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Pakistan ranks third globally in terms of newborn deaths occuring within the first 24 hours of life. With a neonatal mortality rate of 42.0%, it carries the highest burden compared to neighboring countries such as Bangladesh (17%), India (22.7%) and Afghanistan (37%). While there has been a decline in neonatal mortality rates in Pakistan, the pace of this decline is slower than that of other countries in the region. Hence, it is crucial to conduct a comprehensive examination of the risk factors contributing to neonatal mortality in Pakistan over an extended period. This study aims to analyze the trends and determinants of neonatal mortality in Pakistan over three decades, providing valuable insights into this persistent issue.

The study focused on neonatal mortality as the response variable, which is defined as the death of a live-born child within 28 days of birth. Neonates who passed away during this period were categorized as “cases,” while those who survived beyond a specific timeframe were referred to as “noncases.” To conduct a pooled analysis of neonatal mortality, birth records of 39,976 children born in the five years preceding the survey were extracted from four waves (1990–2018) of the Pakistan Demographic and Household Survey. The relationship between risk factors and the response variable was examined using the Cox Proportional Hazard Model. Neonatal mortality rates were calculated through the direct method using the “syncmrates” package in Stata 15.

During the extended period in Pakistan, several critical protective factors against neonatal mortality were identified, including a large family size, improved toilet facilities, middle-aged and educated mothers, female children, singleton live births, large size at birth and longer birth intervals. These factors were found to reduce the risk of neonatal mortality significantly.

This study makes the first attempt to analyze the trends and patterns of potential risk factors associated with neonatal mortality in Pakistan. By examining a large dataset spanning several years, the study provides valuable insights into the factors influencing neonatal mortality.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-09-2022-0604

Farmers in developing countries are used to recycling and purchasing seeds of old and low-yielding varieties, leading to low seed and varietal replacement rates. Seed companies in Nepal have started to conduct traders' meetings (TMs) to promote new rice varieties. This paper aims to assess the effectiveness of this approach in promoting new rice varieties.

The authors assess the effectiveness of TMs by surveying 238 agrodealers from 7 districts of Nepal. The authors used the binary logit model to study the determinants of participation in TM and an instrumental variable approach to estimate the impact of TMs on sales of the promoted rice varieties.

Results indicate that the TM significantly influences traders' knowledge and increases the probability of selling new rice varieties promoted. However, TMs did not significantly increase the overall sales of promoted rice varieties.

The study is based on cross-section data; thus, unobserved fixed effects could not be accounted for. The study finds only one relevant and valid instrumental variable and therefore could not conduct any exogeneity test.

Seed companies in Nepal started to conduct TMs to promote new rice varieties since 2019. However, to the best of the authors’ knowledge, the usefulness of TMs and the impact of these events in changing traders' attitudes toward domestic rice seed varieties or in business performance (annual sales of the promoted varieties) have not been assessed. Therefore, the study findings will help to promote the market-driven seed system and increase the seed replacement rate.

The objective of this study is to investigate the barriers hindering the integration of lean manufacturing (LM) practices within the furniture industry of Bangladesh. The traditional operational paradigms in this sector have posed substantial challenges to the effective implementation of LM. In this study, the barriers of implementing LM in the furniture business are examined, aiming to provide a systematic understanding of the barriers that must be addressed for a successful transition.

The research reveals that “Fragmented Industry Structure,” “Resistance to Lean Practices” and “Inadequate Plant Layout and Maintenance”, emerged as the foremost barriers to LM implementation in the furniture industry. Additionally, “Insufficient Expert Management,” “Limited Technical Resources” and “Lack of Capital Investment” play significant roles.

The outcomes of this study provide valuable insights into the furniture industry, enabling the development of strategies for effective LM implementation. One notable challenge in lean implementation is the tendency to revert to established practices when confronted with barriers. Therefore, this transition necessitates informed guidance and leadership. In addition to addressing these internal challenges, the scope of lean implementation should be broadened.

This study represents one of the initial efforts to systematically identify and assess the barriers to LM implementation within the furniture industry of Bangladesh, contributing to the emerging body of knowledge in this area.

The purpose of this paper through the redundant monitoring unit reflecting the real-time temperature change of the array, an adaptive refresh circuit based on temperature is designed.

This paper proposed a circuit design for temperature-adaptive refresh with a fixed refresh frequency of traditional memory, high refresh power consumption at low temperature and low refresh frequency at high temperature.

Adding a metal oxide semiconductor (MOS) redundancy monitoring unit consistent with the storage unit to the storage bank can monitor the temperature change of the storage bank in real time, so that temperature-based memory adaptive refresh can be implemented.

According to the characteristics that the data holding time of dynamic random access memory storage unit decreases with the increase of temperature, a MOS redundant monitoring unit which is consistent with the storage unit is added to the storage array with the 2T storage unit as the core.

In the last few years, environmental issues have become a matter of survival. In this sense, e-waste management is among the major problems since it may be a way of mitigating mineral depletion. In this context, the literature lacks e-waste supply chain studies that systematically map supply chain challenges and risks concerning material recovery.

Given this context, the authors' paper conducted a systematic literature review (SLR) to build a framework to identify the constructs of e-waste supply chain risk management.

The paper revealed the theoretical relationship between important variables to achieve e-waste supply chain risk management via a circular economy (CE) framework. These variables include reverse logistics (RL), closed-loop supply chains (CLSC), supply chain risk management, supply chain resilience and smart cities.

The literature contributions of this paper are as follows: (1) a complete list of the risks of the e-waste supply chains, (2) the techniques being used to identify, assess and mitigate e-waste supply chain risks and (3) the constructs that form the theoretical framework of e-waste supply chain risk management. In addition, the authors' results address important literature gaps identified by researchers and serve as a guide to implementation.

The purpose of this research is to develop an environmentally friendly antimicrobial dyeing of cotton fabric from the root of Euclea racemosa. Textile phytochemical finishing is in high demand worldwide because of its low toxicity, low pollution, ease of availability, renewability, pharmacological effects and non-carcinogenic properties, as well as its multifunctionality, rapid process stages and potential health benefit.

The cotton fabric was dyed with aqueous extracts of Euclea racemosa root dyes. Dyes were extracted for 20 min at pH 7.43 at room and boiling temperatures with material-to-liquor ratios (MLRs) of 1:5, 1:10, 1:15 and 1:20, altering one variable at a time, and the cotton fabric was colored using a post-mordanting procedure at 50°C with an MLR of 1:20. Using a properly cleaned Petri plate, the colored samples were tested in vitro for antibacterial activity. A spectrophotometer was used to assess color strength and shade depth, as well as wash fastness and annual rubbing fastness tests for both wet and dry.

L* = 36.29, a* = 58.56, b* = 32.46 and K/S = 0.51 were the CIELAB values for dye extracted at boiling temperature. L* = 47.14, a* = 42.23, b* = 49.61 and K/S = 0.38 were the CIELAB values for dye extracted at room temperature. The wash and rubbing fastness of the dyed samples were outstanding and the dyed cotton fabrics were found antibacterial against Gram-negative bacteria Escherichia coli.

Dyes derived from the E. racemosa root could be used to develop a new antibacterial cotton fabric dye.

This study attempts to assess the role that institutional quality (IQ) plays in influencing inflows and outflows of Foreign Direct Investment (FDI) for BRICS nations as burgeoning FDI is flowing into and out of these countries. Moreover, this paper explores the impact of individual governance indicators separately on the FDI flows.

The study analyses this nexus for these emerging economies for the period 1996–2019 using autoregressive distributed lag technique.

The study indicates a significant and positive coefficient for IQ in India and South Africa, suggesting that improving IQ would enhance the IFDI. However, for outward FDI (OFDI)–IQ linkage, the results show a negatively significant impact of IQ on OFDI for Brazil and Russia. Additionally, the authors observe control of corruption as a significant institutional component for attracting inward FDI for Brazil, India and South Africa, whereas it is an insignificant factor for Russia and China. Further, the authors notably find that upgrading the governance indicators will decrease the level of OFDI for Brazil, Russia, China and South Africa. On the contrary, findings suggest that improving the IQ will foster the OFDI for India.

This study uses time-series analysis instead of cross-country analysis (used extensively in literature), avoiding heterogeneity. Further, this study explores the IFDI–IQ link for BRICS nations, which are captivating a significant chunk of IFDI, and still not given much attention in the extant literature. Moreover, the authors identify the impact of IQ on the OFDI, neglected by the existing studies.

This study aims to examine the links between carbon emissions, electric vehicles, economic growth, energy use, and urbanisation in 15 countries from 2010 to 2020.

This study adopts seminal panel methods of moments quantile regression with fixed effects to trace the distributional aspect of the relationship. The reliability of methods is confirmed via fully modified ordinary least squares coefficients.

This study reveals that fossil fuel use, economic activity, and urbanisation negatively impact environmental quality, whereas renewable energy sources have a significant positive long-term effect on environmental quality in the selected panel of countries.

The main limitation of this study is the generalisability of the findings, as the study is confined to a limited number of countries, and focuses on non-renewable and renewable energy sources.

Finally, this study proposes several policy recommendations for decision-makers and policymakers in the 15 nations to address climate change, boost sales of electric vehicles, and increase the use of renewable energy sources.

This study calls for a comprehensive transition towards green energy in the transportation sector, enhancing economic growth, fostering employment opportunities, and improving environmental quality.

This study investigates the impact of big data analytics capabilities on export performance. Moreover, it assesses the mediating effect of the supply chain innovation and moderating effect of supply chain agility.

This study is based on primary data that were collected from the manufacturing sector operating in Jordan. A total of 327 responses were used for the final data analysis. Data analysis was performed via a partial least square structural equation modeling (PLS-SEM) approach.

The results of the data analysis supported a positive relationship between big data analytics capabilities and the export performance as well as a mediating effect of supply chain innovation. It was confirmed that supply chain agility moderated the relationship of supply chain innovation and export performance.

This study developed a theoretical and empirical model to investigate the relationship between big data analytics capabilities, export performance, supply chain innovation and supply chain agility. This study offers new theoretical and managerial contributions that add value to the supply chain management literature by testing the moderated-mediated model of these constructs in the manufacturing sector in Jordan.

This paper aims to focus on the issue of high employee turnover in the Indian tech industry. An integrative review is conducted to analyse the past and current state of literature, as well as prepare a research agenda for future studies.

A pool of 72 articles published between 2010 and 2022 is reviewed with a special focus on Indian tech employees. This study elucidates the extent and impact of employee retention strategies through content analysis.

Two broad perspectives have been established in the literature: the reasons for quitting and the explanations for staying. By means of a comprehensive review, this paper combines these two aspects of literature and suggests factors under organization’s control to retain competent tech employees.

The study is designed to integrate the two theoretical viewpoints of employee turnover literature by consolidating the reasons behind quitting behaviour and staying intention. Codes combining the two aspects are presented as a valuable resource to retain tech talent.