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Technology-enabled business-to-business (B2B) services contribute the largest share to GDP growth and are fundamental for an economy’s value creation. This article aims to identify key service- and digital technology-driven B2B innovation modes and proposes a research agenda for further exploration.

This conceptual paper adopts a techno-demarcation view on service innovation, encompassing three core dimensions: service offering (the service product, or the “what”), service process (the “how”) and service ecosystem (the “who/for whom”). It delineates the implications of three digital technologies – the internet-of-things (IoT), intelligent automation (IA) and digital platforms – for service innovation across these core dimensions in B2B markets.

Digital technology has immense potential ramifications for value creation by reshaping all three core dimensions of service innovation. Specifically, IoT can transform physical resources into reconfigurable service products, IA can augment and automate a rapidly expanding array of service processes, while digital platforms provide the technical and organizational infrastructure for the integration of resources and stakeholders within service ecosystems.

This study suggests an agenda with six themes for further research, each linked to one or more of the three service innovation dimensions. They are (1) new recurring revenue models, (2) service innovation in the metaverse, (3) scaling up service innovations, (4) ecosystem innovations, (5) power dependency and lock-in effects and (6) security and responsibility in digital domains.

The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.

Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.

Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.

The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.

This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.

This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.

The aim of this study is to empirically explore and analyze the concrete tasks of output measurement and the inherent challenges related to these tasks in a traditional and autonomous professional public work setting – the judicial system.

The analysis of the tasks is based on a categorization of general performance measurement motives (control-motivate-learn) and main stakeholder levels (society-organization-professionals). The analysis is exploratory and conducted as an empirical content analysis on materials and reports produced in two performance improvement projects conducted in European justice organizations.

The identified main tasks in the different categories are related to managing resources, controlling performance deviations, and encouraging improvement and development of performance. Based on the results, key improvement areas connected to output measurement in professional public organizations are connected to the improvement of objectivity and fairness in budgeting and work allocation practices, improvement of output measures' versatility and informativeness to highlight motivational and learning purposes, improvement of professional self-management in setting output targets and producing outputs, as well as improvement of organizational learning from the output measurement.

The paper presents empirically founded practical examples of challenges and improvement opportunities related to the tasks of output measurement in professional public organization.

This paper fulfils an identified need to study how general performance management motives realize as concrete tasks of output measurement in justice organizations.

By adopting the “hard” and “soft” project management (PM) approaches from the PM-literature, this paper aims to problematize the expected role of client organizations in driving innovation in the transport infrastructure sector.

Addressing a large public client in Sweden, a case study design was initially applied to provide in-depth insights and perspectives of client project managers’ views and experiences of managing projects expected to drive innovation. In this paper, the concepts of “hard” and “soft” are used to discuss empirical findings on challenges associated with adopting a PM-approach for driving innovation in projects. The empirical material consists of interview data, complemented with observations and archival data.

Findings reveal challenges associated with combining hard and soft approaches, frequently demonstrating difficulties in balancing short-term project expectations with the promotion of innovation. In line with the literature, project managers note that there is a need for soft approaches to promote development and drive innovation. Yet, findings reflect a situation in which operational success criteria predominate, whereas soft approaches are not sufficiently used to create the grounds required for fostering innovation.

Insights are provided into how PM-approaches may impact construction innovation in the infrastructure sector, demonstrating a need for further research on the challenges and implications of applying and combining hard and soft PM-approaches.

This study aims to investigate the relationship between corporate governance (CG) and financial performance in the case of publicly listed companies in Vietnam for the period from 2019 to 2021. The topic is crucial in understanding how effective governance practices can influence the financial outcomes of companies. The study sheds light on the link between CG practice and firm financial performance. It also provides insights for policymakers and practitioners to improve CG practices.

Due to the potential dynamic endogeneity in CG research, this study uses the generalized system methods of moments to effectively address the endogeneity problem. Financial performance is measured by Tobin’s Q, return on equity (ROE) and return on assets (ROA). Based on organization for economic cooperation and development (OECD) standards, these indices were calculated to assess the influence of CG practices on corporate financial performance, namely, for accounting information (ROA and ROE) and market performance (Tobin’s Q and service à resglement différé (SRD) – stock price volatility) for the period 2019–2021. In addition, the study examines the relationship between changes in the CG index and changes in financial performance.

The study’s main objective is to determine the relationship between CG performance scores and financial performance. The study found a positive relationship between transparency disclosure and financial performance and a positive correlation between CG and company size. The COVID-19 pandemic caused a decrease in transparency and information index scores in 2021 compared to 2019 and 2020 due to delayed General Meetings of Shareholders. The study failed to find a relationship between shareholder rights index (“cg_rosh”) and board responsibility (“cg_reob”) and financial performance, concerning which the findings of this study differ from those of previous studies. Reasons are put forward for these anomalies.

Policymakers need to develop a set of criteria for assessing CG practices. They also need to promulgate specific regulations for mandatory and voluntary information disclosure and designate a competent authority to certify the transparency of company information. The study also suggests that companies should develop CG regulations and focus on regulations relating to the business culture or ethics, as well as implementing a system to ensure equal treatment among shareholders. The study found that good CG practices can positively contribute to a company’s financial performance, which is crucial for investors to evaluate the quality of CG practices for each listed company so that investment risks can be limited.

For policymakers and participants of financial markets, predictions of trading volumes of financial indices are important issues. This study aims to address such a prediction problem based on the CSI300 nearby futures by using high-frequency data recorded each minute from the launch date of the futures to roughly two years after constituent stocks of the futures all becoming shortable, a time period witnessing significantly increased trading activities.

In order to answer questions as follows, this study adopts the neural network for modeling the irregular trading volume series of the CSI300 nearby futures: are the research able to utilize the lags of the trading volume series to make predictions; if this is the case, how far can the predictions go and how accurate can the predictions be; can this research use predictive information from trading volumes of the CSI300 spot and first distant futures for improving prediction accuracy and what is the corresponding magnitude; how sophisticated is the model; and how robust are its predictions?

The results of this study show that a simple neural network model could be constructed with 10 hidden neurons to robustly predict the trading volume of the CSI300 nearby futures using 1–20 min ahead trading volume data. The model leads to the root mean square error of about 955 contracts. Utilizing additional predictive information from trading volumes of the CSI300 spot and first distant futures could further benefit prediction accuracy and the magnitude of improvements is about 1–2%. This benefit is particularly significant when the trading volume of the CSI300 nearby futures is close to be zero. Another benefit, at the cost of the model becoming slightly more sophisticated with more hidden neurons, is that predictions could be generated through 1–30 min ahead trading volume data.

The results of this study could be used for multiple purposes, including designing financial index trading systems and platforms, monitoring systematic financial risks and building financial index price forecasting.

In developing countries, how risk management technologies influence management accounting and control (MAC) practices is under-researched. By drawing on insights from institutional studies, this study aims to examine the multiple institutional pressures surrounding an entity and influencing its risk-based management control (RBC) system – that is, how RBC appears in an emerging market attributed to institutional multiplicity.

The authors used qualitative case study research methods to collect empirical evidence from a privately owned Egyptian insurance company.

The authors observed that in the transformation to risk-based controls, especially in socio-political settings such as Egypt, changes in MAC systems were consistent with the shifts in the institutional context. Along with changes in the institutional environment, the case company sought to configure its MAC system to be more risk-based to achieve its strategic goals effectively and maintain its sustainability.

This research provides a fuller view of risk-based management controls based on the social, professional and political perspectives central to the examined institutional environment. Moreover, unlike early studies that reported resistance to RBC, this case reveals the institutional dynamics contributing to the successful implementation of RBC in an emerging market.

This paper aims to identify how a public client’s use of control systems (process, output and social control) affect innovation possibilities in construction projects.

Semi-structured interviews about six infrastructure projects were conducted to identify respondents’ views on innovation possibilities. These possibilities were then analyzed from an organizational control perspective within principal–agent relationships between the Swedish Transport Administration (STA) and their contractors.

How the client uses control systems affects innovation possibilities. Relying on process control could negatively affect innovation opportunities, whereas output control could have a positive influence. In addition, social control seems to have a weak effect, as the STA appears not to use social control to facilitate joint innovation. Public clients must comply with the Public Procurement Act and, therefore, retain the requirements specified in the tendering documents. Much of the steering of the execution is connected to the ex ante phase (before signing the contract), which affects innovation possibilities in the design and execution phases for the contractor.

This study was conducted with only one client, thus limiting its generalizability. However, the findings provide an important stepping stone to further investigation into balancing control systems and creating innovation possibilities in a principal–agent relationship.

Although public procurement has increasingly been emphasized as a major potential source of innovation, studying how a public client’s use of organizational control systems affects innovation possibilities in the construction sector has received scant attention.

Stakeholder engagement in construction projects is an ingredient that contributes to project optimal performance. Many developing countries have a paucity of literature about stakeholders' engagement in construction projects. Therefore, the study investigated South Africa's shareholders' engagement in construction projects and recommended possible measures to mitigate potential limitations.

The researchers collated data from South African experts in stakeholder engagement via a phenomenology type of qualitative research design. They explored the “perceived hindrances” facing stakeholders' engagement in construction projects and proffer measures to mitigate them. The study analysed collected data via thematic analysis and achieved saturation. Three themes emerged from the analysed data.

Findings show that efficient stakeholder engagement will enhance team collaboration and integrated construction project delivery. Results identified the perceived limitations facing stakeholders' engagement in South Africa's construction projects and categorised them into individual perceived hindrances, organisational perceived hindrances and government-related perceived hindrances. Also, findings proffer measures to mitigate perceived hindrances via policies and programmes within the sector.

Besides enhancing policymakers and other stakeholders in South Africa's construction industry to understand the benefits of stakeholder engagement better, the study may stir up the construction sector's stakeholders to embrace enhanced and effective stakeholders' management.

This study contributes to construction project practice that involves stakeholders, as it reveals the underlying causes of perceived hindrances facing stakeholders' engagement in construction projects. Also, it proffers feasible solutions to mitigate these hindrances and enhance stakeholders' engagement within South Africa's construction projects.