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To delve into the integration of global logistics and supply chain networks amidst the digital transformation era. This study aims to investigate the potential role of China’s Belt and Road Initiative (BRI) in facilitating the integration of global flows encompassing both tangible goods and intangibles. Additionally, the study seeks to incorporate third-party logistics activities into a comprehensive global logistics and supply chain integration framework.

Prior research is synthesised into a global logistics and supply chain integration framework. A case study was undertaken on Yuan Tong (YTO) express group to investigate the framework, employing qualitative data analysis techniques. The study specifically examined the context of the BRI to enhance comprehension of its impact on global supply chains. Information was collected in particular to two types of supply chain flows, the physical flow of goods, and intangible information and cash flows.

The proposed framework aligns well with the case study, leading to the identification of global logistics and supply chain integration enablers. The results demonstrate a range of ways BRI promotes global logistics and supply chain integration.

The case study, with multiple examples, focuses on how third-party logistics firms can embrace global logistics and supply chain integration in line with BRI. The case study approach limits generalisation, further applications in different contexts are required to validate the findings.

The framework holds promise for aiding practitioners and researchers in gaining deeper insights into the role of the BRI in global logistics and supply chain integration within the digital era. The identified enablers underscore the importance of emphasising key factors necessary for success in navigating digital transformation within global supply chains.

The purpose of this literature review paper is to explore the concept of organization agility and its relevance in today's dynamic business environment. By conducting an in-depth review of existing academic and industry literature on organization agility, this study aims to identify the key factors that influence an organization's agility and the benefits and drawbacks associated with fostering agility.

Through the technique of bibliometric analysis, we provide the growth trajectory of the field by identifying the publication trends, prominent authors and countries and most prolific journal publishing in the concerned domain. We also provide the intellectual structure of the organization agility research by identifying the prominent themes that have been worked upon till date. In addition, with the backing of the theories, contexts, characteristics and methodology (TCCM) framework, we identify the most frequently applied theories, constructs and methods in organization agility research and provide new avenues for future research by analyzing the most frequently used theories, methods, constructs and research contexts.

With the ever-increasing ambiguity and need for change (why), organization agility serves as the organization's backbone. It acts as a springboard for the organization, an anchor point that remains constant while other functional aspects constantly fluctuate and change. Organization agility can be defined (what) as the ability of organizations to quickly respond to market needs by sensing, renewing, adapting and succeeding in a turbulent market. To summarize, organizational agility matters at three fundamental aspects (where): strategic level or the market capitalizing level, internal operational level and individual level.

This paper is unique in the sense that it is the first comprehensive literature review in the field of organization agility research to use a hybrid methodology (bibliometric review with TCCMs).

Even the greatest developed countries have capitulated to the destructions imposed on the global supply systems, as the COVID-19 pandemic has revealed. The purpose of this study is to explore human resource sourcing strategies for managing supply chain performance during the COVID-19 outbreak. There are six human resource sourcing strategies such as outsourcing, near sourcing, integration, the requirement of suppliers, joint ventures and virtual enterprise that are considered to measure supply chain performance.

Based on collecting data from the potential respondents of Indian manufacturing companies, the elevation of human resource sourcing strategies to supply chain performance is measured considering the multiple regression analysis techniques.

The results of the study revealed that four of the six hypotheses have a significant and positive relationship with supply chain performance during the COVID-19 outbreak while two hypotheses are partially supported that lent good support to this study.

In this critical situation, this study will enable managers and practitioners to support the business in giving customers the best services on time.

The novelty of this study is to identify the key human resource sourcing strategies by using multiple regression analysis methods, considering the case of Indian manufacturing companies to measure their supply chain performance during the COVID-19 outbreak era.

The purpose of this paper is to investigate the impact of cloud computing (CC) on supply chain management (SCM).

The paper is conceptual and based on a literature review and conceptual analysis.

Today, digital technology is the primary enabler of supply chain (SC) competitiveness. CC capabilities support competitive SC challenges through structural flexibility and responsiveness. An Internet platform based on CC and a digital ecosystem can serve as “information cross-docking” between SC stakeholders. In this way, the SC model is transformed from a traditional, linear model to a platform model with the simultaneous cooperation of all partners. Platform-based SCs will be a milestone in the evolution of SCM – here conceptualised as Supply Chain 3.0.

Currently, SCs managed holistically in cyberspace are rare in practice, and therefore empirical evidence on how digital technologies impact SC competitiveness is required in future research.

This research generates insights that can help managers understand and develop the next generation of SCM with the use of CC, a modern and commonly available Information and Communication Technologies (ICT) tool.

The paper presents a conceptual basis of how CC enables structural flexibility of SCs through easy, real-time resource and capacity reconfiguration. CC not only reduces cost and increases flexibility but also offers an effective solution for disruptive new business models with the potential to revolutionise current SCM thinking.

Based on the resource-based view (RBV) theory, this study examines how supply chain digitalisation affects firms’ performance by enabling firms to build supply chain agility and innovation capability.

Drawing from the dataset of 271 firms in the United Arab Emirates (UAE), we used structural equation modelling to validate the models. Mediation and moderation analyses were performed to test the research hypotheses.

The results suggest a positive correlation between supply chain digitalisation and a company’s performance, fully mediated by both supply chain agility and innovation capability. The interplay between supply chain agility and innovation capability has the potential to result in unfavourable outcomes for a firm’s performance. These results provide valuable insights into supply chain management during digital transformation.

The study advances the extant research on the antecedents of a firm’s performance by incorporating supply chain digitalisation and mediating mechanisms of supply chain agility and innovation capability that serve as a conduit between supply chain digitalisation and a firm’s performance based on RBV.

The internal (farmer-controlled) and external (non-farmer-controlled) factors affect crop yield. However, not a single study has identified and analyzed yield predictors in India using effective predictive models. Thus, this study aims to investigate how internal and external predictors impact pearl millet yield and Stover yield.

Descriptive analytics and artificial neural network are used to investigate the impact of predictors on pearl millet yield and Stover yield. From descriptive analytics, 473 valid responses were collected from semi-arid zone, and the predictors were categorized into internal and external factors. Multi-layer perceptron-neural network (MLP-NN) model was used in Statistical Package for the Social Sciences version 25 to model them.

The MLP-NN model reveals that rainfall has the highest normalized importance, followed by irrigation frequency, crop rotation frequency, fertilizers type and temperature. The model has an acceptable goodness of fit because the training and testing methods have average root mean square errors of 0.25 and 0.28, respectively. Also, the model has R² values of 0.863 and 0.704, respectively, for both pearl millet and Stover yield.

To the best of the authors’ knowledge, the current study is first of its kind related to impact of predictors of both internal and external factors on pearl millet yield and Stover yield.

The literature reveals that most studies have estimated crop yield using limited parameters and forecasting approaches. However, this research will examine the impact of various predictors such as internal and external of both yields. The outcomes of the study will help policymakers in developing strategies for stakeholders. The current work will improve pearl millet yield literature.

Prefabricated construction has proven to be superior in terms of affordability and sustainability over the years. As a result of sustainable production, prefabricated housebuilding has evolved into a distinct industry reliant on supplier companies acting as supply chains (SCs) for housing projects. These companies' performance is critical to the successful implementation of prefabricated housebuilding technologies. However, in comparison to those choosing manufacturing as a strategy in other industries, the life span of these companies, providing innovative housing solutions, is relatively short. This is due to critical factors influencing the performance, but the inter-relationship of the performance dimensions is more significant. This study establishes the inter-relationship of the companies involved in house building with steel prefabricated housebuilding technologies.

The most recent factors were extracted from the literature. The relationships were developed using the interpretive structural modeling (ISM) method with the input from industry experts, and the driving factors were determined using the Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) technique.

Critical performance factors were classified according to performance dimensions, ranked and classified based on driving and dependence power. The inter-relationships among the performance dimensions of time, quality, cost, delivery, features and innovation were determined. Key performance strategies were proposed for prefabricated housebuilding companies involved in manufacturing and/or assembly of steel products.

This study established the interrelationship of performance dimensions for prefabricated house building (PHB) companies to develop strategies against critical challenges to remain competitive in the housing market. Previous research had not looked into interrelationship among the performance dimensions. The proposed performance strategies are applicable to supplier organizations using steel prefabricated technologies in similar markets around the world.

The purpose of the study is to analyze and measure the impact of disruption in demand which causes the bullwhip effect. The bullwhip effect impacts the performance of firm. Just like everything else, covid has had an impact on the disruption of supply chain too leading to the need of measuring the bullwhip effect of select Indian sectors. The comparison on bullwhip effect is drawn in pre- and during covid era in major sectors. The study helps to understand, analyze and measure the impact of covid and its challenges to supply chain.

The empirical study is carried out on five major select Indian sectors which have the largest market capitalization in Indian economy, namely, FMCG (fast-moving consumer goods), automobile, utility, consumer durable and IT (information technology). The disruption in the supply chain is measured in terms of bullwhip effect. The novel metric ratio of bullwhip effect is computed which is based on demand–supply mismatch and analyzed based on 10 years of observations. The data is analyzed twice, first from 2011 to 2019 (pre-covid era) and second from 2019 to 2021 (during covid era). Each time, Bombay Stock Exchange (BSE) sectoral indices are used to compute the bullwhip ratio, and empirical data is collected using Prowess. The firms listed in BSE represent most of the sector. Such panel data helps us to analyze inter- and intraindustry bullwhip effect. The changes in the bullwhip effect for various BSE listed firms are analyzed pre- and during covid era. These changes are specifically studied at the manufacturer end of the supply chain. Later regression analysis is performed to study the changes required in production based on the demand. The various strategies that cause or mitigate the impact of covid in intraindustry can be derived from the study. The disruption in production is analyzed based on the disruption in demand and profit before interest and tax (PBIT).

In pre-covid era, the percentage of demand disruption was low in select sectors but not exactly zero. Covid caused the disruptions in supply chain across the globe which resulted in bullwhip effect in Indian sectors too. Yet some of the sectors were able to cope better with the situation as compared to others. In the present study, same is analyzed statistically, and results are derived for practical significance.

The empirical data is having the observations of past 10 years to analyze the pattern of demand disruption in the firms and hence the sectors. The impact of covid is studied on performance, which is analyzed in terms of PBIT. The impact of other factors (political, social, marketing policies, etc.) that may cause disruption in the supply chain of a firm is not considered in the study.

Study is unique, as it measures disruption and provides a peerless way to study the inter- and intrasectors. To analyze the impact of bullwhip effect on sector performance, it is very much required to first measure the bullwhip; this measure of bullwhip as a ratio of the slopes of demand and supply is a novel approach. The study emphasizes that the impact of covid is not the same among the firms, and hence among the sectors. Also, it is found that the impact of such adversities can be mitigated, and performance of firm can remain intact in turbulent times too.

One pertinent dynamic phenomenon in supply chains is the amplification of order variance, i.e. the bullwhip effect. Its continued significance is underscored in contemporary empirical research. While numerous publications have pinpointed various causes of the bullwhip effect, there remains a gap in their systematic consolidation. The purpose of this paper is to compile a comprehensive list of the causes of the bullwhip effect from existing literature and categorize them appropriately.

This study conducts a systematic literature review to offer a comprehensive overview of bullwhip effect causes addressed in the existing literature. The identified causes are categorized using a qualitative content analysis approach.

The study shows the diversity of the causes of the bullwhip effect and their interdependencies. In addition, this study demonstrates that, at the highest level of aggregation, causes of the bullwhip effect can be classified into four main categories: causes inherent in the system structure, causes related to uncertainty, causes related to misaligned incentives and causes related to inadequate cognition of the situation.

The work provides an extensive overview and categorization of bullwhip effect causes, offering valuable insights for both researchers and practitioners seeking a deeper understanding of this phenomenon. In addition, it underscores managerial implications and highlights future research opportunities.

The aim of this paper is to provide a review of state-of-the-art literature on information sharing in the context of African perishable agri-food supply chains (AFSCs). In doing so, the authors hope to stimulate further research and advance both theory and practice on African perishable AFSCs, which is a relevant, but under-investigated context.

The authors’ systematic literature review covers a period of 21 years (2000–2021). After providing the bibliometric and methodological insights related to this sample of literature, the authors provide a detailed analysis and discussion of the key aspects of information sharing in African perishable AFSCs, based on a review framework grounded in the information sharing literature.

The authors’ review revealed that information sharing in African AFSCs is still in its nascent stage. Findings are based on four themes of (1) why share information (mainly to gain market access), (2) what information is shared (price and market information) (3) how it is shared (still traditional communication, with limited adoption of digital technologies?) and (4) antecedents, drivers and barriers (technology adoption and socio-economic background of Africans).

This paper outlines a research agenda for advancing the theory on information sharing in AFSCs. Furthermore, the review highlights the importance of context, supply chain structure, relationships, product characteristics and culture in studying AFSCs.

A review on information sharing in African perishable AFSCs does not appear to exist in operations and supply chain management (O&SCM) and agribusiness journals.