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This study aims to examine the joint effect of accounting background and cross-membership of Islamic Supervisory Board (ISB) members on bank investment efficiency.

This study uses data collected from 36 Islamic banks across 15 countries globally, spanning the period from 2012 to 2021. This research uses an ordinary least squares regression and a comprehensive set of endogeneity and robustness tests.

The findings show a negative relationship between the accounting background of ISB members and investment efficiency. However, when ISB members with accounting backgrounds also have ISB cross-memberships, the banks exhibit high investment efficiency. These results suggest that ISB cross-membership plays a crucial role in facilitating Islamic banks’ access to timely information on investment opportunities. This enables ISB members with accounting expertise to thoroughly assess the benefits and risks associated with their investment prospects. These findings imply that ISB members with accounting backgrounds and cross-memberships have greater motivation and thoughtful considerations for making better investment decisions. Consequently, Islamic banks are better positioned to undertake high profitable investment projects, which enhance their investment efficiency.

The current study holds immense value for Islamic bank management in their selection of ISB members who possess an accounting background and cross-membership.

This study delves into a comprehensive investigation of the proficiency, underlying principles and unique characteristics exhibited by ISB members with an accounting background. Moreover, this study acknowledges the burgeoning global prominence of Islamic banks.

Competition in the banking sector is more complex than in the past, and survival has become more difficult than before. The purpose of this paper is to propose a grey methodology for evaluating, clustering and ranking the performance of bank branches with imprecise and uncertain data in order to determine the relative status of each branch.

In this study, the two-stage data envelopment analysis model with grey data is applied to assess the efficiency of bank branches in terms of operations. The result of grey two-stage data envelopment analysis model is a grey number as efficiency value of each branch. In the following, the branches are classified into three grey categories of performance by grey clustering method, and the complete grey ranking of branches are performed using “minimax regret-based approach” and “whitening value rating”.

The results show that after grey clustering of 22 branches based on grey efficiency value obtained from the grey two-stage DEA model, 6 branches are assigned to “excellent” class, 4 branches to “good” class and 12 branches to “poor” class. Moreover, the results of MRA and whitening value rating models are integrated, and a complete ranking of 22 branches are presented.

Grey clustering of branches based on grey efficiency value can facilitate planning and policy-making for branches so that there is no need to plan separately for each branch. The grey ranking helps the branches find their current position compared to other branches, and the results can be a dashboard to find the best practices for benchmarking.

Compared with traditional DEA methods which use deterministic data and consider decision-making units as black boxes, in this research, a grey two-stage DEA model is proposed to evaluate the efficiency of bank branches. Furthermore, grey clustering and grey ranking of efficiency values are used as a novel solution for improving the accuracy of grey two-stage DEA results.

This study collected the bibliographic data of 2034 journal articles published in 2000–2021 from Web of Science (WoS) core collection database and adopted two bibliometric analysis methods, namely historiography and keyword co-occurrence, to identify the evolution trend of construction risk management (CRM) research topics.

CRM has been a key issue in construction management research, producing a big number of publications. This study aims to undertake a review of the global CRM research published from 2000 to 2021 and identify the evolution of the research topics relating to CRM.

This study found that risk analysis methods have shifted from simply ranking risks in terms of their relative importance or significance toward examining the interrelationships among risks, and that the objects of CRM research have shifted from generic construction projects toward specified types of construction projects (e.g. small projects, underground construction projects, green buildings and prefabricated projects). In addition, researchers tend to pay more attention to an individual risk category (e.g. political risk, safety risk and social risk) and integrate CRM into cost, time, quality, safety and environment management functions with the increasing adoption of various information and communication technologies.

This study focused on the journal articles in English in WoS core collection database only, thus excluding the publications in other languages, not indexed by WoS and conference proceedings. In addition, the historiography focused on the top documents in terms of document strength and thus ignored the role of the documents whose strengths were a little lower than the threshold.

This review study is more inclusive than any prior reviews on CRM and overcomes the drawbacks of mere reliance on either bibliometric analysis results or subjective opinions. Revealing the evolution process of the CRM knowledge domain, this study provides an in-depth understanding of the CRM research and benefits industry practitioners and researchers.

The possibility function-based grey clustering model has evolved into a complete approach for dealing with uncertainty evaluation problems. Existing models still have problems with the choice dilemma of the maximum criteria and instances when the possibility function may not accurately capture the data's randomness. This study aims to propose a multi-stage skewed grey cloud clustering model that blends grey and randomness to overcome these problems.

First, the skewed grey cloud possibility (SGCP) function is defined, and its digital characteristics demonstrate that a normal cloud is a particular instance of a skewed cloud. Second, the border of the decision paradox of the maximum criterion is established. Third, using the skewed grey cloud kernel weight (SGCKW) transformation as a tool, the multi-stage skewed grey cloud clustering coefficient (SGCCC) vector is calculated and research items are clustered according to this multi-stage SGCCC vector with overall features. Finally, the multi-stage skewed grey cloud clustering model's solution steps are then provided.

The results of applying the model to the assessment of college students' capacity for innovation and entrepreneurship revealed that, in comparison to the traditional grey clustering model and the two-stage grey cloud clustering evaluation model, the proposed model's clustering results have higher identification and stability, which partially resolves the decision paradox of the maximum criterion.

Compared with current models, the proposed model in this study can dynamically depict the clustering process through multi-stage clustering, ensuring the stability and integrity of the clustering results and advancing grey system theory.

Small- and medium-sized enterprises (SMEs) often operate in environments marked by high levels of turbulence. Such firms adopt digital technologies and platforms that provide access to external real-time information and establish digital connectivity between firms to remain competitive. This study aims to focus on SMEs’ downstream and upstream platform-based digital connectivity (PDC).

This study examines the effects of PDC on SMEs’ operational performance under conditions of environmental turbulence. The data was gathered from 192 SMEs operating in the manufacturing arena.

The results show that the adoption of PDC does not directly affect an SME’s operational performance. However, in highly turbulent environments, PDC can improve operational performance. The results indicate that the performance effects of PDC vary according to the level and type of environmental turbulence.

This research offers insights into the relationship between PDC among SMEs and operational performance and encourages future research examining other possible conditional effects that could explain the contradictory results found in previous research.

This study contributes to the knowledge of supply-chain digitalization among SMEs and its performance effects in varying environmental conditions. Further, this study contributes to the prior research by focusing on the interorganizational aspects of digitalization in SMEs.

Perceived benefits of building information modelling (BIM) have been discussed for some time, but cost–benefit benchmarking has been inconsistent. The purpose of this paper is to investigate BIM feasibility and evaluate investment worth to elucidate and develop the current understanding of BIM merit. The aim of the study is to propose a research agenda towards a more holistic perspective of BIM use incorporating quantifying investment return.

An in-depth examination of research patterns has been conducted to identify challenges in the assessment of the investment value and return on investment (ROI) for BIM in the construction industry. A total of 75 research articles were considered for the final literature review. An evaluation of the literature is conducted using a combination of bibliometric analysis and systematic reviews.

This study, which analysed 75 articles, unveils key findings in quantifying BIM benefits, primarily through ROI calculation. Two major research gaps are identified: the absence of a standardized BIM ROI method and insufficient exploration of intangible benefits. Research focus varies across phases, emphasizing design and construction integration and exploring post-construction phases. The study categorizes quantifiable factors, including productivity, changes and rework reduction, requests for information reduction, schedule efficiency, safety, environmental sustainability and operations and facility management. These findings offer vital insights for researchers and practitioners, enhancing understanding of ’BIM’s financial benefits and signalling areas for further exploration in construction.

The ’study’s outcomes offer the latest insights for researchers and practitioners to create effective approaches for quantifying ’BIM’s financial benefits. Additionally, the proposed research agenda aims to improve the current limited understanding of BIM feasibility and investment worth evaluation. Results of the study could assist practitioners in overcoming limitations associated with BIM investment and economic evaluations in the construction industry.

Coastal zone ecological restoration project is of great significance to alleviate marine ecological degradation. Evaluating the effect of coastal ecological restoration projects and identifying the obstacle factors affecting their restoration level can provide an empirical basis for future Marine ecological restoration projects.

However, due to the initial stage of coastal zone ecological restoration projects, the actual monitoring data of coastal zone ecological restoration is relatively lacking. Based on the CRITIC-TOPSIS (combination of CRITIC method and TOPSIS method) method, combined with the subjective perception of the public and the actual data of the restoration project, this paper proposes an evaluation method of the coastal zone ecological restoration effect to obtain the specific implementation effect of the coastal zone ecological restoration project. The main obstacle factors affecting the evaluation of coastal ecological restoration effect are identified by using the obstacle degree model.

This paper conducted an empirical study on the restoration of sandy shoreline and coastal wetland in Qinhuangdao city. Based on the data of restoration projects and the subjective perception of ecological restoration by the public in Qinhuangdao city, the research results showed that the coastal zone ecological restoration effect of Qinhuangdao city was general. The quality of the restoration project and the public perception have an important influence on the evaluation of the restoration effect. Improving the quality of the restoration project, strengthening the public's participation in ecological restoration and allowing the public to better participate in the ecological restoration of the coastal zone can improve the effect of ecological restoration of the coastal zone in an all-round way.

The research results of this paper have a guiding role in the ecological restoration of coastal cities in the future, and also have a demonstration and reference role for the assessment of the effect of ecological restoration of coastal zones.

This paper aims to understand and document evaluation criteria used in the new product development (NPD) process of small- and medium-sized enterprises (SMEs) to support the management and control of their NPD projects.

This study combines exploratory and explanatory methodology (case studies) involving five Canadian small and medium enterprises (SMEs) that are successful in NPD. The authors conducted semi-structured interviews with nine selected managers and project managers to explore the process and evaluation criteria used to manage and control NPD projects.

The results highlight that cost, time and quality are key evaluation criteria used by SMEs to make decisions relative to the NPD project's success. Profitability, return on investment, expected sales and customer satisfaction are additional criteria used to evaluate NPD project's success. It has been also found that the SMEs did not consider sustainability issues in the criteria used as their focus are on the needs of stakeholders, mainly customers.

Limitations: The evaluation criteria are extracted from a limited number of SMEs that have successfully carried out NPD projects and may therefore be influenced by some contextual factors. The results cannot be generalized to all SMEs or to all projects, as their characteristics may differ. Implications: This study offers a novel outlook on NPD process in SMEs, by documenting criteria related to constraints in project management. The integration of theory of constraints contributes to increasing theoretical knowledge about the management and control of NPD projects in SMEs. It provides insight into how project managers (and other decision makers) can increase the chances of project success by managing project constraints and criteria.

The evaluation criteria identified in this study can therefore be of use to SMEs managers and project leaders seeking to improve the management and control of their NPD projects. These criteria can help them better manage their limited resources and skills and allocate them to the most promising projects. They can also help them conduct their NPD process more efficiently to achieve the intended objectives, including the desired project profitability targets.

This paper offers new insight and practical implications about evaluation criteria within the stages and activities of the NPD process that needed to be considered by SMEs' managers involved in NPD projects.

Robotic process automation (RPA) has recently emerged as a technology focusing on the automation of repetitive, frequent, voluminous and rule-based tasks. Despite a few practical examples that document successful RPA deployments in organizations, evidence of its economic benefits has been mostly anecdotal. The purpose of this paper is to present a step-by-step method to RPA investment appraisal and a business case demonstrating how the steps can be applied to practice.

The methodology relies on design science research (DSR). The step-by-step method is a design artefact that builds on the mapping of processes and modelling of the associated costs. Due to the longitudinal nature of capital investments, modelling uses discounted cashflow and present value methods. Empirical grounding characteristic to DSR is achieved by field testing the artefact.

The step-by-step method is comprised of a preparatory step, three modelling steps and a concluding step. The modelling consists of compounding the interest rate, discounting the investment costs and establishing measures for comparison. These steps were applied to seven business processes to be automated by the case company, Estate Blend. The decision to deploy RPA was found to be trivial, not only based on the initial case data, but also based on multiple sensitivity analyses that showed how resistant RPA investments are to changing circumstances.

By following the provided step-by-step method, executives and managers can quantify the costs and benefits of RPA. The developed method enables any organization to directly compare investment alternatives against each other and against the probable status quo where many tasks in organizations are still carried out manually with little to no automation.

The paper addresses a growing new domain in the field of business process management by capitalizing on DSR and modelling-based approaches to RPA investment appraisal.

This study aims to investigate the growing use of financial metrics (such as return on investment [ROI]) to measure performance and evaluate human capital (HC) investments.

The research employed an embedded case study approach, examining how one ROI approach was applied to evaluating HC investments, across three sectors (corporate, public health and international development).

Three major findings emerged in this study: First, interpretations of ROI can lead to ambiguity during implementation. ROI is interpreted trichotomously – metaphorically, as a desire for value; literally, as a metric; and procedurally, as a method for planning and evaluating HC investments. Second, understanding, measuring and tracking the domains of people performance (cognitive, affective and psychomotor) is vital to evaluating the impact of HC investments because this is where the change in behavior occurs. Third, although the logic model measures the change in process following an intervention (input-activity-output-outcome-impact), other approaches measure the change in behavior of people in the intervention (people performance).

These findings provide clarity for practitioners about challenges when applying ROI.

This is the first study to explore how the ROI financial metric is applied in a new domain by first examining its interpretation. It elucidates the use of ROI in practice, as well as the different purposes of key ROI approaches.