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The study aims to investigate the effect of corruption and crime on the investments by firms in emerging economies (EEs).

The study adopts the generalised methods of moments (GMM) estimator and data across 57 EEs.

The study shows that crime management, corruption and external quality assurance drive-up investments. Additionally, investments decline with firm age and crime incidence. Corruption and crime managements increase investments by exporting firms more than non-exporting firms investments. Also, external auditor services benefit investments by large firms more than small-medium firms.

There is a need for EEs to implement policies that will curtail corruption and create a level playing field and sustainable firm growth. EEs firms must be innovative to expand their productive investments and grow over time. Also, EEs firms should seek external quality certification, invest in internal security and monitor goods in transit.

Responding to the continuing separation of participants and researchers in LIS participatory research, a new methodology is proposed: action partnership research design (APRD). It is asserted that APRD can mitigate or remove the hierarchical structures often inherent in the research process, thus allowing for equal contribution from all.

Building on the bonded design (BD) methodology and informed by a scoping literature review conducted by the same authors, APRD is a human-centered research approach with the goal of empowering and valuing community partnerships. APRD originates from research investigating the use of participatory design methods to foster collaboration between two potentially disparate groups, firstly with adult researchers/designers and elementary school children, and secondly with university faculty and IT professionals.

To achieve this goal, in addition to BD techniques, APRD draws inspiration from elements of indigenous and decolonization research methodologies, particularly those with an emphasis on destabilizing power hierarchies and involving research participants as full partners.

APRD, which emerged from findings from previous participatory design studies, especially those of BD, is based on the premise of partnership, recognizing that each member of a design team, whether researcher or participant/user, has unique expertise to contribute. By considering participants/users as full research partners, APRD aims to flatten the hierarchies exhibited in some LIS participatory research methodologies, where participants are treated more like research subjects than partners.

This paper aims to synthesise the latest literature on supply chain operations of offsite manufacturing in the construction industry to identify and evaluate the uncertainties at each stage of the offsite construction supply chain (OSC-SC) to compile contributions to knowledge and thereby determine the future research directions to improve supply chain resilience (SCR).

The study was conducted as a systematic literature review. In total, 99 peer-reviewed journal papers published between 2015 and mid-2022 were shortlisted and analysed through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

The bibliometric analysis revealed that the research focusing on supply chain issues and developing best practices in offsite construction adopt case study approaches to investigate the research problems comprehensively. The content analysis revealed the lack of up-to-date knowledge in the construction workforce regarding OSC; low preparedness for the changes brought by the SC uncertainties; the lack of a proper procurement model for OSC; lack of end-to-end visibility of the supply chain to identify uncertainties and lack of national or government standards on OSC-SC, as some of the key problems instigating the identified the uncertainties.

This study clarifies the current knowledge by systematically presenting uncertainties at each stage of the OSC-SC. Moreover, it provides a framework and proposes that future research should focus specifically on individual/team, organisational, supply chain/network and sector/national/supranational levels to improve SCR.

Farmers in India are hesitant to adopt organic farming (OF) despite high demand for organic products and favorable policy measures to encourage the practice. Therefore, this study aims to assess the OF adoption barriers faced by Indian farmers using a systematic method of multi-criteria decision making (MCDM).

The authors explored eighteen barriers to OF adoption by conducting a literature survey and discussion with experts on OF. Then the authors used a combined method of Grey Decision Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) methodology to rank the barriers and analyze their interactions.

The analysis reveals that “Lack of knowledge and information,” “lack of financial capacity of farmers’ and “lack of institutional support” are the cause (independent) barriers that significantly impact other barriers. The top three effect (dependent) barriers are “lack of availability of organic inputs,” “personal characteristics such as age, attitudes and beliefs” and “lack of premium pricing,” which are affected by the other barriers.

This research work will help the decision makers understand the barriers to OF adoption in India and their interrelationships. The proposed framework enables them to focus on the high-priority independent barriers, which will subsequently impact the other dependent barriers.

Previous research on OF adoption barriers lacked a multifaceted scientific approach, which is necessary because OF is a complex system and needs a thorough investigation to assess the interaction between the barriers. The research attempts to fill this gap and addresses the complex nature of adoption barriers.

This study assesses the relevance of foreign aid to the incidence of capital flight and unemployment in 20 countries in sub-Saharan Africa.

The study is for the period 1996–2018, and the empirical evidence is based on interactive quantile regressions in order to assess the nexuses throughout the conditional distribution of the unemployment outcome variable.

From the findings, capital flight has a positive unconditional incidence on unemployment, while foreign aid dampens the underlying positive unconditional nexus. Moreover, in order for the positive incidence of capital flight to be completely dampened, foreign aid thresholds of 2.230 and 3.964 (% of GDP) are needed at the 10th and 25th quantiles, respectively, of the conditional distribution of unemployment. It follows that the relevance of foreign aid in crowding out the unfavourable incidence of capital flight on unemployment is significantly apparent only in the lowest quantiles or countries with below-median levels of unemployment. The policy implications are discussed.

The study complements the extant literature by assessing the importance of development assistance in how capital flight affects unemployment in sub-Saharan Africa.

The role institutional quality plays in the rising pace of globalization and its associated health effects remain unclear in the literature. This study, therefore, empirically examined the moderating role of institutional quality on the globalization-health outcomes nexus in Nigeria, a country with a relatively weak health system.

The study employed Dynamic Ordinary Least Square (DOLS) to estimate the empirical models. The Fully Modified Ordinary Least Square (FMOLS) and Canonical Cointegration Regression (CCR) techniques were thereafter used to check the consistency and robustness of our results. Annual time-series data spanning from 1984 to 2020 were sourced from the World Development Indicator, KOF Globalization Index, International Countries Risk Guide (ICRG) and Central Bank of Nigeria Statistical Bulletin databases.

The results revealed that overall globalization and its three dimensional components (economic, political and social globalization) adversely affect life expectancy in their separate models, but increased life expectancy significantly after their interaction with government effectiveness. Also, real GDP, health aids, government recurrent health expenditure are other determinants of life expectancy in Nigeria.

The Nigerian government should put in place appropriate mechanisms directed toward building and sustaining government effectiveness. This will help mitigate the negative effects of globalization and utilize its net positive benefits to improve life expectancy in Nigeria.

The research is the first to comprehensively examine the moderating impact of institutional quality on the nexus between overall globalization as well as its three dimensional components (economic, political and social) on health outcomes in Nigeria.

Compressing the schedule by using overlapping activities is a commonly adopted approach for accelerating projects. However, this approach might channel a variety of risks into the construction processes. Risks imply waste; still, evaluating the effects of using overlapping activities on schedule quality has been a looming gap in construction research. Therefore, this paper aims to study the quality of overlapping in terms of emerging waste and to demarcate the boundaries of the overlapping envelope.

This study presents a method for assessing the consequences of implementing overlapping activities in a schedule on two types of waste namely waiting time and variation gap. A critical path method (CPM) network including eleven activities is modeled stochastically where the durations of individual activities are sampled as beta-distributions. Using program evaluation and review technique (PERT) assumptions to calculate the schedule dates, the network is simulated for various amounts of overlapping and the corresponding waste is quantified each time.

Results show that not only the returns on overlapping are diminishing after a certain overlap percentage, but also waste in the production system increases. Particularly, results reveal that compressing the schedule leads to a decrease in variation gaps, but at the same time, it leads to a larger increase in waiting times, which creates more waste.

The presented study shows through simulation how overlapping activities affects productivity by identifying wastes. It shows that despite the apparent gains, overlaps should be used with caution, and while considering the side-effects of increased waste which introduces a need for increased managerial awareness.

This study aims to examine how the effect of gender on entrepreneurial growth aspirations is moderated differently by individual resources (human and financial capital) compared to those within the social environment (availability of entrepreneurial knowledge and role models).

A multilevel estimator is used to investigate the determinants of growth aspirations of owners-managers of nascent start-ups. The Global Entrepreneurship Monitor database is employed, covering the period 2007–2019, with 99,000 useable cases drawn from 95 countries.

The results suggest that individual financial resources and human capital have positive effects on entrepreneurial growth aspirations; yet these effects are weaker for female entrepreneurs relative to males. In contrast, the impact of the availability of entrepreneurial social knowledge and role models on their growth aspirations is more positive than for male entrepreneurs.

This study offers a novel insight into entrepreneurial growth ambition, as it utilises a global perspective to scrutinise whether individual and social resources contribute differently to male versus female growth-aspirations, employing a multilevel approach. It also integrates insights from the resource-based view and from the relevant business literature on entrepreneurs’ gender to develop theoretical explanations.

The purpose of this paper was to study the possibility of using smartphone roughness measurements for developing pavement roughness regression models as a function of pavement age, traffic loading and traffic volume variables. Also, the effects of patching and pavement distresses on pavement roughness were investigated. The work focused on establishing pavement roughness prediction models and applying these models to pavement management systems (PMS) to help decision-makers choose the best maintenance and rehabilitation (M&R) options by using cost-effective methods.

Signal processing techniques including filtering and processing techniques were used to obtain the International Roughness Index (IRI) from raw acceleration data collected from smartphone accelerometer sensors. The obtained IRI values were inputted as a dependent variable in analytical regression models as well as several independent variables with proper transformations.

According to the study results, several regression models were developed with a big variation in the coefficients of determination (R²). However, the best models included pavement age, accumulated traffic volume (∑TV) and construction quality factor (CQF) with R² equal to 0.63. It was also found that the effects of pavement distresses and patching was significant at a-level < 0.05. The patching effect on pavement roughness was found higher than the effect of other pavement distresses.

The presented results and methods in this paper could be used in the future predictions of pavement roughness and help the decision-makers to estimate M&R needs. The work focused on establishing IRI prediction models and applying these models to the PMS to help decision-makers choose the best M & R options.

To develop sound pavement roughness models, it is essential to collect roughness data using automated procedures. However, applying these procedures in developing countries faces several difficulties such as the high price and operation costs of roughness equipment and lack of technical experience. The advantage of using IRI values taken from smartphones is that the roughness evaluation survey may be expanded to cover the full road network at a cheaper cost than with automated instruments. Therefore, if the roughness survey covers more roads, the prediction model’s accuracy will be improved.

The United Nations member countries adopted a set of 17 sustainable development goals (SDGs) to achieve a better and more sustainable future for all. It encourages the use of sustainable practices during new product development (NPD). Competitiveness has put pressure on organizations to maintain their market share and look for new approaches related to NPD. The current study aims to focus on creating a framework that can help to achieve the SDGs by adopting agile new product development (ANPD) practices and Industry 4.0 technologies.

From the literature, various ANPD practices, Industry 4.0 technologies, performance metrics, their interconnection and their contribution toward achieving SDGs are extracted. The weights of selected Industry 4.0–ANPD practices are computed by robust best worst method (RBWM), and the Fuzzy-VIKOR method is used to rank the selected performance metrics. To test the robustness of the developed framework, sensitivity analysis is also performed.

The results show that among the various Industry 4.0–ANPD practices “Multi-skilled employees” have the highest weight followed by “Customer requirement analysis and prioritization.” Whereas for performance metrics, “The number of innovative products launched per year” is ranked first, with the “Average time between two launches” at second place.

This research contributes to the adoption of ANPD practices and Industry 4.0 technologies for the achievement of the business SDGs. The shortlisted Industry 4.0–ANPD practices will help in resolving the social and environmental issues. The set of performance metrics will help practitioners and managers to evaluate the performance of ANPD in the context of business SDGs.

This study adds to the understanding related to Industry 4.0–ANPD practices adoption. And to the best of the authors’ knowledge, it is believed that no similar work has been done previously and by using industry insights into technology components, this work contributes to valuable insights into the subject.