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This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.

This study aims to explore some perceptions related to the suggestion that external auditors will be replaced by audit technologies that use artificial intelligence (AI) tools to make audit judgements when performing the financial statement audits. Digital transformation is revitalising the technologies used by external auditors and their firms; thus, the authors seek to understand what challenges this creates for the auditing profession in Vietnam.

Through the theoretical lens of new institutionalism theory, this study uses a qualitative approach involving 20 semi-structured interviews conducted with external auditors in Vietnam during 2022. This sample includes the global Big Four, global mid-tier and smaller local Vietnamese audit firms.

The findings indicate that there is resistance or disagreement with the suggestion that in the future audit technologies using AI tools can replace humans (external auditors). The role of external auditors in the professional services sector will gradually be changed by audit technologies; however, external auditors are unlikely to be replaced by audit technologies that use AI tools based on the responses of the participants. Strict institutional rules that exist in Vietnam would prevent the replacement of (human) external auditors. In the future, external auditors may take on new roles as consultants, with unique skills in classifying and processing data for decision-making processes; however, they will not be completely replaced by technology in the audit space.

This study has limitations that it is based on the data collection from a single developing country, Vietnam; therefore, the generalisability of the findings is limited to Vietnam. Also, the authors sought insights into the future of external audits in Vietnam.

This study highlights the changing role of auditors and institutions. Thus, policymakers, external auditors and auditees in other developing countries would find the findings helpful.

This study provides new perspectives, particularly from local Vietnamese firms, about audit practices that emerge due to high-level technological advancements and then embed themselves into existing audit practices in an emerging economy. Prior studies tended to focus on the global Big Four firms, thus this study contributes by sharing the perceptions of the smaller practitioners also.

This study aims to investigate a mediation model in which generative learning positively affects marketing innovation and both organizational control and relationship openness mediate the relationship between learning intent and generative learning of international joint ventures (IJVs) in emerging markets. We also decipher the degree of necessity of these factors for generative learning and of generative learning for marketing innovation.

A sample of 181 marketing managers of IJVs in Vietnam, an emerging market, was surveyed to collect data. Partial least squares structural equation modeling (PLS-SEM) was employed to test the net effect, and necessary condition analysis (NCA) was used to decipher the degree of necessity.

The PLS-SEM results demonstrate that the effect of learning intent on generative learning is fully mediated by organizational control and relationship openness, which in turn leads to marketing innovation. The NCA findings reveal that all three factors, namely learning intent, organizational control and relationship openness, serve as necessary conditions for generative learning. However, generative learning does not play the role of a necessary condition for marketing innovation.

The study findings suggest that IJVs in emerging markets should pay attention not only to the net effects of those factors but also to their degrees of necessity for generative learning in order to achieve marketing innovation.

The study contributes to the literature by confirming the mediating roles of organizational control and relationship openness in the relationship between learning intent and generative learning. Furthermore, it is among the first to decipher the degrees of necessity of these factors for generative learning and of generative learning for the marketing innovation of IJVs in emerging markets.

Urban rail projects are typically large-scale transport infrastructure projects (megaprojects) which have many potential risks that can influence the strategic goals of owners. However, there is a paucity of studies which explore the impact of risks on both “urban rail” project time and cost together considering quantitative assessments. Therefore, this paper focuses on investigating critical risks and quantifying such risk impacts on urban railway project schedule and cost in practice.

A combination of qualitative and quantitative research methods comprising semi-interviews with five experts and a questionnaire survey of 132 professional respondents is used. The data were modeled using Monte Carlo Simulation to predict the probability of project schedule and cost.

The results show that 30 risk variables are categorized into seven main groups which have significant impacts on both project time and cost. Outstanding five risk variables were highlighted as follows: (1) project site clearance and land compensation; (2) design changes; (3) physical project resources; (4) contractors’ competencies and (5) project finance. Such findings were supported by Monte Carlo simulation which predicted in the worst case that the project may suffer 11.03 months’ delays and have cost overrun with a contingency of US$287.68 million.

This study expands our knowledge about time and cost contingency of urban metro railway implementation across developing economies and particularly within the context of Vietnam. Policymakers will not only gain an understanding about risk structure but will also recognize the significant impacts of critical risk through risk impact modeling and simulation. Such an approach provides insights into risk treatment priorities for planners so that they can proactively establish suitable strategies for risk mitigation in practice.

The paper aims to assess the impact of weather-induced shocks on household food consumption in the rural Vietnamese Mekong Delta (VMD) through the case of Long An province and evaluate the effectiveness of widely used coping strategies in mitigating weather-related shock impacts.

The system generalized method of moments (GMM) estimation method is applied to explore information on shock incidence, recovery, and time occurrences. The paper uses a sample of 272 repeated farming households from 5-wave survey data from 2008 to 2016, resulting in 1,360 observations.

The paper confirms the robust negative effect of a natural shock on food consumption. Additionally, using savings proves to be the most potent measure to smooth food consumption. Other favorable coping strategies are “getting assistance from relatives, friends” or “getting assistance from the Government, and non-government organizations (NGOs).” The mitigating effects are also traced in the current analysis.

Using caution when generalizing the results from Long An to the whole VMD is reasonable. The rather limited observations of coping strategies do not allow the authors to analyze any specific strategy.

The proposed approach employs the GMM technique and controls for endogenous coping strategies and thus provides accurate estimates of the effects of weather-related shocks and the mitigation effectiveness in the rural VMD.

This study explores the economic impact of the COVID-19 crisis on herding behaviour in the Australian equity market by considering liquidity, government interventions and sentiment contagion.

This study utilizes a daily dataset of the top 500 stocks in the Australian market from January 2009 to December 2021. Both predictive regression and portfolio approaches are employed to consider the impact of COVID-19 on herding intention.

This study confirms that herding propensity is more pronounced at the beginning of the crisis and becomes less significant towards later phases when reverse herding is more visible. Investors herd more toward sectors with less available information on financial support from the government during the financial meltdown. Conditioning the stock liquidity, herding is only detectable during highly liquid periods and high-liquid stocks, which is more observable during the initial phases of the crisis. Further, the mood contagion from the United States (US) market to Australian market and asymmetric herding intention are evident during the pandemic.

This is the first study to shed further light on the impact of a health crisis on the trading behaviour of Australian investors, which is driven by liquidity, public information and sentiment. Notwithstanding the theoretical contributions to the prior literature, several practical implications are proposed for businesses, policymakers and investors during uncertainty periods.

This research aims to specialise in the investigation of risk management for service-oriented manufacturing supply chains via two stages, highlighting its differences from manufacturing. The research article is commenced by executing an encyclopedic review of earlier research to ascertain the distinctive traits of service-oriented manufacturing supply chains and identify prevalent risks. Secondly, an empirical study in the construction field, amongst the industry hardest struck in the mist of the COVID-19 epidemic, is conducted to thoroughly inspect the resonant effect of these risks on service-oriented manufacturing supply chain performance.

In this study, to validate the resonant effect mechanism, a thorough assessment is undertaken by juxtaposing theoretical model to a newly constructed comparative model that encompasses the single effects of risks on supply chain performance.

63% variance of service-oriented manufacturing supply chain performance was showcased by the resonant effect model, compared with 46.3% in the comparative model. Moreover, each risk exerts a more glaringly significant impact on supply chain performance, asserting the mechanism of the resonant influence. Another noteworthy result involves the demand risk possessing a low effect on supply chain performance, thus emphasising the superiority of service-oriented manufacturing supply chains.

Future research endeavours should hinge on the optimal “resonant” model explosion, thereby foreseeing and alleviating worst-case scenarios to guarantee the robustness and resilience of supply chain networks.

Indubitably, reducing the intensity of the resonant effect revolves around lowering the coefficient of “a,” thereby restricting/eliminating the link among risks. Therefore, the suggested resonant impact model might thus serve as “a road map”. In light of the aforementioned considerations, it is advisable that supply chain executives employ supply chain management tactics namely avoidance, prediction, and postponement, but only after meticulous consideration the costs and benefits of adopting such strategies.

The service-oriented manufacturing supply chain features and advantages have been analysed and explained throughout the article. The data gathered during the COVID-19 pandemic is a captivating and topical point of this paper.

As an effort to support the quest for a stable financial sector, this study aims to determine the factors that contribute to the financial stability gap in sub-Saharan Africa (SSA).

The estimation techniques used include the fixed and random effect, system general methods of moments and dominance analysis. The data used is annual data for 33 SSA countries, covering the period 2007 to 2018.

Key findings from the analyses indicate that nonperforming loans increase gaps in financial stability while regulatory quality, control of corruption, political stability and appreciation of the local currency reduce the financial stability gap in SSA.

The absence of a specific metric for measuring the financial stability gap appears to be the limitation of this study. Its existence could improve the discussion and also make replicability easier. However, this study relies on a measure introduced by Kulu et al. (2022b), which is also acceptable and quite popular in the literature.

To the best of the authors’ knowledge, this study is the first in the finance literature to estimate the determinants of the financial stability gap in SSA.

Given the relevance of entrepreneurship in nation-building, studies geared towards the promotion of new businesses are crucial. This study aims to contribute to the finance and entrepreneurship literature by providing empirical evidence on the role ease of doing business plays in promoting new business establishments amidst financial stability.

The study used the fixed and random effect estimation techniques as well as the impulse response function to analyse annual panel data covering 53 African countries.

The results indicate that regulatory quality and access to electricity promote new business establishments. Also, to experience the direct effect of financial stability on new business establishments or entrepreneurship in Africa, the role of the ease of doing business cannot be isolated. The policy implication is that the creation of an enabling business environment is crucial for new business establishments.

The sample only includes countries in Africa. Future or further studies may want to expand the sample size and also consider a comparative analysis where this analysis will be done plus another region so that the differences in findings can be known.

To the best of the authors’ knowledge, this is the first study to investigate the role of ease of doing business on new business establishments in the presence of financial stability in Africa.

This study explores the integration of smallholder farmers into the export market in Vietnam, an emerging economy. By introducing a prospective framework, we seek to provide insight into factors that influence this integration process.

This study examines the expected growth and entry of Vietnamese smallholder farmers into high-value export markets. We collected information from 200 independent farmers as well as from five local extension workers, who provided information on 50 farmers.

The study reveals that the adoption of new business models is more influential than the variables traditionally included in models of export-market integration in predicting expected growth and entry into high-value export markets. In addition, the results highlight divergent views between farmers and extension workers regarding the role of collectors, with farmers perceiving collectors as potential partners, while extension workers see them as impediments to growth.

The prospective model presented in this study highlights the importance of policy interventions aimed at promoting new business models and addressing infrastructure and capital constraints for the sustainable transformation of agricultural sectors in emerging markets.

This is one of the first articles to apply a prospective approach to export-market integration and demonstrate its efficacy through an empirical study. The suggested prospective approach could facilitate the design of policies aimed at export-market integration within the context of dynamic, emerging markets.