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The purpose of this study is to forecast the mechanical properties of ternary blended concrete (TBC) modified with oyster shell powder (OSP) and shea nutshell ash (SNA) using deep neural network (DNN) models.

DNN models with three hidden layers, each layer containing 5–30 nodes, were used to predict the target variables (compressive strength [CS], flexural strength [FS] and split tensile strength [STS]) for the eight input variables of concrete classes 25 and 30 MPa. The concrete samples were cured for 3–120 days. Levenberg−Marquardt's backpropagation learning technique trained the networks, and the model's precision was confirmed using the experimental data set.

The DNN model with a 25-node structure yielded a strong relation for training, validating and testing the input and output variables with the lowest mean squared error (MSE) and the highest correlation coefficient (R) values of 0.0099 and 99.91% for CS and 0.010 and 98.42% for FS compared to other architectures. However, the DNN model with a 20-node architecture yielded a strong correlation for STS, with the lowest MSE and the highest R values of 0.013 and 97.26%. Strong relationships were found between the developed models and raw experimental data sets, with R² values of 99.58%, 97.85% and 97.58% for CS, FS and STS, respectively.

To the best of the authors’ knowledge, this novel research establishes the prospects of replacing SNA and OSP with Portland limestone cement (PLC) to produce TBC. In addition, predicting the CS, FS and STS of TBC modified with OSP and SNA using DNN models is original, optimizing the time, cost and quality of concrete.

Commercial banks are the catalysts for meeting the financing needs of small and medium enterprises (SMEs). However, not all commercial banks are equally attractive to SMEs because of differences in banking services’ key attributes. Moreover, customers’ preferences vary between Islamic and conventional banks. This paper aims to identify factors motivating SMEs to establish business ties with banks in Oman.

The authors collected data from 217 SMEs through a questionnaire survey. The data were analyzed using a t-test and structural equation modeling (SEM). In addition, the research applies the theory of planned behavior as a theoretical framework.

The t-test results show that SMEs place greater emphasis on electronic banking, convenient locations, religious beliefs and favorable terms and conditions. The results from the SEM analysis show that the SMEs in Oman consider attractive packages, including favorable rates, transaction processing time, fees and the availability of technology-enabled services, when choosing a bank. Moreover, customers who are aware of Islamic banking products are optimistic about the future of Shariah-based banking.

As a Muslim-majority country, Oman lags behind its Gulf Cooperative Council peers in terms of the development of the Islamic banking system. For the success of this mode of financing, it is essential to know which factors SMEs prioritize to establish ties with Islamic banks. Hence, the research is expected to provide new information for bank management to devise financial products attractive to investors.

Talent management can provide an organization with a competitive advantage. However, little is known about how human resource practices pertaining to talent management drive positive outcomes. Drawing on social exchange theory, this study investigates the effect of talent management practices usage on employee commitment and intention to leave. Integrating social exchange theory and the theory of met expectations facilitated predicting the mediating role of perceived career growth in the talent management practices usage-employee outcomes relationship.

Data were collected using a survey from 268 employees from eight organizations from the financial and services industries in Jordan.

Talent management practices usage has a significant direct positive effect on employee commitment but no direct effect on employees’ intention to leave. Further, there is pioneering evidence that perceived career growth mediates the following relationships: talent management practices usage and commitment and talent management practices usage and intention to leave.

The study provides unprecedented evidence of the effect of TM practices usage on employee outcomes and the role of perceived career growth in the TM practices usage-employee outcomes relationship from an underexplored context of Jordon. Our research results contribute to theory development in TM by supporting, extending and integrating social exchange theory and the theory of met expectations.