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PurposeThe present study aims to assess the role of supply chain resilience as an operational excellence approach to deal with disruptions caused by coronavirus pandemic in the food supply chain of an agri-food supply firm.Design/methodology/approachThe case study method was used to analyse the disruptions faced by the agricultural food supply chain during the pandemic. The study applies a dynamic capability theory as a foundation to develop a contextualised resilience framework for agri-food supply chain to achieve operational excellence. The case has been analysed by using situation-actor-process (SAP) and learning-action-performance (LAP) framework.FindingsThe SAP aspect of framework points that the flexibility amongst actors for a resilient agriculture supply chain worsened due to the lockdown measures post COVID-19. The LAP aspect of framework suggests how resilience can be built at the supply, demand and logistics end through various proactive and reactive practices such as collaboration, coordination, ICT and ground-level inputs. Lack of commitment and inadequate support from top management towards supply chain resilience are also observed as significant challenges to maintain operational excellence during the pandemic.Research limitations/implicationsOne of the major implications of the study is that a mix of capabilities rather than a single capability can be the most appropriate way for making the supply chain resilient to maintain operational excellence during the pandemic. However, the sources of disruptions need to be duly recognised to derive the best-contextualised resilience framework for agri-food supply chains.Originality/valueThe development of a contextualised research framework as well as research propositions for analysing supply chain resilience are the major contribution of this study.

Screening for genomic sequence variants in genes of predictive and prognostic significance is an integral part of precision medicine. Next-generation sequencing (NGS) technologies are progressively becoming platforms of choice to facilitate this, owing to their massively parallel sequencing capability, which can be used to simultaneously screen multiple markers in multiple samples for a variety of variants (single nucleotide and multi nucleotide variants, insertions and deletions, gene copy number variations, and fusions). A crucial step in the workflow of targeted NGS is the enrichment of the genomic regions of interest to be sequenced, against the whole genomic background. This ensures that the NGS effort is focused to predominantly screen target regions of interest with minimal off-target sequencing, making it more accurate and economical. Polymerase chain reaction-based (PCR, or amplicon-based) and hybridization capture-based methodologies are the two prominent approaches employed for target enrichment. This review summarizes the basic principles of target enrichment utilized by these methods, their multiple variations that have evolved over time, automation approaches, overall comparison of their advantages and drawbacks, and commercially available choices for these methodologies.

PurposeMicro, small and medium enterprises (MSMEs) are facing major difficulties with working capital, need of digitalisation and lack of skilled workforce during this crisis situation. Managing resilience post pandemic is again a huge challenge for MSMEs. Therefore, the main objective of the study is to identify the critical barriers for recovery of MSMEs from the pandemic outbreak and recommending potential solutions for avoiding vulnerabilities.Design/methodology/approachThe most significant barriers, which will impact MSMEs resilience issues are extracted from vast literature review, discussed with nine experts from MSMEs and further categorised into organisational, operational and technical barriers. Best–worst method (BWM) has been used to find the importance rating of barriers for developing resilience in MSMEs.FindingsIt can be observed that the organisational barriers (0.507) are the most significant, followed by operational barriers (0.300) and then, technological barriers (0.192). Liquidity crunch and inadequate technical skills of employees are the most significant barriers for MSMEs resilience during COVID-19, whereas fluctuation in input cost, unavailability of containers on time and decreased process efficiency are the least significant barriers for recovering MSMEs post COVID-19.Practical implicationsFindings imply that MSMEs should try to overcome major barriers such as resource constraints, lack of skills and knowledge and inefficient inventory planning.Originality/valueFindings of study will be of immense use for MSMEs in efficient management of operations and in developing resilience during uncertain business environment.

Quantification and prediction of drought events are important for planning and management of water resources in coping with climate change scenarios at global and local scales. In this study, heuristic approaches including Co-Active Neuro Fuzzy Inference System (CANFIS), Multi-Layer Perceptron Neural Network (MLPNN) and Multiple Linear Regression (MLR) were utilized to predict the hydrological drought based on multi-scalar Streamflow Drought Index (SDI) at Naula and Kedar stations located in upper Ramganga River basin, Uttarakhand State, India. The SDI was calculated on 1-, 3-, 6-, 9-, 12- and 24-month time scales (SDI-1, SDI-3, SDI-6, SDI-9, SDI-12, and SDI-24) using monthly streamflow data of 33 years (1975-2007). The significant input variables (lags) for CANFIS, MLPNN, and MLR models were derived using autocorrelation and partial autocorrelation functions (ACF &PACF) at 5% significance level on SDI-1, SDI-3, SDI-6, SDI-9, SDI-12 and SDI-24 data series. The predicted values of multi-scalar SDI using CANFIS, MLPNN and MLR models were compared with the calculated values, based on root mean squared error (RMSE), Nash-Sutcliffe efficiency (NSE), coefficient of correlation (COC) and Willmott index (WI). The visual interpretation was also made using line diagram, scatter diagram and Taylor diagram (TD). The results of analysis revealed that the performance of CANFIS models was the best for hydrological drought prediction at 3-, 6- and 12-month time scales for Naula station, and at 1-, 3-, 12- and 24-month time scales for Kedar station; while MLPNN was the best at 1- and 9-month time scales for Naula station, and at 6- and 9-month time scales for Kedar station. The MLR model was found to be the best at 24-month time scale for Naula station only. The results of this study could be helpful in prediction of hydrological drought on multiple time scales and decision making for remedial schemes to cope with hydrological drought at Naula and Kedar stations.

Blockchain technology, is conceptualised as a type of disruptive technology and is regarded as one of the prime tools of Industry 4.0 today. The varied features of Blockchain like smart contract, decentralisation, transparency, traceability, data immutability and data privacy along with a consensus mechanism make it suitable to be utilized in the complex and multi—echelon supply chains of today. These factors improve the production processes and make the existing supply chains agile, resilient and responsive in the long term. Blockchain also add an aspect of sustainability which correlates with the phenomenon of circular economy in today’s world. Hence firms should compare and evaluate the significance of the traditional supply chain and blockchain-enabled supply chain in bringing the concept of sustainability in the supply chain today. This paper aims to highlight the benefits of blockchain in supply chain management with the help of a literature review along with opinions of experts from the agricultural sector. The key benefits identified are data privacy, decentralisation, immutability of data, smart contract, improved sustainability, building of resilient supply chains, transparency and shared database. These potential benefits of blockchain are assessed using the analytical hierarchical process technique. Global desirability index for traditional supply chain and blockchain—enabled supply chain is calculated. The high value of global desirability index of the blockchain-enabled supply chain over the traditional supply chain suggests that the application of blockchain technology in the supply chain is justified for bringing sustainability in the supply chain. This study aims to offer meaningful implications for practitioners so that they can take suitable measures for adoption of this technology.

PurposeThe agricultural supply chain is susceptible to disruptive geopolitical events. Therefore, agri-food firms must devise robust resilience strategies to hasten recovery and mitigate global food security effects. Hence, the central aim of this paper is to investigate how supply chains could leverage digital technologies to design resilience strategies to manage uncertainty stemming from the external environment disrupted by a geopolitical event. The context of the study is the African agri-food supply chain during the Russian invasion of Ukraine.Design/methodology/approachThe authors employ strategic contingency and dynamic capabilities theory arguments to explore the scenario and conditions under which African agri-food firms could leverage digital technologies to formulate contingency strategies and devise mitigation countermeasures. Then, the authors used a multi-case-study analysis of 14 African firms of different sizes and tiers within three main agri-food sectors (i.e. livestock farming, food-crop and fisheries-aquaculture) to explore, interpret and present data and their findings.FindingsDownstream firms (wholesalers and retailers) of the African agri-food supply chain are found to extensively use digital seizing and transforming capabilities to formulate worst-case assumptions amid geopolitical disruption, followed by proactive mitigation actions. These capabilities are mainly supported by advanced technologies such as blockchain and additive manufacturing. On the other hand, smaller upstream partners (SMEs, cooperatives and smallholders) are found to leverage less advanced technologies, such as mobile apps and cloud-based data analytics, to develop sensing capabilities necessary to formulate a “wait-and-see” strategy, allowing them to reduce perceptions of heightened supply chain uncertainty and take mainly reactive mitigation strategies. Finally, the authors integrate their findings into a conceptual framework that advances the research agenda on managing supply chain uncertainty in vulnerable areas.Originality/valueThis study is the first that sought to understand the contextual conditions (supply chain characteristics and firm characteristics) under which companies in the African agri-food supply chain could leverage digital technologies to manage uncertainty. The study advances contingency and dynamic capability theories by providing a new way of interacting in one specific context. In practice, this study assists managers in developing suitable strategies to manage uncertainty during geopolitical disruptions.

Trees growing in boreal and temperate regions synchronize their growth with seasonal climatic changes in adaptive responses that are essential for their survival. These trees cease growth before the winter and establish a dormant state during which growth cessation is maintained by repression of responses to growth-promotive signals. Reactivation of growth in the spring follows the release from dormancy promoted by prolonged exposure to low temperature during the winter. The timing of the key events and regulation of the molecular programs associated with the key stages of the annual growth cycle are controlled by two main environmental cues: photoperiod and temperature. Recently, key components mediating photoperiodic control of growth cessation and bud set have been identified, and striking similarities have been observed in signaling pathways controlling growth cessation in trees and floral transition in Arabidopsis. Although less well understood, the regulation of bud dormancy and bud burst may involve cell–cell communication and chromatin remodeling. Here, we discuss current knowledge of the molecular-level regulation of the annual growth cycle of woody trees in temperate and boreal regions, and identify key questions that need to be addressed in the future.

Streamflow flash droughts (SFDs) occur due to a rapid decline in streamflow and cause major challenges associated with water availability for downstream ecosystems, hydropower generation, and irrigation water demand. Human interventions such as reservoir operations and reservoir storage can considerably influence streamflow variability. However, the crucial role of dams/reservoirs on the occurrence of SFDs in India remains unexamined. Using a combination of hydrological and hydrodynamical models, we examined the role of reservoirs on SFDs in India during 1971–2020. Reservoirs play a considerable role in the occurrence of SFDs during the summer monsoon season (June‐September) in India. The frequency and severity of SFDs in the presence of reservoirs are substantially lesser than in the absence of them. In addition, high and low antecedent reservoir storage conditions before meteorological flash droughts (MFDs) do not support the rapid decline of streamflow (i.e., SFDs) downstream of reservoirs, while the medium reservoir storage conditions prior to MFDs favor the development of SFDs. Similar to conventional (or long‐term) streamflow droughts (SDs), SFDs are more frequent in the El Nino phase than in the La Nina phase. Unlike the long‐term streamflow droughts, the implementation of dams considerably reduces the frequency of SFDs during both the negative and positive phases of El Nino Southern Oscillation. Overall, our findings demonstrate the considerable role of human interventions in flash drought occurrence, as SFDs are triggered by MFDs but modulated by reservoir storage and operations. Plain Language Summary A rapid decline in streamflow poses significant challenges to water availability in downstream regions. Human interventions, particularly associated with dam operations and reservoir storage, can profoundly affect streamflow variability in the downstream of reservoirs. However, the impact of reservoirs on a rapid decline in streamflow (i.e., streamflow flash drought (SFD)) in India has not been examined. Using hydrological and hydrodynamical models, we investigated the role of dams/reservoirs on the occurrence of SFDs in India from 1971 to 2020. We find that reservoirs play a substantial role in reducing the frequency and severity of SFDs during the summer monsoon. High and low reservoir storage before the occurrence of a considerable precipitation deficit in short duration (meteorological flash droughts (MFDs)) in the upstream catchment restricts the occurrence of SFDs. However, medium reservoir storage conditions support the occurrence of SFDs. These findings highlight the crucial role of human interventions, specifically reservoir storage and operations, in mitigating SFDs triggered MFDs. Key Points Examined the role of dams in modulating flash and conventional streamflow droughts in 36 catchments in India Dams/reservoirs decrease the frequency and severity of streamflow flash droughts (SFDs) during the summer monsoon season Dams modulate the influence of climate variability more effectively on SFDs compared to conventional streamflow droughts

PurposeThe purpose of this study is to identify factors that are important for logistics organizations from the perspective of manpower readiness for digitization of logistics operations. The study also prioritizes the identified factors and also evaluates the readiness index of manpower for the digitalization of logistics processes.Design/methodology/approachThe factors for manpower readiness are identified through literature review and analysis of a case study. Three major categories of factors are identified. These are organizational, behavioural and technological factors. Under these three major categories of factors, 18 sub-factors are identified. Thereafter, with experts' inputs, the factors are prioritized using Fuzzy analytic hierarchy process (AHP). Further, a case illustration of an Indian logistics company has been taken to understand the current processes, technical capabilities, manpower skills and organization culture. After the case analysis and expert inputs, the manpower readiness index has been evaluated by using graph theory matrix approach (GTMA).FindingsThe prioritization of manpower readiness factors has been done using Fuzzy AHP. Organizational factors are found to be the most important factors which require quick attention. Sub-factors that are most important for building competencies in the logistics sector are providing the right training on functional skill development (0.129), top management support and commitment for digitalization (0.117), and organizational culture for process digitalization (0.114), etc. Finally, framework for evaluation of manpower readiness index for logistics operations in the digital age has been illustrated for a case company.Practical implicationsIndian logistics companies can benchmark their readiness index with respect to the best in the industry. Based on the readiness index, logistics companies can analyse their position, gaps from best and worst and can also identify potential areas for improvement.Originality/valueThe novelty of the study lies in the development of a framework for manpower readiness for digitalization in the logistics sector. In literature, this field is very less researched and provides the scope for developing strategies for improving manpower competencies for Industry 4.0. Logistics companies can improve their performance by making their manpower ready based on results obtained for readiness index.