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This study examines the causal relationship between exports and economic growth in sub-Saharan African (SSA) countries during the period 1980 to 2017. The study also examines whether the causality between these two macroeconomic variables depends on the countries' stage of development as proxied by their per capita income.

The study uses a panel cointegration test and panel Granger-causality model to examine the link between exports and growth. The study also incorporates external debt as an intermittent variable in a bivariate setting between exports and economic growth, thereby creating a dynamic multivariate panel Granger-causality model.

Although the study found the existence of a long-run relationship between exports and economic growth, the study failed to find any export-led growth response in both low-income and middle-income countries. Instead, the study found evidence of a bidirectional causality and a neutrality response in middle-income and low-income countries, respectively. The study, therefore, concludes that the benefits of an export-led growth hypothesis may have been oversold, and that the strategy may not be desirable to some low-income developing countries.

These findings have important policy implications as they indicate that the causality between exports and economic growth in SSA countries varies with the countries' stage of development. Consistent with the contemporary literature, the study cautions low-income SSA countries against over-relying on an export-led growth strategy to achieve a sustained growth path as no causality between exports and economic growth has been found to exist in those countries. Instead, such countries should consider pursuing new growth strategies by building the domestic demand side of their economies alongside their export promotion strategies in order to expand the real sector of their economies. For middle-income countries, the study recommends that both export promotion strategies and pro-growth policies should be intensified as economic growth and exports have been found to reinforce each other in those countries.

Unlike the previous studies, the current study disaggregated the full sample of SSA countries into two subsets – one comprising of low-income countries and the other consisting of middle-income countries. In addition, the study uses a multivariate Granger-causality model in order to address the emission-of-variable bias. To our knowledge, this may be the first study of its kind in recent years to examine in detail the causal relationship between exports and economic growth in SSA countries using an ECM-based multivariate panel Granger-causality model.

本研究旨在探討在1980年至2017年期間撒哈拉以南非洲國家的出口、與其經濟增長之間的因果關係，亦探討這兩個宏觀經濟變量之間的因果關係、會否取決於有關國家所處以人均收入來衡量的發展階段。

本研究雖然發現出口與經濟增長存有一個長期性關係，唯未能於低收入國家或中等收入國家、找到任何出口帶動的增長反應。研究反而找到證據，證實中等收入國家為一雙向性因果關係反應，而低收入國家則為一中立性反應。因此，研究的結論是：出口必能帶動經濟增長這假設被過度吹噓，而且，對部份低收入發展中國家而言，實施以出口帶動經濟增長的策略或許是沒有用的。

本研究的結果在政策方面有其重要意義。這是因為研究結果顯示、於撒哈拉以南非洲國家、出口與經濟增長之間的因果關係，會因有關國家所處的發展階段而有所變更。與當代文獻一樣，本研究提醒低收入的撒哈拉以南非洲國家，不要過度依賴以出口帶動增長的策略來謀求踏上持續增長之路，這是因為在這些國家，出口與經濟增長之間的因果關係仍未確立。他們反而應考慮推行新增長經濟策略，方法是在實施推動出口的策略的同時，也要建立其經濟的國內需求面，以擴大其經濟實業部門。就中等收入國家而言，本研究建議他們應增強推動出口的策略及強化促進增長的政策，這是因為在這些國家裏，經濟增長及出口已被證實會互為增強。

有別於過去的研究，本研究把撒哈拉以南非洲國家的整體樣本分解為兩個子集：一個包括低收入國家，另一個則包括中等收入國家。而且、研究使用了多變量面板格蘭傑因果關係模型、以處理遺漏變數偏差的問題。據我們了解，這大概是近年首個同類研究、以基於歐洲共同市場多變量面板格蘭傑因果關係模型、來詳細探討於撒哈拉以南非洲國家、出口與經濟增長之間的因果關係。

The purpose of this paper is to explore differences in the degree of innovation in employment relations (ER) between emerging and established firms,

A large national telephone survey (N=1,416) of both emerging (<5 years) and established firms was conducted.

Emerging firms were more casualised, less unionised, and experiencing higher levels of market expansion and unpredictability. Despite these differences, younger firms showed otherwise remarkable similarity to older firms across a range of ER practices, and both categories showed a reliance on business networks, rather formal training, for ER knowledge. While introducing ER changes more rapidly than older (and larger) firms, they were converging towards a suite of ER practices similar to that adopted by older firms. The results suggest that, if anything, established firms may have been engaged in greater innovation in more unusual ER practices.

Only managers were surveyed. The data are cross-sectional rather than longitudinal. As the study was undertaken in only one country, replication in other settings would be desirable.

The results raise major doubts about the notion that new firms represent the cutting edge of innovation, and highlights the degree to which newer firms match or mimic older firms’ ER architecture.

Alcohol, tobacco, marijuana and other drugs use typically increases in prevalence and frequency during middle and late adolescence. School health instruction often focusses on providing facts and rarely provides tools for addressing the psychosocial risk factors needed to prevent substance use. The purpose of this paper is to report about the effectiveness of a prevention programme delivered in US high school health classes. The intervention augments typical instruction by providing teachers with activities that can be infused in their daily teaching.

In total, 26 schools were randomly assigned to receive the intervention or serve as controls. Pupils were pretested near the beginning of the school year, posttest near the end of the school year and administered a final test near the beginning of the following school year. Teachers in treatment schools were provided with activities designed to target psychosocial variables known to mediate substance use onset and self-initiated cessation. These include normative beliefs, intentionality, lifestyle incongruence, beliefs about consequences of use, peer pressure resistance skills, decision-making skills, goal setting skills and stress management skills.

Hierarchical modelling analytic strategies revealed the intervention to have definable positive impacts on alcohol and cigarette use. Moreover, the intervention had strongest effects on alcohol and cigarette use among pupils who were identified at pretest as being lower-than-average risk.

This research provides support for providing teachers with a strategy for preventing alcohol, tobacco and other drugs that can be used in a flexible manner to augment the instruction they are already mandated to provide.

The purpose of this paper is to review the establishment of Primary Health Network (PHN) in Australia and its utility in commissioning Primary Health Care (PHC) services.

This study is an analysis of management practice about the establishment and development of a PHN as a case study over the three-year period. The PHN is the Hunter New England and Central Coast PHN (HNECCPHN). The study is based on “insiders perspectives” drawing from documentation, reports and evaluations undertaken.

HNECCPHN demonstrates a unique inclusive organisation across a substantial diverse geographic area. It has taken an innovative and evidence-based approach to its creation, governance and operation. HNECCPHN addresses the health challenges of a substantial Aboriginal and/or Torres Strait Islander population. It contains significant and diverse urban, coastal and distinct rural, regional and remote populations. It can be described as a “virtual” organisation, using a distributed network of practice approach to engage clinicians, communities and providers. The authors describe progress and learning in the context of theories of complex organisations, innovation, networks of practice, knowledge translation and social innovation.

The study provides initial publication into the establishment phase of a PHN in Australia.

The study describes the implementation and progress in terms of relevant international practice and theoretical concepts. This paper demonstrates significant innovative practice in the short term.

The study describes significant engagement and the importance of that with and between communities, service providers and health professionals.

This is the first study of the results of the implementation of an important change in the funding and delivery of PHC in Australia.

The purpose of this study is to provide current state of knowledge on how the COVID-19 emergency situation necessitated the behaviour influencing use and acceptance of telehealth. This study interlinks the health belief model (HBM) and the unified theory of acceptance and use of technology (UTAUT) to highlight the challenges and opportunities as a result of the COVID-19 pandemic in the public health sector.

This study used three online databases (Emerald publishing, Science Direct and Taylor and Francis) that enabled the authors to access electronic journal articles. Search strategy was used to extract articles based on the relevance of this study.

The key findings from this study suggested that the COVID-19 emergency forced health-care workers and their patients to rapidly use and rely on telehealth to reduce the rate of COVID-19 transmissions. The key benefits of telehealth use highlighted an expansive cost effective and convenient access to health-care services irrespective of geographical local and levels of physical impairment. Moreover, telehealth inhibited in person human interaction, which was perceived as impersonal and not ideal for new patient consultations. The barriers outweighed the benefits; as a result, it is unlikely that there will be a wide use of telehealth beyond the COVID-19 emergency situation.

The research findings are limited to discussions drawn from available secondary data. The criteria within telehealth for policymakers to note the technology acceptance and use for both health-care and outpatient stakeholders and their health seeking behaviour. Health-care sectors (private and public) and government need to understand enablers of effective telehealth in policymaking to ease the barriers during an emergency situation like a pandemic.

This study contributes to the emerging literature on how COVID-19 pandemic has disrupted and accelerated telehealth by extending both the UTAUT and HBM theories. This study is expected to contribute and expand literature on telehealth during emergency situations, given the novice nature of COVID-19 and limited literature surrounding it.

We make use of the Volunteered Geographic Information (VGI) data to extract the total extent of the roads using remote sensing images. VGI data is often provided only as vector data represented by lines and not as full extent. Also, high geolocation accuracy is not guaranteed and it is common to observe misalignment with the target road segments by several pixels on the images. In this work, we use the prior information provided by the VGI and extract the full road extent even if there is significant mis-registration between the VGI and the image. The method consists of image segmentation and traversal of multiple agents along available VGI information. First, we perform image segmentation, and then we traverse through the fragmented road segments using autonomous agents to obtain a complete road map in a semi-automatic way once the seed-points are defined. The road center-line in the VGI guides the process and allows us to discover and extract the full extent of the road network based on the image data. The results demonstrate the validity and good performance of the proposed method for road extraction that reflects the actual road width despite the presence of disturbances such as shadows, cars and trees which shows the efficiency of the fusion of the VGI and satellite images.

The purpose of this paper is to explore the prevalence of potential problem gambling among Finnish prisoners; the associations between problem gambling and demographics, substance use and crime-related factors; and problem gamblers’ support preferences.

Prisoners (n=96) from two Finnish prisons were recruited between December 2017 and January 2018. The estimated response rate was 31 percent. Gambling problems were measured using the Brief Biosocial Gambling Screen. The participants were asked to report their gambling both for one year prior to their incarceration and for the past year. The independent variables were demographics (age, gender and marital status), substance use (alcohol, smoking and narcotics) and crime-related factors (crime type, prison type and previous sentence). Statistical significance (p) was determined using Fischer’s exact test.

Past-year pre-conviction problem gambling prevalence was 16.3 percent and past-year prevalence 15 percent. Age, gender, smoking, alcohol or illicit drug use were not associated with past-year problem gambling before sentencing. One-third of the prisoners (33.3 percent) who were sentenced for a property crime, financial crime or robbery were problem gamblers. One-quarter (24 percent) of all participants showed an interest in receiving support by identifying one or more support preferences. The most preferred type of support was group support in its all forms.

It is recommended that correctional institutions undertake systematic screening for potential problem gambling, and implement tailored intervention programs for inmates with gambling problems.

This study provides a deeper understanding of problem gambling in prisons. Problem gambling is associated with crime and also seems to be linked with serving a previous sentence. Early detection and tailored interventions for problem gambling may help to reduce reoffending rates.

This study analyses the literature on artificial intelligence (AI) and its implications for the agri-food sector. This research aims to identify the current research streams, main methodologies used, findings and results delivered, gaps and future research directions.

This study relies on 69 published contributions in the field of AI in the agri-food sector. It begins with a bibliographic coupling to map and identify the current research streams and proceeds with a systematic literature review to examine the main topics and examine the main contributions.

Six clusters were identified: (1) AI adoption and benefits, (2) AI for efficiency and productivity, (3) AI for logistics and supply chain management, (4) AI for supporting decision making process for firms and consumers, (5) AI for risk mitigation and (6) AI marketing aspects. Then, the authors propose an interpretive framework composed of three main dimensions: (1) the two sides of AI: the “hard” side concerns the technology development and application while the “soft” side regards stakeholders' acceptance of the latter; (2) level of analysis: firm and inter-firm; (3) the impact of AI on value chain activities in the agri-food sector.

This study provides interpretive insights into the extant literature on AI in the agri-food sector, paving the way for future research and inspiring practitioners of different AI approaches in a traditionally low-tech sector.