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Culture plays a vital role in shaping individuals’ intentions and behaviour. Influence of cultural values on entrepreneurship has been acknowledged widely by academics and practitioners. However, little in terms of empirical results is known. Thus, the purpose of this paper is to investigate the effect of cultural values on entrepreneurial intentions (EI) of Pakistani students.

Cultural values of individualism and collectivism were incorporated into the theory of planned behaviour (TPB). Smart-PLS software was used to run a structural equation modelling (SEM) technique to analyse the data.

SEM results showed that attitudes towards entrepreneurship and perceived behavioural controls (PBC) mediated the relationship between individualism and EI while subjective norms (SN) mediated the relationship between collectivism and EI.

The study confirms the applicability of the TPB for understanding the EI in a collectivist culture. Additionally, findings of this study displayed that external factors, such as cultural values, can impact EI through SN, attitude and PBC. Incorporation of cultural values in TPB contributed to the understating of antecedents of EI.

This paper aims to investigate the role of nature and nurture in students’ entrepreneurial intention (EIs). In doing so, the study examines the relationship between prenatal testosterone exposure (2D:4D), risk-taking propensity, entrepreneurial self-efficacy and EIs. Moreover, the moderating role of entrepreneurial education between entrepreneurial self-efficacy and EI is also investigated.

In line with previous studies on EI, the authors tested hypotheses based on quantitative data obtained from university students.

Data were analyzed with the help of the structural equation modeling technique, and the results revealed that all the hypothesized relationships were supported.

The field of entrepreneurship has become an attractive area of research for practitioners and academics. One tinted area of research in entrepreneurship is the investigation of EI because it is a good predictor of entrepreneurial behavior. Several antecedents of EIs have been recognized in the literature ranging from personality traits to environmental factors. However, less is known about the role of biology in entrepreneurship. Incorporating biological factors in the field of entrepreneurship appears to be theoretically viable and sound. Thus, this study investigates the effect of biological factors in the presence of psychological factors on EIs, which is a unique contribution to the literature on entrepreneurship.

Academic rankings are facing various issues, including the use of data sources that are not publicly verifiable, subjective parameters, a narrow focus on research productivity and regional biases and so forth. This research work is intended to enhance creditability of the ranking process by using the objective indicators based on publicly verifiable data sources.

The proposed ranking methodology – OpenRank – drives the objective indicators from two well-known publicly verifiable data repositories: the ArnetMiner and DBpedia.

The resultant academic ranking reflects common tendencies of the international academic rankings published by the Shanghai Ranking Consultancy (SRC), Quacquarelli Symonds (QS) and Times Higher Education (THE). Evaluation of the proposed methodology advocates its effectiveness and quick reproducibility with low cost of data collection.

Implementation of the OpenRank methodology faced the issue of availability of the quality data. In future, accuracy of the academic rankings can be improved further by employing more relevant public data sources like the Microsoft Academic Graph, millions of graduate's profiles available in the LinkedIn repositories and the bibliographic data maintained by Association for Computing Machinery and Scopus and so forth.

The suggested use of open data sources would offer new dimensions to evaluate academic performance of the higher education institutions (HEIs) and having comprehensive understanding of the catalyst factors in the higher education.

The research work highlighted the need of a purposely built, publicly verifiable electronic data source for performance evaluation of the global HEIs. Availability of such a global database would help in better academic planning, monitoring and analysis. Definitely, more transparent, reliable and less controversial academic rankings can be generated by employing the aspired data source.

We suggested a satisfying solution for improvement of the HEIs' ranking process by making the following contributions: (1) enhancing creditability of the ranking results by merely employing the objective performance indicators extracted from the publicly verifiable data sources, (2) developing an academic ranking methodology based on the objective indicators using two well-known data repositories, the DBpedia and ArnetMiner and (3) demonstrating effectiveness of the proposed ranking methodology on the real data sources.

The purpose of this paper is to investigate the relationship between individual characteristics and knowledge sharing (KS) in higher education institutes (HEIs) of Pakistan.

The study used a quantitative research methodology. The empirical data consisted of 370 responses from the academic staff of six HEIs of Pakistan.

The findings revealed a significant impact of dispositional factors on KS. More precisely, extroversion, openness to experience, agreeableness, emotional intelligence and religiosity were positively associated with KS, while neuroticism was found to be negatively associated with KS.

This micro-level model of KS has some potential implications for the decision makers in the context of HEIs. To enhance the KS in HEIs, the decision makers should take the findings of this study into consideration while hiring the academicians in the universities. The decision makers should give priority to the potential candidates who have a higher level of extroversion, openness and agreeableness. Further, while making hiring and other job-related strategies, religiosity and emotional intelligence of the potential candidates should not be ignored.

The paper tested a micro-level model of KS in HEIs and contributed to the body of knowledge by jointly investigating the relationship between religiosity, emotional intelligence, personality traits and KS. To the best of researchers’ knowledge, no study has been conducted, so far, which tested these variables jointly. Thus, the present research filled this knowledge gap.

An attempt is made to study magnetohydrodynamic viscous fluid impinging orthogonally toward a stagnation point on a vertical surface lubricated with power law fluid. It has been assumed that the surface temperature varies linearly with the distance from the stagnation point. The problem is governed by system of partial differential equations for both the base fluid and the lubricant. The continuity of velocity and shear stress is assumed at the interface layer between the base fluid and the lubricant. Dimensionless variables are introduced to transform original problem into ordinary differential equations. An implicit finite-difference scheme known as the Keller-Box method is implemented to obtain the numerical solutions. The influence of various important parameters is presented in the form of graphs and tables. The limiting cases for full and no-slip conditions are deduced from the present solutions. A comparison of the present results with the existing results in the special case validates the obtained numerical solutions. The purpose of this study is to see the behaviour of flow characteristics in the presence of lubrication.

The authors’ problem is governed by system of partial differential equations for both the base fluid and the lubricant. Dimensionless variables are introduced to transform original problem into ordinary differential equations. The obtained ordinary differential equation along with boundary conditions are highly nonlinear and coupled. An implicit finite-difference scheme known as the Keller-Box method is implemented to obtain the numerical solutions.

Some findings of this study are that the lubricant increases the velocity of the base fluid inside the boundary layer. In the case of full slip, the effects of viscosity are suppressed by the lubricant. The temperature of the base fluid decreases by increase in lubrication on the surface. By increasing the slip on the surface, the skin friction decreases and local Nusselt number increases, but the rate of increase or decrease is less in magnitude for the case of opposing flow. The similarity solutions only exist for n = 1/2. A non-similar solution is obtained for the other values of the power-law index n.

The study of flow phenomenon over a lubricated surface has important applications in machinery components such as fluid bearings and mechanical seals. Coating is another major application of lubrication including the preparation of thin films, printing, painting, etc. The authors hope that the current study will provide the roadmap for the future studies in this direction.

This study empirically examines the impact of some domestic as well as global factors such as trade openness (TO), money supply (MS), exchange rate, global oil prices (GOPs) and interest rate (IR) on inflation.

This study deploys a quantitative method considering 30 years of data (1991–2020) from four South Asian countries, namely, Sri Lanka, Pakistan, Bangladesh and India. To determine the potential impact of different factors on inflation, this study applies the panel analysis of the system generalized method of moments (SGMM).

This study empirically finds that TO, MS, exchange rate and GOPs have a positive impact on inflation, while IR and the structural adjustment program (SAP) have a negative impact on inflation. Out of the various determinants considered in this study, TO, exchange rate and the SAP are insignificant, while the rest of the variables are significant and consistent with previous studies.

This study informs policymakers about maintaining price stability and fostering economic growth in South Asian nations. It breaks new ground as the first empirical examination of the International Monetary Fund (IMF)’s SAP impact on inflation in the region.

This study tries to find out whether the SAP of the IMF is responsible for inflation in South Asian countries. It gives renewed attention to the causality of inflation from the perspective of countries receiving loans from donors, especially the IMF.

Presentation of the different industrial carbon linkages of India. The purpose of this paper is to understand the direct and indirect impact of these industrial linkages.

This study uses a hypothetical extraction method with its various extensions. Under this method, different carbon linkages of a block are removed from the economy, and the effects of carbon linkages are determined by the difference between the original and the post-removal values. Energy and non-energy carbon linkages are also estimated.

“Electricity, gas and water supply (EGW)” at 655.61 Mt and 648.74 Mt had the highest total and forward linkages. “manufacturing and recycling” at 231.48 Mt had the highest backward linkage. High carbon-intensive blocks of “EGW” plus “mining and quarrying” were net emitters, while others were net absorbers. “Fuel and chemicals” at 0.08 Mt had almost neutral status. Hard coal was the main source of direct and indirect emissions.

Net emitting and key net forward blocks should reduce direct emission intensities. India should use its huge geographical potential for industrial accessibility to cheaper alternative energy. This alongside with technology/process improvements catalyzed by policy tools can help in mitigation efforts. Next, key net-backward blocks such as construction through intermediate purchases significantly stimulate emissions from other blocks. Tailored mitigation policies are needed in this regard.

By developing an understanding of India’s industrial carbon links, this study can guide policymakers. In addition, the paper lays out the framework for estimating energy and non-energy-based industrial carbon links.

Cost overrun is inherent to project chaos, which is one of the key drivers of project failure. The purpose of this paper is to explore the critical elements of complexity-risk interdependency for cost-chaos in the construction management domain by utilizing a multi-criteria decision model.

A total of 12 complexity and 60 risk attributes are initially identified from the literature and using expert’s judgements. For the development of a structured hierarchy of key complexity and risk drivers, a real-time Delphi process is adopted for recording and evaluating the responses from experts. Afterwards, a pair-wise comparison using analytical network processing is performed to measure complexity-risk interdependencies against cost alternatives.

The findings of the integrated priority decision index (IPDI) suggest that uncertainties related to contingency and escalation costs are the main sources of cost overrun in project drift, along with the key elements such as “the use of innovative technology,” “multiple contracts,” “low advance payment,” “change in design,” “unclear specifications” and “the lack of experience” appear to be more significant to chaos in complexity-risk interdependency network.

This study did not address the uncertainty and vulnerability exit in the judgment process, therefore, this framework can be extended using fuzzy logic to better evaluate the significance of cost-chaos drivers.

These results may assist the management of cost overrun to avoid chaos in a project. The proposed model can be applied within project risk management practices to make better-informed technical decisions in the early phases of the project life cycle where uncertainty is high.

This research addresses the importance of cost overruns as a source of project chaos in dynamic systems where projects reach the edge of chaos and progress stops. A new IPDI index contributes toward evaluating the severity of complexity and risk and their interdependencies which create cost-chaos in infrastructure transport projects.

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.

This study aims to identify the developer’s objectives, current state-of-the-art techniques, challenges and performance evaluation metrics, and presents outlines of a knowledge-based application programming interfaces (API) recommendation system for the developers. Moreover, the current study intends to classify current state-of-the-art techniques supporting automated API recommendations.

In this study, the authors have performed a systematic literature review of studies, which have been published between the years 2004–2021 to achieve the targeted research objective. Subsequently, the authors performed the analysis of 35 primary studies.

The outcomes of this study are: (1) devising a thematic taxonomy based on the identified developers’ challenges, where mashup-oriented APIs and time-consuming process are frequently encountered challenges by the developers; (2) categorizing current state-of-the-art API recommendation techniques (i.e. clustering techniques, data preprocessing techniques, similarity measurements techniques and ranking techniques); (3) designing a taxonomy based on the identified objectives, where accuracy is the most targeted objective in API recommendation context; (4) identifying a list of evaluation metrics employed to assess the performance of the proposed techniques; (5) performing a SWOT analysis on the selected studies; (6) based on the developer’s challenges, objectives and SWOT analysis, presenting outlines of a recommendation system for the developers and (7) delineating several future research dimensions in API recommendations context.

This study provides complete guidance to the new researcher in the context of API recommendations. Also, the researcher can target these objectives (accuracy, response time, method recommendation, compatibility, user requirement-based API, automatic service recommendation and API location) in the future. Moreover, the developers can overcome the identified challenges (including mashup-oriented API, Time-consuming process, learn how to use the API, integrated problem, API method usage location and limited usage of code) in the future by proposing a framework or recommendation system. Furthermore, the classification of current state-of-the-art API recommendation techniques also helps the researchers who wish to work in the future in the context of API recommendation.

This study not only facilitates the researcher but also facilitates the practitioners in several ways. The current study guides the developer in minimizing the development time in terms of selecting relevant APIs rather than following traditional manual selection. Moreover, this study facilitates integrating APIs in a project. Thus, the recommendation system saves the time for developers, and increases their productivity.

API recommendation remains an active area of research in web and mobile-based applications development. The authors believe that this study acts as a useful tool for the interested researchers and practitioners as it will contribute to the body of knowledge in API recommendations context.