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This research was carried out with the purpose to empirically test the model to explain the procedures concerned with the translation of social capital (SC) into strategic renewal (SR) of SMEs in developing economy like Pakistan. This procedure involves the mediating role of firms' strategic agility (SA) as well as the contingent effects of firms' absorptive capacity (AC).

This study employed a cross-sectional design to evaluate the hypothesized model. To validate the moderated mediation model, data was collected from 519 CEOs, owners, finance managers and managing directors of 123 manufacturing units dealing in agricultural machinery (32 units), automobile accessories (16 units), pharmaceutical instrument (11 units), electrical equipment (25 units), IT related accessories (21 units) and garments (18 units).

The findings of the study confirm a positive association between SC on SR. Moreover, results also validate the mediating role of SA in the relationship between SC and SR. In addition, the moderating role of AC is also confirmed and presented this construct as a catalyst in the relationship between SC and SR.

This research provides new endeavors for strategic management and strategic entrepreneurship literature by focusing on distinctive resources such as SC with its different facets. Therefore, it provides a new dimension and a roadmap that will be beneficial to the achievement of the objectives of SR.

The findings of this research have contributed to the streams of strategic management perspective by emphasizing upon the mediating mechanism how SC can be transformed into SR of SMEs through SA. Findings of the research also contribute to understand the moderating role of AC, and how its association with SC and SA augments the effects on SR of firms.

The study was initiated to test the relationship of social media site addiction on librarians' performance. Furthermore, the study also tested the mediating role of task distraction and moderating role of effective self-control in aforesaid relationship.

This was an empirical study, and data for the research were collected through a standardized questionnaire from 503 librarians who were having Facebook accounts and are questionnaire developed through “Google Forms” and the link of the questionnaire was distributed using Facebook groups. Data was analyzed using descriptive analysis, correlation, Baron and Kenny's approach, and Normal Test Theory.

Results indicate that social media addiction is an important factor for that is reducing librarians' performance. At the same time task distraction also adds to negative impact of social media addiction on librarians' performance. However, effective self-control can reduce the negative impact of social media addiction on their performance.

This research has some important theoretical as well as practical implications for librarians, library management, and well as for policy makers and government.

Social media is commonly used for communication but when it becomes addiction, it can reduce the employees' performance. Most of existing researched focused on positive aspects of social media; only few researches explored the negative impacts of social media. The proposed relationship was never tested on librarians. This study filled this literature gap and proposed as well as empirically tested a model for evaluating negative impact of social media on librarians' performance.

The objective of this study is to evaluate the key issues that how social capital augments the initiation of strategic renewal through the mediating role of entrepreneurial orientation and the moderating role of organizational flexibility. In the context of Small and Medium Enterprises (SMEs) of developing economies, the study developed and tested the theoretical model of strategic renewal for analyzing its major outputs.

This study utilized cross-sectional design and employ quantitative approach. The data were collected from the owner, managers and executive directors of pharmaceutical SMEs of Pakistan. The study used statistical analysis of correlation and regression for the analysis of data.

The study discovered that entrepreneurial orientation mediates the positive relationship of social capital and strategic renewal. Moreover, high organizational flexibility strengthens the association between social capital and strategic renewal of SMEs.

This research contributes to the body of knowledge by providing empirical evidence that how to thrive the mechanism of strategic renewal. The study further provides understanding of the effects of organizational social capital, entrepreneurial orientation and organizational flexibility on strategic renewal.

This research aims to concentrate on the important concern that how social capital (SC) influences business model innovation (BMI) in the course of the mediating role of organizational learning capabilities (OLC) and the moderating role of entrepreneurial orientation (EO). In the context of small and medium enterprises (SMEs), this study empirically tested a theoretical model of BMI to advocate a mechanism for the analysis of its significant determinants.

In order to achieve the objective of the research, survey method was utilized, and data were collected from 521 CEOs, MDs and the owners of ICT sector SMEs. Correlation, causal step approach and regression analysis were used to test the proposed model.

Finding of the research advocates that OLC mediate the relationship between SC and BMI. In addition, stronger EO augments the association between OLC and BMI.

The study adds to the literature by providing insights regarding the impact of SC, OLC and EO on BMI of small firms.

This research enriches the existing knowledge by testing a mediating role of OLC between SC-BMI link and, therefore, makes an important addition to the existing knowledge in the context of SMEs by concentrating on the relationship between SC, OLC, BMI and EO.

Over the last few decades, electronic banking has been used widely to manage financial transactions worldwide. More recently electronic wallet (e-wallet) banking has been identified as an innovative mode of e-payment and enhances e-banking customer experience. Although e-wallet banking service is more secure, fast, convenient and cost effective, compared to conventional web-based banking, adoption of e-wallet application is limited among e-banking consumers. To address this issue, the current study has conceptualized task technology fit (TTF) model, diffusion of innovation (DOI) theory and protection motivation theory towards adoption of e-wallet service. Moreover, pandemic risk is studied as moderating factor between the relationship of e-wallet and use of e-wallet banking among banking consumers.

The research design of this study is based on positivism research paradigm. This study is cross-sectional and used deductive level of theory to formulate hypotheses. Research survey was conducted towards e-banking users. For statistical findings research framework is tested with 280 numerical responses. Data are estimated through partial least square structural equation modeling (PLS-SEM) approach.

Statistical results demonstrates that collectively factors underpinned protection motivation theory, TTF and DOI have shown large variance R² 65.7% in adoption of e-wallet. The effect size f² analysis has revealed that compatibility is one of the most influential factors in determining individual behavior to adopt e-wallet. Similarly, Geisser and Stone Q² analysis has disclosed substantial predictive power to predict adoption and use of e-wallet service.

Theoretically, this study integrates protection motivation theory, DOI theory and TTF model toward adoption of e-wallet service and hence contributes to information system literature. To practice this, research has suggested that factors such as pandemic risk, perceived severity and compatibility are most influential factors and hence need policy makers' attention to boost e-wallet adoption.

This study is original as the study develops an integrative research model to investigate e-banking user behavior to adopt of e-wallet service. Moreover, pandemic risk is tested as moderating factor between adoption and use of e-wallet which, in turn, enhance the value of this study and directs how to deal with existing and future pandemic crisis.

The purpose of this study is to introduce the reproducing kernel algorithm for treating classes of time-fractional partial differential equations subject to Robin boundary conditions with parameters derivative arising in fluid flows, fluid dynamics, groundwater hydrology, conservation of energy, heat conduction and electric circuit.

The method provides appropriate representation of the solutions in convergent series formula with accurately computable components. This representation is given in the W(Ω) and H(Ω) inner product spaces, while the computation of the required grid points relies on the R_(y,s) (x, t) and r_(y,s) (x, t) reproducing kernel functions.

Numerical simulation with different order derivatives degree is done including linear and nonlinear terms that are acquired by interrupting the n-term of the exact solutions. Computational results showed that the proposed algorithm is competitive in terms of the quality of the solutions found and is very valid for solving such time-fractional models.

Future work includes the application of the reproducing kernel algorithm to highly nonlinear time-fractional partial differential equations such as those arising in single and multiphase flows. The results will be published in forthcoming papers.

The study included a description of fundamental reproducing kernel algorithm and the concepts of convergence, and error behavior for the reproducing kernel algorithm solvers. Results obtained by the proposed algorithm are found to outperform in terms of accuracy, generality and applicability.

Developing analytical and numerical methods for the solutions of time-fractional partial differential equations is a very important task owing to their practical interest.

This study, for the first time, presents reproducing kernel algorithm for obtaining the numerical solutions of some certain classes of Robin time-fractional partial differential equations. An efficient construction is provided to obtain the numerical solutions for the equations, along with an existence proof of the exact solutions based upon the reproducing kernel theory.

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.