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The purpose of this paper is to present the efficient iterative methods for solving linear complementarity problems (LCP), using a class of pre-conditioners.

By using the concept of solving the fixed-point system of equations associated to the LCP, pre-conditioning techniques and Krylov subspace methods the authors design some projected methods to solve LCP. Furthermore, within the computational framework, some models of pre-conditioners candidates are investigated and evaluated.

The proposed algorithms have a simple and graceful structure and can be applied to other complementarity problems. Asymptotic convergence of the sequence generated by the method to the unique solution of LCP is proved, along with a result regarding the convergence rate of the pre-conditioned methods. Finally, a computational comparison of the standard methods against pre-conditioned methods based on Example 1 is presented which illustrate the merits of simplicity, power and effectiveness of the proposed algorithms.

Comparison between the authors' methods and other similar methods for the studied problem shows a remarkable agreement and reveals that their models are superior in point of view rate of convergence and computing efficiency.

For solving LCP more attention has recently been paid on a class of iterative methods called the matrix-splitting such as AOR, MAOR, GAOR, SSOR, etc. But up to now, no paper has discussed the effect of pre-conditioning technique for matrix-splitting methods in LCP. So, this paper is planning to fill in this gap and the authors use a class of pre-conditioners with iterative methods and analyze the convergence of these methods for LCP.

This work presents a new two-step iterative technique for solving absolute value equations. The developed technique is valuable and effective for solving the absolute value equation. Various examples are given to demonstrate the accuracy and efficacy of the suggested technique.

In this paper, we present a new two-step iterative technique for solving absolute value equations. This technique is very straightforward, and due to the simplicity of this approach, it can be used to solve large systems with great effectiveness. Moreover, under certain assumptions, we examine the convergence of the proposed method using various theorems. Numerical outcomes are conducted to present the feasibility of the proposed technique.

This paper gives numerical experiments on how to solve a system of absolute value equations.

Nowadays, two-step approaches are very popular for solving equations (1). For solving AVEs, Liu in Shams (2021), Ning and Zhou (2015) demonstrated two-step iterative approaches. Moosaei et al. (2015) introduced a novel approach that utilizes a generalized Newton’s approach and Simpson’s rule to solve AVEs. Zainali and Lotfi (2018) presented a two-step Newton technique for AVEs that converges linearly. Feng and Liu (2016) have proposed minimization approaches for AVEs and presented their convergence under specific circumstances. Khan et al. (2023), suggested a nonlinear CSCS-like technique and a Picard-CSCS approach. Based on the benefits and drawbacks of the previously mentioned methods, we will provide a two-step iterative approach to efficiently solve equation (1). The numerical results show that our proposed technique converges rapidly and provides a more accurate solution.

The purpose of this paper is to develop a numerical method based on quintic B‐spline to solve the linear and nonlinear Fredholm and Volterra integral equations.

The solution is collocated by quintic B‐spline and then the integral equation is approximated by the Gauss‐Kronrod‐Legendre quadrature formula.

The arising system of linear or nonlinear algebraic equations can solve the linear combination coefficients appearing in the representation of the solution in spline basic functions.

The error analysis of proposed numerical method is studied theoretically. Numerical results are given to illustrate the efficiency of the proposed method. The results are compared with the results obtained by other methods to verify that this method is accurate and efficient.

The paper provides new method to solve the linear and nonlinear Fredholm and Volterra integral equations.

The high degree of likely disruption challenges organizations at all levels to develop and implement innovative strategies. Ensuring supply chain continuity even during emergency and complex situations is critical for organizations. Therefore, this study explores some strategies adopted by firms based on innovation and blockchain-enabled digital transformation to reduce risk in their supply chain.

This study follows the qualitative form of enquiry. The authors interviewed 26 professionals from the supply chain domain. After three-layered coding and mapping multiple layers to the data of interviews, the authors identified emerging themes and sub-themes through a thematic analysis.

The authors identified type of risks that can affect global supply chains along with both the role of blockchain and innovation culture in minimizing the degree of such risks and the challenges in adopting blockchain technologies. This led us to develop a framework to address supply chain risk through digital transformation through innovation and blockchain.

This research offers exciting implications for practice by drawing on the insights gathered to facilitate supply chain risk management through innovation and blockchain applications for organizations that are strongly impacted by digital transformation practices around the world. The study also offers the utilization of a framework followed by propositions to reduce supply chain risks in the digital transformation era.

This study focuses on presenting a mechanism of supply chain risk management through the application of innovation and blockchain technology for the digital transformation of a value chain. Blockchain can offer an innovative platform to ready the supply chain for future dynamic situations.

This paper aims to set out the development, based on the extant literature, an integrated conceptual framework for the emergent field of sustainable global sourcing (GS) that synthesizes its antecedents, GS practices and sustainable performance.

Conceptual theory building combined with content analysis is used to develop a framework and propositions representing a middle-range theory of sustainable GS. A literature review of the 89 most influential papers is followed by a further discussion based on the resource orchestration perspective (ROP) to advance an integrated conceptual framework.

Three main themes are identified from the literature as antecedents, GS practices and sustainable performance, with each theme being detailed in a variety of constructs. Based on the ROP, the relationships between these constructs are revealed, and therefore, an integrated conceptual framework is advanced via three sets of propositions in recourse orchestration breadth, recourse orchestration depth and resource orchestration evolution, respectively. Eight directions for future research are further proposed.

First, this study provides a comprehensive framework for future study in the emergent field of sustainable GS. Second, the authors contribute to theory development by proposing a ROP to explore the GS practices towards sustainability. Third, the future research directions we proposed can benefit scholars interested in the overlapping areas of GS and sustainability.

This study empirically investigates how ambidextrous innovations and their balancing affect the supply chain financing performance (SCFP) of small and medium-sized enterprises (SMEs), based on signaling theory. Moreover, this study explores the moderating effect of the breadth and depth of digital technology deployment on the relationship between ambidextrous innovations and the SCFP of SMEs.

A mixed-methods design is used, including a qualitative study and a quantitative study. Qualitative data have been collected from six multi-cases in different industries. Questionnaire data have been collected from 259 SMEs in China, and a multiple regression model is used to verify the research hypotheses.

The findings indicate that, in supply chain financing, both exploitative innovation and exploratory innovation are helpful in improving the SCFP of SMEs. For resource-constrained SMEs, a relative balance between exploitative innovation and exploratory innovation can help improve SCFP. The breadth of digital technology deployment can strengthen the relationship between exploitative innovation and SCFP, while the depth of digital technology deployment can weaken the relationship between exploratory innovation and SCFP. In addition, increasing the depth of digital technology deployment strengthens the positive correlation between the relative balance of ambidextrous innovations and SCFP.

To effectively obtain supply chain financing, SMEs can either concentrate their limited resources on a single type of innovation or use relative balance strategies to simultaneously pursue two innovations. In addition, in the process of obtaining supply chain financing by ambidextrous innovations, SMEs should appropriately deploy digital technologies.

This study first deconstructs the impact mechanism of ambidextrous innovation capabilities on SCFP based on signaling theory, and then discusses the balancing effect of ambidextrous innovations on SCFP in the cases of resource-constrained SMEs. This study also goes further and finds the negative moderating effect of digital technology deployment in the process of supply chain financing.

The purpose of this paper is to investigate the relationships between technology orientations and export performance of small and medium-sized enterprises (SMEs).

A quantitative research design was adopted for this study. The paper formulates hypotheses from the literature review. These hypotheses are tested using structural equation modeling with data collected from 231 SMEs in Uganda. Data were analyzed using SPSS version 23 and AMOS.

The findings of this study showed technology orientation has a positive and significant relationship with the performance of Ugandan SMEs and that supply chain agility moderates technology orientation and export performance.

The study discusses the findings, advances limitations and managerial implications. It also suggests future research avenues. It proposes some recommendations to help Ugandan SMEs to form flexible supply chains, use the latest technology and create strong relationship ties with their partners in the supply chain.

The study suggests that managers of Ugandan SMEs should use the latest technology in production, marketing, logistics and supply chain management which will enable them to respond quickly to customer tastes and preferences leading to higher levels of export performance.

This study contributes to the literature on strategic management showing the reliability of scales used and the confirmatory of the factor structure. This study shows that in strategic management technology, orientation is critical in increasing export performance. This study has extended the resource-based view (RBV) and dynamic capabilities theories.

This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.

The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.

The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.

This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.

The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.

This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.

The purpose of this meta-analysis was to examine the effect of pomegranate juice (PJ) intake on glycemic control in adults.

Materials and methods: PubMed (Medline), ISI Web of Science, Cochrane Library and Scopus databases, measuring glucose and/or insulin and Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) in adults, were searched from inception to December 11, 2021. Moreover, to examine whether grouping factors influenced heterogeneity between research results, subgroup analysis was used.

This meta-analysis showed that PJ intake reduced HOMA-IR significantly, especially if =250 mL was used. This reducing effect remained significant in females, nondiabetic patients and unhealthy subjects.

The authors believe the presented data would be highly motivating and of a wide readership for the readers of your journal, and this paper stimulating a surge of research on the impact of PJ consumption on glycemic indices.

This study aims to assess dietary intake and prevalence of metabolic syndrome (MetS) among tanker truck drivers in the Kumasi metropolis, Ghana.

A cross-sectional study design enrolled 212 fuel tanker drivers. Sociodemographic, anthropometric, dietary and biochemical data were collected. MetS was assessed using the National Cholesterol Education Program Expert Panel on detection, evaluation and treatment of high blood cholesterol in adults Adult Treatment Panel III (NCEP ATP III) 2005 criteria. A three-day 24-h dietary recall was used to assess dietary intake. Binary logistic regression analysis was performed to determine the predicting factors of MetS among study participants.

The prevalence of MetS was 19.6% according to NCEP ATP III criteria. The prevalence of obesity, high BP, hyperglycaemia, dyslipidemia among participants were 7.5, 39.7, 37.7 and 57.3%, respectively. The energy intake for 176 (88.4%) of the participants was inadequate. The predicting factors of MetS were age (OR: 1.3, p = 0.04), glycated haemoglobin (OR: 9.6, p = 0.004), systolic blood pressure (OR: 1.2 95%, p = 0.01) and service years (OR: 0.8, p = 0.01).

The current study focused on MetS among tanker truck drivers in Kumasi metropolis, which makes the current findings only limited to drivers of tanker truck within the municipality. Additionally, the 24-h dietary recall could be subjected to recall bias. However, the study is still of relevance as it becomes the first to target such a group within the municipality, taking into consideration the importance of these tanker truck drivers in driving the economy of Ghana.

This study highlights dietary intake and MetS among fuel tanker drivers previously underreported in the Ghanaian population. Findings of this study would inform further studies on lifestyle-related determinants of MetS among other cohort of drivers in other settings within the country.