digitalisation on management control elements, organisation, and roles/competencies. The automation and standardisation of management control processes result in new elements for management control, such as strategic support for management. In addition, the increased availability and transparency of data enable the use of instruments within a company that allow for quick analyses of the company's development. Digitalisation leads to the integration of management control into the corporate network and, thus, a change in the organisation of management control. It also triggers the expansion of management control competencies, especially IT competencies. A shortage of internal digitalisation resources, unclear corporate roadmaps, and a lack of managerial experience loom as central challenges for digitalising the management control function. Measures derived from the interviews can help SMEs overcome the obstacles to the digitalisation of management control.

This research is the first interview-based study of the impact of digitalisation on management control in SMEs, potential obstacles to that digitalisation, and measures to overcome those obstacles. Thus, it contributes to the emerging debate on factors that may explain why SMEs lag in terms of the digitalisation of their internal processes.

E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.

Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.

Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.

TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.

The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.

Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.

This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior.

Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors.

The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory.

The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds.

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 aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image. The authors used three feature extraction methods: handcrafted features, convolutional features and autoencoder features. Subsequently, these features were mapped to contact locations through a contact location regression network. Finally, the network performance was evaluated using spherical fittings of three different radii to further determine the optimal feature extraction method.

This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image.

This research indicates that data collected by probes can be used for contact localization. Introducing a batch normalization layer after the feature extraction stage significantly enhances the model’s generalization performance. Through qualitative and quantitative analyses, the authors conclude that convolutional methods can more accurately estimate contact locations.

The paper provides both qualitative and quantitative analyses of the performance of three contact localization methods across different datasets. To address the challenge of obtaining accurate contact locations in quantitative analysis, an indirect measurement metric is proposed.

This study aims to explore the potential of Islamic climate finance in Indonesia and to map Islamic climate finance based on Islamic finance instruments, both commercial and social.

The analysis was conducted in Jakarta, Indonesia, between October 2022 and June 2023. This study adopted a qualitative interpretive approach in two phases. The first phase was desk-based research which focused on document analysis such as official documents, scientific publications, non-governmental organization publications and company reports in Indonesia. This analysis was conducted to identify significant milestones in developing green and eco-friendly finance that used Islamic financial instruments in Indonesia. The second phase consisted of interviews with essential Islamic climate finance project actors, such as green sukuk publishers, zakat and waqf collection agencies, stakeholders, capital market regulators, Shariah supervisory boards and Islamic finance experts.

The main finding of this study is that the development of Islamic green finance in Indonesia can occur through various channels, including greening Islamic capital markets, greening Islamic social finance, Islamic green finance and developing green banking services for the unbanked to support financial inclusion. Green sukuk, or Islamic bonds, are key financial instruments in Islamic green finance. They are used to fund projects in areas such as clean energy, mass transit, water conservation, forestry and low-carbon technology. These green financing initiatives also include socially responsible investments that are designed to improve the lives of people and communities.

First, the availability of data on Islamic green finance practices in Indonesia may be limited, making it difficult to obtain a comprehensive understanding of the current landscape. Second, cultural and religious factors may play a role in the adoption and implementation of Islamic green finance, and these factors may vary across different regions in Indonesia.

The exploration and clustering of Islamic climate finance based on Islamic financial instruments in Indonesia can lead to the development of more sustainable and environmentally friendly practices in the financial industry.

This study serves as a pioneering effort to explore the potential and clustering of Islamic climate finance based on Islamic financial instruments in Indonesia.

This article investigates the practical implementation of the ecosystem approach in different branches of public management within an urban context. It explores how ecosystem thinking is introduced, disseminated and applied in a local government organization.

We utilize a qualitative case study methodology, relying on official documents and expert interviews. Our study focuses on the city of Espoo, Finland, which has actively embraced ecosystem thinking as a fundamental framework for its organizational development for almost a decade.

The case of Espoo highlights elements that have not been commonly attributed to the ecosystem approach in the public sector. These elements include (1) the significance of complementary services, (2) the existence of both collaborative and competitive relationships among actors in public service ecosystems and (3) the utilization of digital platforms for resource orchestration. Our study also emphasizes the need for an incremental adoption of ecosystem thinking in organizational contexts to enable its successful implementation.

The study provides valuable insights into the introduction and dissemination of ecosystem thinking in public management. It also further develops previously developed hypotheses regarding public service ecosystems.

The combination of an Engineered Cementitious Composite (ECC) layer and steel plate to reinforce RC beams (ESRB) is a new strengthening method. The ESRB was proposed based on the steel plate at the bottom of RC beams, aiming to solve the problem of over-reinforced RC beams and improve the bearing capacity of RC beams without affecting their ductility.

In this paper, the finite element model of ESRB was established by ABAQUS. The results were compared with the experimental results of ESRB in previous studies and the reliability of the finite element model was verified. On this basis, parameters such as the width of the steel plate, thickness of the ECC layer, damage degree of the original beam and cross-sectional area of longitudinal tensile rebar were analyzed by the verified finite element model. Based on the load–deflection curve of ESRB, ESRB was discussed in terms of ultimate bearing capacity and ductility.

The results demonstrate that when the width of the steel plate increases, the ultimate load of ESRB increases to 133.22 kN by 11.58% as well as the ductility index increases to 2.39. With the increase of the damage degree of the original beam, the ultimate load of ESRB decreases by 23.7%–91.09 kN and the ductility index decreases to 1.90. With the enhancement of the cross-sectional area of longitudinal tensile rebar, the ultimate bearing capacity of ESRB increases to 126.75 kN by 6.2% and the ductility index elevates to 2.30. Finally, a calculation model for predicting the flexural capacity of ESRB is proposed. The calculated results of the model are in line with the experimental results.

Based on the comparative analysis of the test results and numerical simulation results of 11 test beams, this investigation verified the accuracy and reliability of the finite element simulation from the aspects of load–deflection curve, characteristic load and failure mode. Furthermore, based on load–deflection curve, the effects of steel plate width, ECC layer thickness, damage degree of the original beam and cross-sectional area of longitudinal tensile rebar on the ultimate bearing capacity and ductility of ESRB were discussed. Finally, a simplified method was put forward to further verify the effectiveness of ESRB through analytical calculation.

Research highlights that residential care experienced children and young people in Scotland have poorer educational outcomes than their peers within the wider population. Despite this, poor educational attainment is not inevitable, and further research is needed to increase the understanding of long-term trajectories. This paper aims to address a gap in contemporary literature that is of benefit to practitioners, academics and policymakers. Despite experiencing adversity, attachment, separation and loss, school attainment data on leaving care only reflects part of the educational journey.

Using a mixed methodology and social constructionist theoretical framework, a practitioner-led PhD study gathered data from questionnaires and qualitative information from 13 semi-structured interviews with young people who had experienced residential care in Scotland. Recruitment was through a gatekeeper within a national third-sector organisation. The educational trajectories for young people with experience of residential care in Scotland are complex. A lived experience perspective from a PhD study illustrates that statistical data only captures part of the journey and the author needs to reconsider how success is measured.

Of the 13 participants in the study, 12 achieved success educationally, although for the majority of those interviewed, attainment continued after leaving compulsory education. Barriers to greater success included placement uncertainty and movement, stigma, low expectations, pressure to not become a statistic, procedural obstacles and inconsistency or poor relationships.

Supportive relationships and stable placements can create circumstances conducive to effective learning, but evidence reflects that support is necessary throughout the life course if children, young people and adults with care experience are to reach their full academic potential.

Research into the educational outcomes for those with experience of residential care in Scotland is limited. This paper, from a PhD, provides lived experience accounts from a practitioner-led study.

Digital transformation is crucial for achieving high-quality development in the construction industry. Assessing the industry's digital maturity is an urgent necessity. The Digital Transformation Maturity Model is a potential tool to systematically evaluate the digital maturity levels of various industries. However, most existing models predominantly focus on sectors such as the Internet and manufacturing, leaving the construction industry comparatively underrepresented. This study aims to address this gap by developing a maturity model tailored specifically for digital transformation within the construction industry.

This study leverages the Capability Maturity Theory and integrates the unique characteristics of the construction industry to construct a comprehensive maturity model for digital transformation. The model comprises five critical dimensions: industry environment, strategy and organization, digital infrastructure, business process and management digitization, and digital performance. These dimensions encompass a total of 25 assessment indexes. To validate the model's feasibility and effectiveness, a digital transformation maturity assessment was conducted within China's construction industry.

The results of the maturity assessment within the Chinese construction industry reveal that it currently operates at the third level of digital maturity (defined level). The industry's maturity score stands at 2.329 out of 5. This outcome indicates that the developed model is accurate and reliable in assessing the level of digital transformation maturity within the construction industry.

This paper contributes both practical and theoretical insights to the field of digital transformation within the construction industry. By creating a tailored maturity model, it addresses a significant gap in existing research and offers a valuable tool for assessing and advancing digital maturity levels within this industry.