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This study aims to examine the associations between socioeconomic status, types of rigging (pre- polling-day and post-), politics and voting behavior, vote casting and perceptions of rigging in Pakistan’s most recent elections, and attitudes toward electoral integrity.

Data were collected from students at three different universities. In all, 748 units of analysis (488 male and 260 female) recorded their responses by means of a self-structured questionnaire. Linear regression was applied to measure the associations between variables, and the reliability and validity of the scales were tested.

A significant relationship was found between pre-poll rigging, post-poll rigging, politics and voting behavior, socioeconomic characteristics (i.e. age, education, father’s education, background or place of residence and monthly household incomes), the perception of rigging in the last elections and attitudes toward electoral integrity.

Pakistan’s history has been blemished by electoral malpractices during both de facto and de jure regimes. Attention has formerly been paid to either polling-day or post-election rigging. The relationship of electoral integrity with different factors explored in this study have usually been ignored or overlooked. The findings of this study would help policy-makers, youth experts and academicians to reorient their behaviors to strengthen political stability, the rule of law and the continuation of democracy via their participation in the system.

To the researchers’ best knowledge, there has not been a single peer-reviewed study of Pakistan which has explored the associations between the variables examined for this study. The main academic challenge the researchers faced was to find a standardized and contextualized scale or tool to explore how different types of vote-rigging affected attitudes toward electoral integrity. Thus, the structured scales for types of rigging and electoral integrity developed here would be useful for future studies in the field of electoral integrity in democratic countries.

This study investigates the flow and heat transfer in a magnetohydrodynamic (MHD) ternary hybrid nanofluid (HNF), considering the effects of viscous dissipation and radiation.

The transport equations are transformed into nondimensional partial differential equations. The local nonsimilarity (LNS) technique is implemented to truncate nonsimilar dimensionless system. The LNS truncated equation can be treated as ordinary differential equations. The numerical results of the equation are accomplished through the implementation of the bvp4c solver, which leverages the fourth-order three-stage Lobatto IIIa formula as a finite difference scheme.

The findings of a comparative investigation carried out under diverse physical limitations demonstrate that ternary HNFs exhibit remarkably elevated thermal efficiency in contrast to conventional nanofluids.

The LNS approach (Mahesh et al., 2023; Khan et al., 20223; Farooq et al., 2023) that we have proposed is not currently being used to clarify the dynamical issue of HNF via porous media. The LNS method, in conjunction with the bvp4c up to its second truncation level, yields numerical solutions to nonlinear-coupled PDEs. Relevant results of the topic at hand, obtained by adjusting the appropriate parameters, are explained and shown visually via tables and diagrams.

This study aims to investigate how the timing behavior affects the capital structure decisions of South Asian family firms. A strand of literature is available based on the capital structure of firms in general but inconsistent with family businesses framework and not from market timing outlook. This study looks at the issues from the market timing perspectives of both equity and debt market timing.

The sample of the study is the listed family firms of India, Pakistan and Bangladesh. The firm-level data are collected from Thomson Reuters' DataStream and the ownership data collected from the countries' stock exchanges and financial statements of the family firms.

The results show that there is strong support for the market timing in the family firms' capital structure. Moreover, the financial crisis of 2007–2009 surprisingly had a positive effect on the capital structure of South Asian family business.

This study looks at the issues from the market timing perspectives of both equity and debt market timing. It provides evidence for supporting the equity and debt market timing effect on the capital structure and financing decision of family firms. It also addresses the impact of the 2007–2009 financial crisis on the capital structure of family firms.

The purpose of this paper is to identify major macroeconomic factors that enhance foreign direct investment (FDI) for Pakistan through the co‐integration and error correction model over a 28‐year time period, i.e. between 1980 and 2008.

The study employed the Johansen co‐integration technique to estimate the long‐run relationship between the variables, while an error correction model was used to determine the short‐run dynamics of the system.

Finding suggests that FDI has had a significant positive impact on Pakistan's economic growth in the long run. For example, trade liberalization and their interactive terms have a positive effect in the short run, while a negative effect is observed in the long run upon economic growth of Pakistan. The results indicate that due to a low quality of human capital in Pakistan; the direct effect of FDI on economic growth becomes negative.

The study was limited to a few variables, including human capital, trade openness, government size, population and consumer price index, in order to manage robust data analysis.

The authors find that for FDI to be a significant contributor to economic growth in Pakistan, government must focus upon improving physical infrastructure, and quality of human resources.

The study confirms that Pakistan did not enjoy substantial growth benefits from FDI because human capital, trade openness, government size and interactive terms of FDI and per capita income have a negative impact on economic growth. These findings have important policy implications.

The transition from school to higher education is a complex process. Peer mentoring is often used by institutions to facilitate this process. The purpose of this research, which was conducted at a South African university, was to determine whether a peer mentoring programme, which involved a large number of students and a limited number of mentors, could successfully assist students to adapt to the academic and psychosocial demands of university life.

A sequential explanatory mixed method design was implemented. In the first phase, a questionnaire was used to collect data to establish participants' experience of the programme. The findings from the questionnaire were used to inform the qualitative phase, in which the participants' perceptions of the benefits of the mentor programme were further explored by means of group interviews. The qualitative data were analysed using inductive qualitative content analysis.

The results indicate that a structured peer mentoring programme, in which a mentor works with up to 70 mentees in a group setting, can be a useful tool to assist with students' transition to university. The research found that the peer mentoring programme contributed to the students' academic, social and personal integration into the higher education environment.

The perspectives of mentors and faculty were not included. No comparative study with students who did not participate in the programme was conducted.

This research illustrates that it is possible to mentor large groups of disadvantaged and vulnerable students notwithstanding limited resources.

In contrast to the existing literature on peer mentoring in higher education, which focuses on one-on-one or small-group mentoring, this research suggests that peer mentoring of larger groups can also play an important role in assisting students to transition to higher education. The description of the programme and the benefits students derived from it offer other institutions with limited resources some ideas about how a peer mentoring programme can be implemented.

Small farmers, being the primary producers of crops, are the key players in the food supply chain. Yet, they remain the most marginalized in the value chain. The marginalization of small farmers can affect food sustainability. The purpose of this paper is to identify opportunities for bringing more value to small farmers in an agricultural value chain.

This paper makes use of action research, studying the potato value chain, in a developing agricultural country Pakistan. The authors conducted an in-depth study of 37 farmers in four regions, each being a large potato growing ecosystem. The study examined the end-to-end decision-making processes, sources of input (both physical and information), cultivation and sales practices, cost structure, productivity and profitability of the farmers in potato farming.

Large variations exist in the crop yield, cost structure and profitability of farmers within each of and among the four regions due to differences in cultivation practices and approach to sales. There is a significant potential to lower costs, increase yield and enhance overall profitability by using the existing better processes. By addressing the issues faced by small farmers their profits can be potentially doubled. The paper also discusses potential means of recrafting and streamlining the value chain to bring more value to small farmers.

The paper provides a detailed account of how different interventions can increase the value for small farmers. Since the current food supply chain and sustainability are under stress, worldwide, the findings of this study have implications for farmers as well as policy makers.

The literature on streamlining the agricultural value chain and enhancing the share of small farmers is scarce. Improving the value chain and reducing the marginalization of small farmers is an essential step toward increasing food sustainability.

Pakistan has experienced financial liberalization with rapid ups and downs in economic growth due to domestic issues during the last 2 decades. Motivated by inconclusive and conflicting time-driven findings about the performance of the business groups, this study examines the performance of business groups in Pakistan for a relatively long period from 2003 to 2018.

The study uses 3,821 firm-year observations from non-financial firms listed on the Pakistan Stock Exchange (PSX). For the estimation, pooled ordinary least squares (OLS) with industry- and year fixed effects and two-step system generalized methods of moments (GMM) are used.

The study finds that group-affiliated firms outperform independent firms in accounting performance, while underperform in market performance. The outperformance is mainly driven by medium-sized business groups, while underperformance is driven by small and large business groups. Further, the study documents that the underperformance in terms of market performance of firms affiliated with small and large groups is greater before the economic downturn, while outperformance in terms of the accounting measure of firms affiliated with medium-sized groups is greater during the economic downturn. These findings support our time-driven concerns. Overall, the authors' findings are consistent with institutional and transaction cost theories.

Business groups are important channels to reduce market inefficiencies. Business groups may enhance the affiliated firms' resources and resistance capacity through active utilization of the internal capital market, specifically when market conditions are not ideal for affiliates. However, effective utilization of internal capital markets depends on group size. Therefore, investors should deliberate on the size of business groups and diversification within business groups.

The authors extend the literature by providing fresh evidence related to the performance of business groups in the Pakistani context while accounting for the role of the size of business groups.

Tags are used to annotate resources on social media platforms. Most tag recommendation methods use popular tags, but in the case of new resources that are as yet untagged (the cold start problem), popularity-based tag recommendation methods fail to work. The purpose of this paper is to propose a novel model for tag recommendation called multi-feature space latent Dirichlet allocation (MFS-LDA) for cold start problem.

MFS-LDA is a novel latent Dirichlet allocation (LDA)-based model which exploits multiple feature spaces (title, contents, and tags) for recommending tags. Exploiting multiple feature spaces allows MFS-LDA to recommend tags even if data from a feature space is missing (the cold start problem).

Evaluation of a publicly available data set consisting of around 20,000 Wikipedia articles that are tagged on a social bookmarking website shows a significant improvement over existing LDA-based tag recommendation methods.

The originality of MFS-LDA lies in segregation of features for removing bias toward dominant features and in synchronization of multiple feature space for tag recommendation.