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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.

The objective is to develop an empirical model estimating the relationship and interaction amongst the factors affecting and enhancing green finance (GF) in developing economies like India.

Around nine growth-accelerating enablers of green financing were found through literature and unstructured interviews and analysed using the total interpretive structural modelling (TISM) method. The hierarchical link between each factor is established using TISM, and further to evaluate the driver-dependent relationship the Matriced’ Impacts Croises Appliquee Aaun Classement (MICMAC) approach is utilised.

The findings demonstrate an interrelationship between growth-accelerating factors, where the political environment and information and communication technology (ICT), have minimal dependency but a strong driving force. Political environment and ICT are found as strategic-level factors lying at the bottom of the model driving towards the dependent variables. The government should focus on enacting effective policies such as the green credit guarantee scheme and carbon credit and establishing a regulatory framework to enhance green financing.

This study examines the literature to generalise the findings and focus on the primary motivators for developing green financing. To increase green financial activity, practitioners must concentrate on aspects with significant driving forces. Furthermore, it makes organisations more profitable, efficient and competitive and promotes long-term growth.

The study is the first in the literature which identifies the growth-accelerating factors of green financing using the TISM and MICMAC-based hierarchical models.

Blockchain has the potential to facilitate a paradigm shift in the construction industry toward effectiveness, transparency and collaboration. However, there is currently a paucity of empirical evidence from real-world construction projects. This study aims to systematically review blockchain adoption barriers, investigate critical ones and propose corresponding solutions.

An integrated method was adopted in this research based on the technology–organization–environment (TOE) theory and fuzzy decision-making trial and evaluation laboratory (DEMATEL) approach. Blockchain adoption barriers were first presented using the TOE framework. Then, key barriers were identified based on the importance and causality analysis in the fuzzy DEMATEL. Several suggestions were proposed to facilitate blockchain diffusion from the standpoints of the government, the industry and construction organizations.

The results highlighted seven key barriers. Specifically, the construction industry is more concerned with environmental barriers, such as policy uncertainties (E2) and technology maturity (E3), while most technical barriers are causal factors, such as “interoperability (T4)” and “smart contracts' security (T2)”.

This study contributes to a better understanding of the problem associated with blockchain implementation and provides policymakers with recommendations.

Identified TOE barriers lay the groundwork for theoretical observations to comprehend the blockchain adoption problem. This research also applied the fuzzy method to blockchain adoption barrier analysis, which can reduce the uncertainty and subjectivity in expert evaluations with a small sample.

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.

Documentation plays a key role in navigating the costs of construction projects. Traditional document management systems (TDMS) used in developing countries, however, hinder the achievement of expected cost targets. Although the electronic document management system (EDMS) has been implemented to improve documentation, the Sri Lankan construction industry has failed to effectively adapt to it. Hence, this study aims to provide strategies for the effective application of EDMS to the cost management of Sri Lankan mega construction projects.

This study uses a qualitative approach followed by 12 semi-structured expert interviews. Quantity surveying experts were selected through judgemental sampling. Manual content analysis was used to analyse the data.

The EDMS is more suitable for megaprojects than traditional methods of documentation in terms of functionality, neutrality, interoperability, space, reversibility and delivery speed. However, there are contradictory views about cost and security. Furthermore, five transitional challenges of EDMS have been identified under the three key themes of cost, stakeholder perception and technical difficulties. Four reasons were also identified as causing these five challenges. Seven suggestions were made to deal with these transitional challenges and three key feasible solutions for the Sri Lankan construction industry regarding the EDMS were identified. Development of Sri Lankan software with low initial cost was highlighted as the most feasible solution.

This is a novel study to investigate the applicability of EDMS to cost management mechanisms of megaprojects in Sri Lanka. The findings reveal transitional challenges and appropriate feasible solutions for EDMS adaptation. This can be applied to the cost management of megaprojects in other developing countries as well.

This paper proposes strategies for adopting Industry 4.0 in achieving sustainable manufacturing, by overcoming barriers in the Sri Lankan manufacturing sector.

A conceptual model of sustainable manufacturing and Industry 4.0 was proposed based on a comprehensive literature review and validated through experts' inputs. The model was illustrated using three case studies to assess the relationships between sustainable manufacturing and Industry 4.0 in the Sri Lankan manufacturing context. Furthermore, possible strategies were proposed to overcome current barriers identified from case studies.

The case studies showcase that there is a considerable gap in Industry 4.0-enabled sustainable manufacturing in the Sri Lankan manufacturing sector due to several barriers. Thus, experts' knowledge-based strategies to overcome those barriers are proposed.

The conceptual model provides a holistic view of maturity levels of sustainable manufacturing measures directly connected with Industry 4.0 technologies. The study was limited to investigating the application of Industry 4.0 for sustainable manufacturing in leading apparel manufacturing organisations in Sri Lanka.

The conceptual model can be used as a framework to guide practitioners in implementing Industry 4.0-enabled sustainable manufacturing. The proposed strategies in addressing barriers to Industry 4.0 adoption towards sustainable manufacturing can be directly applied to achieving better sustainable manufacturing performance.

This study is an informative guide to encourage the Sri Lankan manufacturing industry to adopt Industry 4.0 technologies in achieving sustainable manufacturing, using the knowledge of relationships between Industry 4.0 and three dimensions of sustainable manufacturing, possible barriers and strategies.

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.

Effectuation, which articulates the process of entrepreneurial action based on nonpredictive control logic, is receiving extensive scholarly attention. What drives the effectual entrepreneurship is featured with high complexity. However, existing studies ignored the complex driving forces underlying entrepreneurial decision-making. Building on a configurational perspective, the purpose of this study was to examine the combinative effects of environmental uncertainty and entrepreneurs’ means on effectual entrepreneurship.

Drawing on 54 entrepreneurs who are launching new ventures in China, this study adopts a fuzzy-set Qualitative Comparative Analysis (fsQCA) to investigate two sets of antecedent conditions and how they form different combinations for a highly effectual entrepreneurship.

Our findings disclose four highly effectual entrepreneurship paths involving novice–specialist effectual entrepreneurship in a highly uncertain environment, socialite–specialist effectual entrepreneurship in a highly uncertain environment, pure-specialist effectual entrepreneurship and resourceful effectual entrepreneurship, and one path of barefoot noneffectual entrepreneurship in a highly uncertain environment, which reveals the complex nature of environmental uncertainty and entrepreneurs’ means in driving entrepreneurs to adopt effectuation.

Our study makes the following contributions. First, by taking a configurational perspective, we are able to obtain an elaborate view of the combined effects of environmental uncertainty and entrepreneurs’ means on effectual entrepreneurship. Second, we expand prior thinking on the relationship between environmental uncertainty and effectuation. Third, our study offers a more delicate understanding of entrepreneurs’ means in driving effectuation by splitting means into three separate factors.