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This study aims to investigate how the interplay of multiple strategic orientations influences the growth-based performance of small and medium enterprises (SMEs). The authors have specifically examined the direct and complementary effects of multiple strategic orientations [i.e. entrepreneurial orientation (EO), market orientation (MO) and sustainability orientation (SO)] on firm performance.

The data have been collected from 410 SMEs operating in Pakistan.

The results revealed that the multiple strategic orientations (EO, SO and MO) have positive direct as well as complementary effects on SMEs' growth-based performance. Specifically, the joint effects of EO and MO were shown higher than other combinations and complementarities. Moreover, the direct effect of SO is found far lesser than the joint implementation of SO with either EO or MO.

This study provides key insights into corporate sustainability, strategic orientations and SME performance literature. The implications for theory, practice, policy and future research are discussed.

The breakout of the COVID-19 pandemic has forced governments all over the globe to bring radical changes to all walks of life. Strict lockdowns are not only adversely affecting the social, economic, and psychological wellbeing of individuals but also questioning the sustainability of most businesses. In wake of the current scenario, this study is aimed at exploring how the COVID-19 pandemic is influencing the sustainability of entrepreneurship particularly from a female perspective and further providing insights into the role of Islamic financial institutions in the sustainability of businesses during COVID-19.

This is a qualitative study that takes social constructivism approach to study the underlying phenomenon. Semi-structured interviews are conducted to collect primary data. Secondary data are also utilized in this study to theoretically define various concepts relating to entrepreneurial sustainability. The application of thematic analysis revealed various risks associated with sustainability. The interviews reveal the ground realities and tell us about the hardships being faced by the entrepreneurs due to ongoing crises. The participants of the study also shed light on the role of Islamic financial institutions during the pandemic.

The study results revealed that it may look impossible for women entrepreneurs to halt or avoid the adverse consequences of the pandemic; however, a few female entrepreneurs strived to guard their existing portfolios with the help of Islamic microfinance institutions. Whereas, several women, especially those running home-based businesses, lost their income streams. Despite these rapid challenges, most female entrepreneurs are working on inventive online systems to sustain their business activities during the crisis. Finally, guidelines are suggested which can help achieve sustainability of the entrepreneurial startups.

The outcomes of this study are expedient for funding agencies, government authorities and Islamic financial institutions as well as for non-government institutions to establish sustainable and broader policies for women to become successful entrepreneurs during severe disasters like COVID-19. Moreover, the study is a helpful tool for women entrepreneurs to avert the worst impact of the pandemic with the help of Islamic microfinance institutions. The themes of this study help generate realistic information to appraise the strategies to create facilitating business environments that drive the women to carry out the entrepreneurial activity during any crisis like the COVID-19.

The results of this study provide evidence that crisis can be anticipated up to some extent if entrepreneurs become able to take proactive decisions in case of expected or identifiable threats. The study may also help the women entrepreneurs to comprehend the serious consequences of the pandemic by shifting their mode of financing to Islamic finance. Although this pandemic is a cause of physical discomfort instead this research may encourage the female entrepreneurs not to lose heart, just find the potential opportunities for their home-based and small businesses and manage funding from the Islamic microfinance institutions.

The study adds to the existing literature on entrepreneurial sustainability with a particular focus on the role of Islamic microfinance institutions for women entrepreneurs' sustainability in Pakistan. Secondly, the study employs the entrepreneurial sustainability model (ESM) that, according to the best of our knowledge, has not been used by the researchers earlier to study the given research phenomenon. Thirdly, the study findings are expedient for funding agencies, government authorities and financial institutions as well as for non-government institutions to establish sustainable and broader policies for women to become successful entrepreneurs during disasters like COVID-19.

The purpose of this study is to investigate the relationship between sustainable leadership and sustainable project performance. Specifically, the study aims to examine the mediating role of knowledge integration, examining how knowledge integration within an organization influences project outcomes. In addition, the study seeks to explore the moderating role of top management knowledge values, examining how the values and beliefs of top management influence the relationship between sustainable leadership and project performance.

A three-wave survey of 392 employees working in construction sector projects in Pakistan used both hierarchical regression analysis and Hayes’ PROCESS macro method to evaluate the hypotheses.

The study results show that sustainable leadership positively relates to sustainable project performance and knowledge integration mediating this relationship. In addition, the top management knowledge value moderates the indirect effect of sustainable leadership on sustainable project performance via knowledge integration.

Although the model was tested using three-wave data, it is important to note that the data were obtained from a single source. Therefore, it is possible that common method bias may have influenced the results, and this cannot be disregarded.

Organizations seek to prioritize sustainability and integrate sustainability considerations into their project management processes. Organizations can achieve improved sustainable project performance by investing in sustainable leadership development, fostering a culture of knowledge sharing and learning, prioritizing top management support for sustainable performance and integrating sustainable considerations into project management processes.

The study’s grounding on organizational learning theory adds an original and valuable perspective to the relationship between sustainable leadership and sustainable project performance. This investigation is original, as it combines sustainable leadership, knowledge integration and the moderating role of top management knowledge value to understand their impact on sustainable project performance. This unique approach contributes to the literature by providing new insights into these relationships and mechanisms in the construction industry.

In recent years, especially after the COVID-19 pandemic, home textile production orders decreased significantly. This sudden drop in production has increased industry competition, making customer satisfaction more challenging. As a result, it has become imperative for the industry to deftly navigate such ongoing challenges.

This study examines textile production efficiency methodically. Customer requirements like quality, on-time delivery, better working conditions, cost-effectiveness and facility safety audits are understood first. Quality function deployment (QFD) turns client requirements into technical requirements. Prioritise and analyse risks using Monte Carlo simulation and Pareto charts. Consequently, experts and literature propose corrective measures, which are tested in a pilot run to see how they affect production.

QFD, define, measure, analyse, improve and control (DMAIC) and Monte Carlo simulation were used to reduce high-priority risks and meet client requirements in this study. The house of quality helped relate customers’ requirements and technical requirements. Monte Carlo simulation has also improved risk prioritisation by providing a flexible mathematical structure for identifying and managing the most important risks.

This study is novel in the way it applies this integrated approach to the understudied home textile sector. Unlike traditional DMAIC, this study introduces a novel matrix encompassing all defects. This study offers a data-driven approach to improve product quality, meet customer expectations and reduce prioritised risks in home textile manufacturing.

Drawing upon Drucker’s theory of productivity, this study proposes to examine the relationship between knowledge-oriented leadership (KOL) and knowledge worker performance (KWP) within the Chinese information technology (IT) industry during the COVID-19 pandemic. Further, this study examines the direct connection between KWP and organizational performance (OP), as well as mediated via employee creative work behavior (ECWB), and digital citizenship behavior (DCB).

The data for the research was collected from a sample size of 322 individuals working in the IT industry context in China, with varying levels of seniority (lower, middle and upper). The relationship was examined by employing Smart PLS 4 in a current study.

The study findings revealed a significant and conspicuous effect of KOL on KWP. The outcomes divulged the fact that KOL has a positive impact on the ECWB, and DCB improves the performance of knowledge workers, resulting in an overall augmentation in the organizational performance of the IT industry.

Presently, there exist a scarcity of substantial empirical studies to thoroughly examine the influence of KOL, ECWB, DCB, KWP and OP in the domain of Chinese IT industry research, particularly in the setting of the pandemic. The study makes a substantial contribution to the extant literature on the topic via empirically examining the association among KOL, KWP and organizational performance, as well as evaluating the mediation mechanism of both employee creative work behavior and digital citizenship behavior.

Employee’s innovative behavior as a team allows the organization to achieve its goals; however, team green creativity requires transformational and entrepreneurial leader support. Therefore, the study explores the impact of green transformational and entrepreneurial leadership on team innovative behavior and green new product development with the mediating role of team green creativity.

A survey was conducted to collect data from 455 employees working in the hospitality industry via a self-administered questionnaire, and hypotheses were analyzed using the partial least squares structural equation modeling PLS-SEM technique using Smart-PLS 4.0.

The results indicate that green transformational and entrepreneurial leadership styles positively and significantly affect team innovative behavior and new green product development performance. Furthermore, findings show that team green creativity partially mediates the relationship between green transformational and entrepreneurial leadership on team innovative behavior, and new green product development performance.

The results of this study provide insights to hospitality professionals pursuing the improvement of team innovative behavior and new green product development performance through team green creativity and leadership styles.

This study is useful for organizations that target new green product development performance and establish higher green innovative behavior cohesively among its team members through these robust leadership styles.

This study is the first attempt to provide a valuable contribution to the growing field of green leadership styles on team innovative behavior and new green product development performance through team green creativity.

Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are produced globally per year. In addition, concrete also accelerates the consumption of natural resources, leading to the depletion of these natural resources. Therefore, this study uses artificial intelligence (AI) to examine the utilization of recycled concrete aggregate (RCA) in concrete.

An extensive database of 583 data points are collected from the literature for predictive modeling. Four machine learning algorithms, namely artificial neural network (ANN), random forest (RF), ridge regression (RR) and least adjacent shrinkage and selection operator (LASSO) regression (LR), in predicting simultaneously concrete compressive and tensile strength were evaluated. The dataset contains 10 independent variables and two dependent variables. Statistical parameters, including coefficient of determination (R²), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE), were employed to assess the accuracy of the algorithms. In addition, K-fold cross-validation was employed to validate the obtained results, and SHapley Additive exPlanations (SHAP) analysis was applied to identify the most sensitive parameters out of the 10 input parameters.

The results indicate that the RF prediction model performance is better and more satisfactory than other algorithms. Furthermore, the ANN algorithm ranks as the second most accurate algorithm. However, RR and LR exhibit poor findings with low accuracy. K-fold cross-validation was successfully applied to validate the obtained results and SHAP analysis indicates that cement content and recycled aggregate percentages are the effective input parameter. Therefore, special attention should be given to sensitive parameters to enhance the concrete performance.

This study uniquely applies AI to optimize the use of RCA in concrete production. By evaluating four machine learning algorithms, ANN, RF, RR and LR on a comprehensive dataset, this study identities the most effective predictive models for concrete compressive and tensile strength. The use of SHAP analysis to determine key input parameters and K-fold cross-validation for result validation adds to the study robustness. The findings highlight the superior performance of the RF model and provide actionable insights into enhancing concrete performance with RCA, contributing to sustainable construction practice.

This study investigates the link between servant leadership and project management effectiveness in developmental projects in non-governmental organisations (NGOs). Further, this study examined the mediating role of conflict resolution and moderating role of organisational culture.

A three-wave survey of 288 non-governmental organisation (NGO) employees was used to evaluate the hypotheses. Hierarchical regression analysis and Hayes' PROCESS macro technique were used for data analysis.

In this study, servant leadership positively affects employee project management effectiveness in developmental projects in NGOs, and conflict resolution mediates the relationship. Furthermore, the results show that organisational culture moderates the positive relationship between servant leadership and employee project management effectiveness. Moreover, the authors investigated the hypotheses via a moderation mediation model. The strength of the mediated link between servant leadership and project management effectiveness (via conflict resolution) depends on organisational culture strength.

Leaders that practice servant leadership care for their employees genuinely and serve them by allowing them to make their own decisions. Every organisation may benefit from this leadership style since it encourages project effectiveness

New empirical data from this study suggests that servant leadership positively and substantially affects employee project management effectiveness in developmental projects in NGOs.

The purpose of this study is to assess the incorporation of fiber reinforced polymer (FRP) bars in concrete as a reinforcement enhances the corrosion resistance in a concrete structure. However, FRP bars are not practically used due to a lack of standard codes. Various codes, including ACI-440-17 and CSA S806-12, have been established to provide guidelines for the incorporation of FRP bars in concrete as reinforcement. The application of these codes may result in over-reinforcement. Therefore, this research presents the use of a machine learning approach to predict the accurate flexural strength of the FRP beams with the use of 408 experimental results.

In this research, the input parameters are the width of the beam, effective depth of the beam, concrete compressive strength, FRP bar elastic modulus and FRP bar tensile strength. Three machine learning algorithms, namely, gene expression programming, multi-expression programming and artificial neural networks, are developed. The accuracy of the developed models was judged by R², root means squared and mean absolute error. Finally, the study conducts prismatic analysis by considering different parameters. including depth and percentage of bottom reinforcement.

The artificial neural networks model result is the most accurate prediction (99%), with the lowest root mean squared error (2.66) and lowest mean absolute error (1.38). In addition, the result of SHapley Additive exPlanation analysis depicts that the effective depth and percentage of bottom reinforcement are the most influential parameters of FRP bars reinforced concrete beam. Therefore, the findings recommend that special attention should be given to the effective depth and percentage of bottom reinforcement.

Previous studies revealed that the flexural strength of concrete beams reinforced with FRP bars is significantly influenced by factors such as beam width, effective depth, concrete compressive strength, FRP bars’ elastic modulus and FRP bar tensile strength. Therefore, a substantial database comprising 408 experimental results considered for these parameters was compiled, and a simple and reliable model was proposed. The model developed in this research was compared with traditional codes, and it can be noted that the model developed in this study is much more accurate than the traditional codes.

A novel type of heat transfer fluid known as hybrid nanofluids is used to improve the efficiency of heat exchangers. It is observed from literature evidence that hybrid nanofluids outperform single nanofluids in terms of thermal performance. This study aims to address the stagnation point flow induced by Williamson hybrid nanofluids across a vertical plate. This fluid is drenched under the influence of mixed convection in a Darcy–Forchheimer porous medium with heat source/sink and entropy generation.

By applying the proper similarity transformation, the partial differential equations that represent the leading model of the flow problem are reduced to ordinary differential equations. For the boundary value problem of the fourth-order code (bvp4c), a built-in MATLAB finite difference code is used to tackle the flow problem and carry out the dual numerical solutions.

The shear stress decreases, but the rate of heat transfer increases because of their greater influence on the permeability parameter and Weissenberg number for both solutions. The ability of hybrid nanofluids to strengthen heat transfer with the incorporation of a porous medium is demonstrated in this study.

The findings may be highly beneficial in raising the energy efficiency of thermal systems.

The originality of the research lies in the investigation of the Darcy–Forchheimer stagnation point flow of a Williamson hybrid nanofluid across a vertical plate, considering buoyancy forces, which introduces another layer of complexity to the flow problem. This aspect has not been extensively studied before. The results are verified and offer a very favorable balance with the acknowledged papers.