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Islamic financial technology (fintech), primarily peer-to-peer (P2P) lending, plays a substantial role in funding the unbanked population and small and medium enterprises (SMEs) by offering streamlined financial services through online digital technology. In addition, Islamic fintech lending offers a promising return rate for individual and institutional investors, and therefore, it is considered a worthy investment alternative for diversification. This study aims to examine the determinants of project returns of SMEs on Islamic fintech lending platforms, taking the case study of one Islamic fintech lending platform registered at the Financial Service Authority in Indonesia.

Project return information and other information, such as the name of the SME raising fund, project duration, location, contract (aqad) and value (amount of money) to be raised, were extracted from the Islamic fintech lending platform. Furthermore, a regression analysis was performed using the completed projects as sample data (n = 122) on the platform.

The results show that the rate of return is significantly affected by project duration and type of Sharia-compliant contract. Location and project value are, however, found to be statistically insignificant. This study’s overall results align with the Signaling theory, indicating the importance of information for decision-making.

Due to limited access to the data, our study uses data from one of seven Islamic fintech lending platforms; thus, the study results may not be generalized to the general population.

The results suggest that investors aspiring to invest their funds in SME projects on Islamic fintech lending platforms should consider the project duration and contractual agreement since these factors significantly influence the return. Additionally, society may consider the Islamic fintech lending platform a viable investment instrument since its return rate follows the risk-return principle in classical and established finance theories. That is why Islamic fintech lending platforms are competitive compared to the more established ones, such as the Islamic stock market.

To the best of the authors’ knowledge, this study is the first study using an empirical approach to reveal the project return determinants of SMEs on Islamic fintech lending platform.

The present study aims to inform the requirements for developing a sustainable rating tool for small-scale infrastructure projects (SSIPs) through research findings.

A review-based comparative study of existing infrastructure sustainability (IS) rating tools for assessment of SSIPs is presented. Key stakeholder participants of the existing IS rating tools, are interviewed to identify existing barriers and requirements for sustainability rating. The study further presents possible rating tool options to optimise the sustainable performance evaluation of SSIPs.

Findings of this study indicated that prevalent IS rating tools are majorly applied to large-scale infrastructure projects and sustainability of SSIPs are seldom assessed. Based on a literature review and series of interviews, it was found that user friendliness, efficient structure, training and technical support, cost effectiveness and stakeholder recognition are the five key requirements of a sustainability rating tool for SSIPs. Additionally, six sustainability assessment options were proposed for SSIPs which range from pathways for existing tools through to new, customisable tools. Upon comparison, a new modified tool with verification process and revised tool with defined grouping of sustainable criteria was more effective for evaluation of SSIPs.

Use of case specific information for validation and framework development may lack generalisation. However, methodology can be used for future decision-making by making necessary adjustments to suit different local regional requirements.

Despite lack of generalisation, the findings can lead to future general studies on sustainability of SSIPs. Findings of the study provide foundation knowledge and awareness for sustainability evaluation of SSIPs.

The European Commission has established the reference value of the social discount rate (SDR) to be used in the cost-benefit analysis according to the subdivision of the states relating to the beneficiaries of the Cohesion Fund. This criterion does not allow to adequately consider the economic, social and environmental conditions of each European states for ensuring an equitable and inclusive growth. The aimof the work is to provide an innovative methodology for assessing the “adjusted” SDR according to the socioeconomic and environmental conditions that differently affect the sustainable development of each European state.

Through the implementation of a methodological approach that consists of ordered and sequential phases and the synergic adoption of the Multi-Criteria Techniques with the Data Envelopment Analysis, a corrective coefficient of the SDR established by the European Commission is determined.

The results obtained for the 27 European states highlight how the different conditions of each of them could affect the correct choice of the SDR to be used in the Cost-Benefit Analysis.

The proposed research represents a useful reference for identifying national reference SDR values for each European state, consistent with its specificities and with the goals of inclusive growth of the countries and of social and territorial cohesion. Furthermore, the traceability of the methodology in its phases will allow to adapt the SDR to sudden events or exogenous shocks.

The primary objective of this research is to explore the potential of utilizing Global Consciousness Project (GCP) data as a tool for understanding and predicting market sentiment. Specifically, the study aims to assess whether incorporating GCP data into econometric models can enhance the comprehension of daily market movements, providing valuable insights for traders.

This study employs econometric models to investigate the correlation between the Standard & Poor's 500 Volatility Index (VIX), a common measure of market sentiment and data from the GCP. The focus is particularly on the largest daily composite GCP data value (Max[Z]) and its significant covariation with changes in VIX. The research employs interaction terms with VIX and daily returns from global markets, including Europe and Asia, to explore the relationship further.

The results reveal a significant relationship with the GCP data, particularly Max[Z] and VIX. Interaction terms with both VIX and daily returns from global markets are highly significant, explaining about one percent of the variance in the econometric model. This finding suggests that variations in GCP data can contribute to a better understanding of market dynamics and improve forecasting accuracy.

One limitation of this study is the potential for overfitting and P-hacking. To address this concern, the models undergo rigorous testing in an out-of-sample simulation study lasting for a predefined one-year period. This limitation underscores the need for cautious interpretation and application of the findings, recognizing the complexities and uncertainties inherent in market dynamics.

The study explores the practical implications of incorporating GCP data into trading strategies. Econometric models, both with and without GCP data, are subjected to an out-of-sample simulation where an artificial trader employs S&P 500 tracking instruments based on the model's one-day-ahead forecasts. The results suggest that GCP data can enhance daily forecasts, offering practical value for traders seeking improved decision-making tools.

Utilizing data from the GCP is found to be advantageous for traders as noteworthy correlations with market sentiment are found. This unanticipated finding challenges established paradigms in both economics and consciousness research, seamlessly integrating these domains of research. Traders can leverage this innovative tool, as it can be used to refine forecasting precision.

Customer lifetime value (CLV) is one of the key indicators to measure the success or health of an organization. How can an organization assess the organization's customers' lifetime value (LTV) and offer relevant strategies to retain prospective and profitable customers? This study offers an integrated view of different methods for calculating CLVs for both loyalty members and non-membership customers.

This study outlines eleven methods for calculating CLV considering (1) the deterministic aspect of NPV (Net present value) models in both finite and infinite timespans, (2) the geometric pattern and (3) the probabilistic aspect of parameter estimates through simulation modeling along with (4) the migration models for including “the probability that customers will return in the future” as a key input for CLV calculation.

The CLV models are validated in the context of complementary and alternative medicine (CAM)in the healthcare industry. The results show that understanding CLV can help the organization develop strategies to retain valuable customers while maintaining profit margins.

The integrated CLV models provide an overview of the mathematical estimation of LTVs depending on the nature of the customers and the business circumstances and can be applied to other business settings.

As a disruptive technology, blockchain technology brings new opportunities and challenges to operations management. We aim to examine the influences of blockchain cooperation project announcements (BCPAs) on firms’ stock market reactions in an emerging market. From 2016 to 2021, a total of 113 BCPAs of listed firms from the Chinese A-share market are selected as samples.

This study is based on the loose coupling theory and uses the event study method and probit regression analysis.

We find BCPAs positively affect the firm’s stock price on the day they are released. Compared with vertical BCPAs in a supply chain, horizontal BCPAs exert a more positive market reaction. Moreover, a BCPA with a partner within a shorter geographical distance exerts a more positive influence on market reaction. Contrary to the intuition of the decentralized blockchain feature that one-to-many cooperation leads to better benefits, one-to-one BCPAs exert a more positive effect on market reaction than one-to-many BCPAs. We further find that (1) industry type has a certain impact on cooperation mode selection, and (2) manufacturing firms are more inclined to choose one-to-one cooperation than those in service industry.

We focus on the impact of blockchain cooperative announcements and additionally use the probit regression models to analyze the influencing factors of cooperation mode selection and find the critical role of the industry type, which complements the existing empirical research on blockchain announcements and is conducive to provide decision-making reference for managers.

The purpose of microcredit is to offer small loans to people who are not covered by traditional financial channels. It can facilitate entrepreneurship, boosting local socio-economic development and improving environmental and political factors.

This paper aims to analyse microcredit in Italy, focusing on a project based in Rione Sanità, Naples. Rione Sanità is one of the poorest areas of Southern Italy, displaying high rates of criminality and unemployment, especially among youth, women, migrants and the vulnerable. The district is renowned for its fine and ancient handicrafts, food, trade and historical heritage – potential drivers for boosting tourism in the area. Qualitative methodologies were used to collect primary data through field visits and interviews with project bankers, local businesses, artisans, associations and religious representatives, project volunteers, as well as participation at local meetings. These data were corroborated by budget analysis based on the project's accounting.

The study shows encouraging results for the project and policy prospects. Despite the tiny starting numbers, there emerges a significant potential for microcredit to spread in the district, as in Southern Italy, providing an effective strategy to combat unemployment, usury and criminality, yielding community development and favoring broad societal challenges.

With this evidence, the paper attempts to shed some light and verify the potential of microfinance projects as a driver of sustainable development and ethical finance in poor areas of developed countries.

The role of construction industry in harnessing human and material resources of a nation cannot be overemphasised; hence, the emergence of the requirement of leadership. This study aims to assess the usage of factors of transactional leadership style (TSLS) by the project managers (PMs) in the Nigeria construction industry.

A survey research design approach with questionnaire as an instrument of gathering data was adopted. Out of 1,233 questionnaires distributed, data from 975 received with acceptable feedback were analysed using both descriptive and inferential statistics.

This study revealed the following factors under active management by exception as the TSLS factors often employed by PMs in Nigeria. These factors are the three frequently used factors: they are: “always give clear and final instructions to be implemented in the project”; “always observed the progress of the project, assessed risk and took precaution to avoid mistakes in the project”; and “always closely monitor performance for errors needing correction”. This study concludes that it is imperative for PMs in the study area to adopt and incorporate these factors to ensure continuous successful delivery of construction projects.

Therefore, it is hoped that the findings of this research will help the construction industry managers to address the age-long but unrecognised leadership problem confronting the sector, thereby boosting project delivery.

The findings establish the appropriateness or otherwise of adoption of factors of transactional leadership, either in part or a whole.

This study examines how local governments and enterprises can implement ecological restoration of abandoned mines based on ecology-oriented development (EOD), which will be more beneficial to local environmental protection and economic development under the central government’s policy of outcome incentives or process subsidies.

We construct a dynamic differential game model to simulate the interactions between local governments and enterprises during the ecological restoration of abandoned mines from an EOD perspective.

The findings suggest that under the central government’s outcome incentive policy, cooperation between local governments and enterprises is an optimal strategy. Under the process subsidy policy, while neither cooperative nor non-cooperative models significantly affect the investment levels of local governments and enterprises, a cooperative approach ensures optimal investments from both without solely relying on the process subsidy. Additionally, incorporating altruistic preferences can lead to Pareto improvements in economic and environmental results under central government outcome incentives.

This research offers a policy foundation for governments to encourage the EOD model in the ecological restoration of abandoned mines. It provides theoretical support for achieving environmental sustainability and high-quality economic development, and is particularly significant for resource-depleted cities seeking to transform their development strategies.

Through a dynamic differential game model involving government agencies and enterprises to simulate decision-making in the ecological restoration of abandoned mines, incorporating altruistic preferences into this restoration process, and identifying optimal strategies and policies for ecological restoration.

Equitable risk allocation is important for the effective management of inevitable risks in International Construction Joint Venture (ICJV) projects. Previous studies have documented risks facing ICJV projects. However, there is a dearth of studies on the risk allocation preferences that take into consideration the opinions of both the local and foreign partners. This study aims to fill this gap by ascertaining the risk allocation preferences of the partners of ICJV projects for effective risk management.

Through a survey, data on risk allocation preferences were collected from both local and foreign partners of ICJV projects using a comprehensive register of 74 risks.

Following analysis, six risks were allocated to the local partner, 11 were allocated to the foreign partner, 51 risks were shared, four were allocated to a third party and two were to be negotiated based on the specific circumstances of the project. Practically, the study’s findings will help ICJV partners in drafting their ICJV contracts to adequately allocate risks and reduce contract negotiation time considerably.

The findings from this study will help partners in drafting their joint venture contract agreement and also reduce the period for contract negotiation. Knowledge of the preferred risk allocation is important in allocating risks in the contract agreement to the relevant partner for effective management.

This study, to the best knowledge of the authors, is one of the early studies to ascertain the risk allocation preferences of ICJV project partners in the Ghanaian construction industry – a departure from previous studies which focused on the identification and evaluation of risks. This study is also different from previous studies by considering the allocation preferences of both partners of the ICJV. The collection of data from both partners of the ICJV helped to consider their perceptions on risk allocation and evaluation, essentially leading to cross-cultural and optimal risk allocation preferences.