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Big data analytics (BDA) capabilities can affect supply chain performance in several ways. The main purpose of this study was to understand how BDA capabilities could affect supply chain performance through supply chain resilience and supply chain innovation.

The study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. Accordingly, 187 responses were collected and analyzed using partial least squares (PLS) in the SmartPLS3.

The results showed that BDA capabilities improve supply chain performance through resilience and innovation of the supply chain.

The present study also contributed to the existing literature by demonstrating the mediating role of supply chain resilience and supply chain innovation between BDA capabilities and supply chain performance. In this context, some theoretical and managerial implications were proposed and discussed.

Developing country workers mainly face important challenges when examining equality in health services utilization among the population and identifying influential factors. The purpose of this paper us to: understand health service use among households with different socio-economic status in Isfahan province; and to investigate probable inequality determinants in service utilization.

Almost 1,040 households living in Isfahan province participated in this cross-sectional study in 2013. Data were collected by a questionnaire with three sections: demographic characteristics; socio-economic status; and health services utilization. The concentration index was applied to measure inequality. Analysts used STATA 11.

Economic status, educational level, insurance coverage and household gender were the most influential factors on health services utilization. Those with a high socio-economic level were more likely to demand and use such services; although self-medication patterns showed an opposite trend.

Female-headed families face with more difficulties in access to basic human needs including health. Supportive policies are needed to meet their demands.

The authors used principle component analysis to assess households’ economic situation, which reduced the variables into a single index.

This paper aims to investigate the two-dimensional numerical modeling of fluid flow and heat transfer in a fluid channel.

The channel is filled with the CuO-water nanofluid. The KKL model is used to estimate the dynamic viscosity and considering Brownian motion. On the other hand, the influence of CuO nanoparticles’ shapes on the heat transfer rate is taken account in the simulations. The channel is included with several active pipes with hot and cold temperatures. Furthermore, the external curved and sinusoidal walls have cold and hot temperatures, respectively.

Three different tilt angles are considered with similar boundary and operating conditions. The Rayleigh numbers, solid volume fraction of CuO nanoparticles in the pure water and the tilt angles are the governing parameters. Different cases studies, such as streamlines, heat transfer rate, local and total entropy generation and heatlines, are analysed under influences of these governing parameters.

The originality of this work is investigation of fluid flow, heat transfer and entropy generation within a nanofluid filled channel using FVM.

As hospitals are the most costly service providers in every healthcare systems, special attention should be given to their performance in terms of resource allocation and consumption. The purpose of this paper is to evaluate technical, allocative and economic efficiency in intensive care units (ICUs) of hospitals affiliated by Yazd University of Medical Sciences (YUMS) in 2015.

This was a descriptive, analytical study conducted in ICUs of seven training hospitals affiliated by YUMS using data envelopment analysis (DEA) in 2015. The number of physicians, nurses, active beds and equipment were regarded as input variables and bed occupancy rate, the number of discharged patients, economic information such as bed price and physicians’ fees were mentioned as output variables of the study. Available data from study variables were retrospectively gathered and analyzed through the Deap 2.1 software using the variable returns to scale methodology.

The study findings revealed the average scores of allocative, economic, technical, managerial and scale efficiency to be relatively 0.956, 0.866, 0.883, 0.89 and 0.913. Regarding to latter three types of efficiency, five hospitals had desirable performance.

Given that additional costs due to an extra number of manpower or unnecessary capital resources impose economic pressure on hospitals also the fact that reduction of surplus production plays a major role in reducing such expenditures in hospitals, it is suggested that departments with low efficiency reduce their input surpluses to achieve the optimal level of performance.

The authors applied a DEA approach to measure allocative, economic, technical, managerial and scale efficiency of under-study hospitals. This is a helpful linear programming method which acts as a powerful and understandable approach for comparative performance assessment in healthcare settings and a guidance for healthcare managers to improve their departments’ performance.

Big data analytics capability (BDAC) can affect firm performance in several ways. The purpose of this paper is to understand how BDA capabilities affect firm performance through supply chain resilience in the presence of the risk management culture.

The study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. 167 responses were collected and analyzed using partial least squares in SmartPLS3. The respondents were generally senior IT executives with education and experience in data and business analytics.

The results show that BDA capabilities increase supply chain resilience as a mediator by enhancing innovative capabilities and information quality, ultimately leading to improved firm performance. In addition, the relationship between supply chain resilience and firm performance is influenced by risk management culture as a moderator.

The present study contributes to the relevant literature by demonstrating the mediating role of supply chain resilience between the BDA capabilities relationship and firm performance. In this context, some theoretical and managerial implications are proposed and discussed.

The purpose of this study is to develop an efficient numerical procedure for simulating the effect of printing orientation, as one of the primary sources of anisotropy in 3D-printed components, on their fracture properties.

The extended finite element method and the cohesive zone model (XFEM-CZM) are used to develop subroutines for fracture simulation. The ability of two prevalent models, i.e. the continuous-varying fracture properties (CVF) model and the weak plane model (WPM), and a combination of both models (WPM-CVF) are evaluated to capture fracture behavior of the additively manufactured samples. These models are based on the non-local and local forms of the anisotropic maximum tangential stress criterion. The numerical models are assessed by comparing their results with experimental outcomes of 16 different configurations of polycarbonate samples printed using the material extrusion technique.

The results demonstrate that the CVF exaggerates the level of anisotropy, and the WPM cannot detect the mild anisotropy of 3D-printed parts, while the WPM-CVF produces the best results. Additionally, the non-local scheme outperforms the local approach in terms of finite element analysis performance, such as mesh dependency, robustness, etc.

This paper provides a method for modeling anisotropic fracture in 3D-printed objects. A new damage model based on a combination of two prevalent models is offered. Moreover, the developed subroutines for implementing the non-local anisotropic fracture criterion enable a reliable crack propagation simulation in media with varying degrees of complication, such as anisotropy.

This paper aims to propose a new nonlinear function estimation fuzzy system as a novel statistical approach to estimate nanofluids’ thermal conductivity.

A fuzzy system having a product inference engine, a singleton fuzzifier, a center average defuzzifier and Gaussian membership functions is proposed for this purpose.

Results indicate that the proposed fuzzy system can predict the thermal conductivity of Al₂O₃/paraffin nanofluid with appropriate precision and generalization and it also outperforms the classic interpolation methods.

A new nonlinear function estimation fuzzy system was introduced as a novel statistical approach to estimate nanofluids’ thermal conductivity for the first time.

Eyewitness testimony can determine the outcome of criminal investigations. The cognitive interview (CI) has been widely used to collect informative and accurate accounts. However, face-to-face interviews have been restricted during the current pandemic, raising the need for using video-conferencing. The authors tested whether virtual interviews could produce elaborate accounts from eyewitnesses and if the CI superiority effect against a structured interview (SI) could be fully replicated online.

The authors used a 2 × 2 factorial design with interview condition (CI vs SI) and environment (face-to-face vs virtual) manipulated between-subjects. A total of 88 participants were randomly assigned to one of the four conditions. Participants watched a mock robbery and were interviewed 48 h later using either the SI or the CI. Both interviews contained the same structure and interview phases but only the CI included its key cognitive mnemonics/ instructions. Both sessions were either face-to-face or online.

Participants interviewed with the CI recalled more information than participants interviewed with the SI, regardless of the interview environment. Both environments produced a comparable amount of recall. Report accuracy was high for all groups.

This can be crucial to inform police practices and research in this field by suggesting investigative interviews can be conducted virtually in situations such as the current pandemic or when time and resources do not allow for face-to-face interviewing.

To the best of the authors’ knowledge, this is the first study showing that the CI superiority effect can be replicated online and that a fully remote CI can produce elaborate accounts.

The purpose of this paper is to explore the possible relationship between knowledge management infrastructures (KMI) and organizational intelligence (OI) in two country-wide research centers dependent to Ministry of Science, Research and Technology, namely, Iranian Research Institute for Information Science and Technology (IRIIST) and Institute for Humanities and Cultural Studies (IHCS).

The research is a survey in a descriptive manner. Using two validated questionnaires related to KMI and OI, the research was conducted among 175 faculty members and staffs of the two research centers. Using structural equation modeling (SEM) procedures, collected data were then analyzed by software SPSS and partial least squares.

Factor analysis showed a high factor loading related to the two main variables and all of the items indicated goodness of fit (GoF) related to the questions. The variance-mean ratio between two variables was higher than 0.5 indicating a high convergent validity. R² for OI showed fitness of SEM. The GoF for IRIIST was 0.642 lower than IHCS with 0.645. Also, path analysis indicated a significant relationship between two variables by 95 percent degree of confidence accepting the two research hypothesis.

By comparison, KMI was more correlated with OI in IHCS than IRIIST. KMI in IRIIST predicted OI by 0.826 percent while in the IHCS by 0.848 percent.

The purpose of this paper is to investigate the drivers of e-banking entrepreneurship. The impact of e-banking entrepreneurship on banks’ performance in the banking industry is also investigated.

A questionnaire was developed to collect data from 16 banks with a sample of 214 respondents. Structural equation modeling using PLS was conducted to analyze the data.

The results reveal a significant impact of top management support, organizational context, technological context and social capital on the degree of e-business entrepreneurship. The findings also reveal a direct impact of e-banking entrepreneurship on achieving a competitive advantage, financial performance and customer performance.

The present empirical study contributes to a better understanding of the existing theories and practices of banking entrepreneurship and e-innovations in today’s banking industry. This study also provides insights into the drivers and the role of e-entrepreneurship in this industry for improving the opportunities of competitiveness and growth. The findings of the present study are of importance to both academic and practitioner audiences. The present study provides empirical evidence to bolster e-banking technology as an enabler of banking entrepreneurship and improving performance. Additionally, these findings provide directives to managers regarding the untapped opportunities and potential that innovative e-banking technology can offer in a highly volatile and rapidly changing environment.