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This article examines the fiscal challenges the coronavirus pandemic poses in African countries, using Ghana as a case study and summarizes the country's immediate monetary and fiscal responses to the pandemic. The article also discusses the potential impacts of coronavirus-related shocks on the Ghana economy and policy options the national government may pursue to counteract the pandemic's adverse long-term effects.

The article uses daily and monthly economic indicators to assess the immediate impact of the pandemic on Ghana's economy. The article also uses latest data from the Ghana Living Standards Survey (GLSS) to simulate potential shocks to the economy related to the coronavirus crisis and examines the outcomes from a potential government response that expands spending on an existing direct social assistance program.

The authors find that the coronavirus pandemic is associated with a significant increase in Ghana's poverty measures over time, and an expansion in government spending under an existing cash transfer program would partly offset the economic shocks related to the crisis and improve outcomes for poverty and inequality. The authors also argue that other well-targeted expenditure and revenue policies will support long-term economic resilience.

The research suggests that a temporary expansion of the existing program of direct cash payments to poor households may be an effective social protection policy, as are well-targeted revenue and spending policies that support economic recovery and long-term fiscal sustainability.

The findings imply that while the pandemic might cause severe shocks in the economy, well-targeted spending and revenue policies that are anchored in sound macroeconomic management can promote economic resilience and long-term fiscal sustainability.

Public managers must ensure that national policy responses to the coronavirus pandemic consider socio-economic indicators, such as poverty and income inequality.

The authors present research that uses novel household-level data and an evidence-based microsimulation framework to articulate potential public policy strategies that can guide national responses to, and recovery from, the coronavirus pandemic.

This article examines the preliminary impact of the Sars-CoV-2 pandemic on India's economic and budgetary landscape – the most affected developing country from the first wave of the pandemic. It also includes a discussion of the monetary and fiscal responses adopted and the challenges faced in formulating the response to the pandemic.

Using high-frequency economic and fiscal indicators, this article evaluates the economic impact of the pandemic on the Indian economy. Further, it uses data from government sources and news to highlight the measures adopted at the national and subnational level in response to the pandemic.

The difficult economic conditions prior to the pandemic limited the fiscal space available to the government. As a result, the national and subnational governments have been cautious of accumulating excessive debt and have primarily responded with liquidity-enhancing measures, in addition to some fiscal measures for the most vulnerable. Overdependence on consumption taxes has led to unprecedented revenue shortfalls prompting the exploration of new avenues for revenue generation and implementation of austerity measures – some of which may be counterproductive in the long run.

The paper highlights the policy response of the largest democracy that has been hit hard by the pandemic. It also highlights various institutional and resource constraints that influenced the policies adopted. India's experience in responding to the virus could provide lessons for other developing countries.

Over the years, public sector reforms in emerging economies have focused on improving national budget systems and financial management practices to promote sustainable development. In the context of the COVID-19 crisis, this article examines whether the strength or effectiveness of national budget systems and related financial management practices moderates the impact of fiscal policy measures on economic recovery and resilience.

The article uses bivariate correlations and difference-in-difference analyses to examine the relationship between budget system effectiveness, government stimulus measures and forecasts of economic recovery and resilience. The analysis uses data from the Public Expenditure and Financial Accountability (PEFA) program, International Monetary Fund (IMF) and World Bank.

The article finds that estimates of economic recovery and resilience are higher in countries with more reliable budget processes and more transparent public finances. Also, the strength or effectiveness of the budget system before the pandemic appears to moderate the impact of government stimulus measures on economic recovery and resilience over a medium-term forecast horizon.

This is a prospective analysis based on economic forecasts from the IMF, which are subject to change in the coming years. In addition, the analysis uses subjective budget system indicators, which present measurement challenges that often influence this area of research. Better comparative data in the future, for example, large administrative datasets, will enable researchers to explore these issues with less estimation bias.

The findings are relevant for policymakers and budget officials in developing countries in Africa who are engaged in plans to improve national budget systems and enhance resilience to crises, such as the COVID-19-induced economic crisis. The findings also have implications for developing countries beyond Africa with similar economic and fiscal conditions.

The findings have implications for economic and budgetary planning for the social sector as well as the efficient delivery of public services in developing countries. Public managers have a critical role to play in adapting national budget systems and financial management reforms within complex and evolving economic circumstances even after the coronavirus pandemic.

The authors use novel and latest data on country responses to the COVID-19 pandemic as well as medium-term economic forecasts to examine the relationship between national budget systems and post-pandemic economic recovery and resilience in the African context. Previous research has only addressed these issues in the context of industrialized countries, and a limited number of empirical studies examine these relationships. The findings also have significant value for policymakers outside Africa who are facing similar challenges related to the coronavirus pandemic.

The general data protection regulation (GDPR) was designed to address privacy challenges posed by globalisation and rapid technological advancements; however, its implementation has also introduced new hurdles for companies. This study aims to analyse and synthesise the existing literature that focuses on challenges of GDPR implementation in business enterprises, while also outlining the directions for future research.

The methodology of this review follows the preferred reporting items for systematic reviews and meta-analysis guidelines. It uses an extensive search strategy across Scopus and Web of Science databases, rigorously applying inclusion and exclusion criteria, yielding a detailed analysis of 16 selected studies that concentrate on GDPR implementation challenges in business organisations.

The findings indicate a predominant use of conceptual study methodologies in prior research, often limited to specific countries and technology-driven sectors. There is also an inclination towards exploring GDPR challenges within small and medium enterprises, while larger enterprises remain comparatively unexplored. Additionally, further investigation is needed to understand the implications of emerging technologies on GDPR compliance.

This study’s limitations include reliance of the search strategy on two databases, potential exclusion of relevant research, limited existing literature on GDPR implementation challenges in business context and possible influence of diverse methodologies and contexts of previous studies on generalisability of the findings.

The originality of this review lies in its exclusive focus on analysing GDPR implementation challenges within the business context, coupled with a fresh categorisation of these challenges into technical, legal, organisational, and regulatory dimensions.

3D food printing technology is an emerging smart technology, which because of its inbuilt capabilities, has the potential to support a sustainable supply chain and environmental quality management. This new technology needs a supportive ecosystem, and thus, this paper identifies and models the enablers for adopting 3D printing technology toward a sustainable food supply chain.

The enablers were identified through an extensive literature review and verified by domain experts. The identified enablers were modelled through the hybrid total interpretive structural modelling approach (TISM) and the decision-making trial and evaluation laboratory (DEMATEL) approach.

It emerged that stakeholders need technical know-how about the 3D printing technology, well supported by a legal framework for clear intellectual property rights ownership. Also, the industry players must have focused and clear strategic planning, considering the need for sustainable supply chains. Moreover, required product innovation as per customer needs may enhance the stakeholders' readiness to adopt this technology.

The framework proposed in this research provides managers with a hierarchy and categorization of adoption enablers which will help them adopt 3D food printing technology and improve environmental quality.

This research offers a framework for modelling the enablers for 3D food printing to develop a sustainable food supply chain using the TISM and DEMATEL techniques.

Employees have gradually adopted social media sites and their applications that have been associated with enhanced communication and collaboration at the workplace. However, social technologies have both positive as well as negative consequences. The current study examines the impact of loneliness on employees' psychological well-being (PW); subsequently, the mediating role of social media use intensity (SMI) at the workplace. It also examines the moderating role of gender and management status of employees.

The present study conducted an online and offline survey using a cross-sectional design. Data were collected from 206 working professionals from the IT industry in India. Structural equation modelling was applied to analyse data.

Results revealed that employee loneliness is positively associated with SMI. Employee's SMI was positively associated with enhanced PW. Unexpectedly, employee loneliness is positively and significantly related to PW. However, the moderating roles of gender and management status of employees were not supported.

The current study can help managers, policymakers and organizations better understand the role of employee social media use in the workplace. Using the insights and understanding offered by the study, social media can be effectively utilized in the workplace. The study recommends that organizations may allow the use of social media at the workplace. Social media resources may also be helpful in improving employee communication and digital literacy.

The current study is a pioneer work and contributes to the literature by examining the relationship between loneliness, SMI and PW. This study has essential theoretical and managerial contributions.

The aim of the paper is to measure the service quality, satisfaction, service value and behavioral intentions of Gen Z in leading global Quick Service Restaurants (QSRs) in India by integrating QUICKSERV into an established model of consumer behavior.

A cross-sectional study design was used for the hypothesis testing. Service quality perceptions with satisfaction, service value and behavioral intentions were measured using structural equation modeling.

The outcomes suggest a direct effect of the service quality of QSRs on the satisfaction, service value and behavioral intentions of Gen Z customers. Satisfaction further influenced customers' behavioral intentions. However, customer satisfaction and behavioral intentions were not directly influenced by service value. Finally, the association between service quality and behavioral intentions was mediated by satisfaction.

Managers should encourage a pleasant attitude, good grooming and friendliness in QSR employees as Gen Z highly values these aspects. At the same time, QSRs should focus to elevate the service value of Gen Z customers by lowering their sacrifice perceptions and fostering initiatives.

Although many studies have considered millennials along with Gen Z to analyze the relationship between service quality and behavioral intentions in different service settings, few researchers have considered the impact of Gen Z consumer features in service quality research separately. The findings of the study will help both practitioners of different QSR brands and facilitators in hospitality academia to better understand the nuances and uniqueness of Gen Z consumer behavior in the QSRs.

International projects very commonly experience failure due to various factors at the global level. Especially, large projects at the international level virtually have no chance of meeting scope, time, cost and quality. This fact has been underlined by most of the international surveys and published literature. Effective risk management plays a vital role in preventing projects from failure by implementing appropriate risk response strategies. The success of risk management will be based on the understanding of various risk categories which specifically affect international projects, analysis of their interdependence, prioritize them according to their importance and develop strategies for risk management based on the prioritization. The paper aims to discuss these issues.

This paper represents typical eight risk categories frequently observed in the international projects through literature survey and feedback from project professionals. Interpretive structural modeling (ISM) and Matrice d’Impacts croises-multiplication applique´ an classment (MICMAC) analysis have been used to analyze the interactions among the risk categories and prioritize them. The strategy management tool threats, opportunities, weaknesses and strengths (TOWS) matrix has been used to develop the strategies for effective project risk management.

The analysis represents political risks, contractual and legal risks, cultural risks, and financial and economic risks as the highest priority risk categories, the mitigation of which should be paid the highest attention. The strengths-threats strategy has been applied to develop the strategies by identifying the various internal strengths of project organization to overcome the various threats caused by the eight risk categories observed in international projects.

This paper tries to represent the prioritization of international project risk categories which are generic in nature. For any specific international project, the risk categories as well as their prioritization may be slightly varying. The tool used for prioritization; Interpretive structural modeling (ISM) is more suitable for few numbers of variables as it becomes complex as the number of variables increases. The strengths and threats considered for developing strategies using TOWS matrix are based on the feedback from project professionals and may vary according to the nature of project.

This paper uses ISM and MICMAC for risk prioritization in international projects and TOWS matrix for developing risk management strategies. This may trigger new opportunities for in-depth research in the risk management strategy development for international projects.

This study explores match related factors and their impact on the batting strike rate in Twenty20 cricket – an aspect which can generate excitement and fan engagement in cricket matches.

Data was collected from www.cricinfo.com using a web scraping tool based on R programming from February 17, 2005, to October 25, 2022, numbering 4,221 men’s Twenty20 international innings featuring 41 national teams that had taken place in 85 venues across 11 countries of play. Hypothesis testing was conducted using one-way ANOVA.

The findings indicate that batters score faster in the first inning of a match, and mean strike rates also vary significantly based on the country of play. Further, the study analyses the top performing national sides, venues and country of play in terms of mean batting strike rate, thus providing insights to cricket boards, international regulating bodies of cricket, sponsors, media companies and coaching staff for better decision-making based on batting strike rate.

The originality of the study lies in its focus on using non-marketing strategies to increase fan engagement. Further, this study is the first one to examine different venues from the perspective of batting strike rate in men’s Twenty20 international matches.

The purpose of this paper is to quantify and evaluate transport sustainability from an integrated perspective. It is argued that transportation systems being interdisciplinary and complex, the integrated approach towards quantification and evaluation would present its sustainability goals’ attainment in a much better way.

The proposed integrated methodology is divided into five major steps that are sub-divided. It adopts a three-tier classification system i.e. pillar, sub-division and indicator. In total, 116 sustainable transportation indicators (STIs) were classified into 10 subdivisions corresponding to three sustainability pillars. The weighting and aggregation of STIs were done using a combination of a statistical tool called principal component analysis/factor analysis, a machine learning tool called fuzzy logic and equal weighting method. The final output that the proposed integrated methodology generates is a new composite index called the integrated sustainable transportation index (IIST).

To check the credibility of the proposed integrated methodology, it was applied to 26 states and the National Capital Territory (NCT) of Delhi, India. Based on the computed IIST, 27 study zones were ranked and mapped. The results showed that while Tamil Nadu (0.643), Telangana (0.574) and Maharashtra (0.564) were the best-performing states, Goa (0.347), Chhattisgarh (0.436) and Meghalaya (0.439) were the worst-performing states, as far as the relative transportation sustainability is concerned.

The proposed integrated methodology could be useful for transportation evaluators, planners and policymakers who can recognize, track and improve the strengths and overcome the weaknesses within a transportation system.

The novelty of this research work is that it uses a multi-stage multi-tool approach to quantify and evaluate transport sustainability that minimizes the demerits of single-stage individual tools while maximizing their merits.