Impact of metric-alignment on supply chain performance: a behavioral study

PurposePrevious research has shown that firms are struggling to incorporate collaboration among supply chain partners. This paper presents a new approach to incorporate collaboration using metric-alignment. The analysis provides key insights regarding the usefulness of this approach to synchronize decision-making that leads to reduced bullwhip effect, less backordering and lower supply chain costs.Design/methodology/approachThis research is based on a large-scale behavioral study comprising 556 participants in multi-echelon supply chain games. Supply chain decisions from these experiments are evaluated to study the impact of metric-alignment on managerial decision-making and the corresponding effects on the overall supply chain performance.FindingsResults show that the metric-alignment approach offers an informal and self-enforced governance mechanism that changes managerial decision-making behaviors and improves supply chain performance. Results also show this approach to yield operational and financial benefits for all supply chain partners in the form of reduced bullwhip effect, less backordering and lower supply chain costs.Originality/valueThis is the first behavioral study of its kind that evaluates a new approach to incorporate collaboration in supply chains using metric-alignment. This approach avoids the shortcomings of current industry practices of using monetary penalties, such as on-time in-full (OTIF) mandates in supply contracts. The study shows that metric-alignment approach can improve overall supply chain performance while offering mutually beneficial rewards for all supply chain partners.

Using AI and ML to predict shipment times of therapeutics, diagnostics and vaccines in e-pharmacy supply chains during COVID-19 pandemic

PurposeThis paper aims to address the pressing problem of prediction concerning shipment times of therapeutics, diagnostics and vaccines during the ongoing COVID-19 pandemic using a novel artificial intelligence (AI) and machine learning (ML) approach.Design/methodology/approachThe present study used organic real-world therapeutic supplies data of over 3 million shipments collected during the COVID-19 pandemic through a large real-world e-pharmacy. The researchers built various ML multiclass classification models, namely, random forest (RF), extra trees (XRT), decision tree (DT), multilayer perceptron (MLP), XGBoost (XGB), CatBoost (CB), linear stochastic gradient descent (SGD) and the linear Naïve Bayes (NB) and trained them on striped datasets of (source, destination, shipper) triplets. The study stacked the base models and built stacked meta-models. Subsequently, the researchers built a model zoo with a combination of the base models and stacked meta-models trained on these striped datasets. The study used 10-fold cross-validation (CV) for performance evaluation.FindingsThe findings reveal that the turn-around-time provided by therapeutic supply logistics providers is only 62.91% accurate when compared to reality. In contrast, the solution provided in this study is up to 93.5% accurate compared to reality, resulting in up to 48.62% improvement, with a clear trend of more historic data and better performance growing each week.Research limitations/implicationsThe implication of the study has shown the efficacy of ML model zoo with a combination of base models and stacked meta-models trained on striped datasets of (source, destination and shipper) triplets for predicting the shipment times of therapeutics, diagnostics and vaccines in the e-pharmacy supply chain.Originality/valueThe novelty of the study is on the real-world e-pharmacy supply chain under post-COVID-19 lockdown conditions and has come up with a novel ML ensemble stacking based model zoo to make predictions on the shipment times of therapeutics. Through this work, it is assumed that there will be greater adoption of AI and ML techniques in shipment time prediction of therapeutics in the logistics industry in the pandemic situations.

Blockchain systems and ethical sourcing in the mineral and metal industry: a multiple case study

PurposeThe purpose of this paper is to examine blockchain's roles in promoting ethical sourcing in the mineral and metal industry.Design/methodology/approachIt analyzes multiple case studies of blockchain projects in the mineral and metal industry.FindingsIt gives detailed descriptions of how blockchain-based supply chain networks' higher density of information flow and high degree of authenticity of information can increase supply chain participants' compliance with sustainability standards. It gives special consideration to blockchain systems' roles in overcoming the deficits in the second party and the third-party trust. It also demonstrates how blockchain-based supply chain networks include outside actors and configure the supply chain networks in a way that enhances the empowerment of marginalized groups.Practical implicationsIt suggests various mechanisms by which blockchain-based supply chain networks can give a voice to marginalized groups.Originality/valueIt demonstrates how blockchain is likely to force mineral and metal supply chains to become more traceable and transparent.

Modelling inter-firm competitive rivalry in a port logistics cluster: a case study of Melbourne, Australia

PurposeThe paper models the effect of spatial clustering on various dimensions of inter-firm competitive rivalry among port logistics firms using Porter's five forces model.Design/methodology/approachA survey-based quantitative approach is adopted to collect data from logistics firms, which are directly or indirectly dependent on the Port of Melbourne in Australia. A structural equation modelling (SEM) technique is used to examine the theorised relationships between various dimensions of inter-firm competitive rivalry and the tendency of spatial clustering of logistics firms in the vicinity of Port of Melbourne.FindingsThe results indicate that the inter-firm competitive rivalry increases significantly when logistics firms are spatially clustered. This effect is further augmented when they cluster around the port. Co-location of firms near the port tends to increase “bargaining power of buyers”, whilst indirectly affecting “competitive rivalry” via “threats of substitutes”. This indicates that co-location enhances the bargaining power of buyers through the greater availability of substitute services that in turn promotes competitive rivalry among firms. However, co-location has an insignificant effect on “barriers to entry” and “bargaining power of suppliers”. Low entry barrier thus favours high competitive rivalry among firms. Hence, this paper validates the Porter's cluster and five forces models that confirm the positive effect of port logistics clusters (PLCs) on bargaining power of buyers and indirect effect on competitive rivalry partially mediated through threats of substitutes.Practical implicationsThis study provides empirically grounded evidence for firms to evaluate co-location decision choices and help buyers and sellers to devise business strategies to enhance inter-firm competitive rivalry and bargaining power.Originality/valueThis is the first systematic attempt to empirically validate Porter's five forces model in the context of PLC. Furthermore, the conceptualisation of PLC concept both as spatial and functional constructs (i.e. dependency on port) is novel. This study thus has broadened the meaning of cluster from a geographic entity to a more useful functional construct to reflect inter-firm dependencies.

Supply chain risk management in the COVID-19 pandemic: strategies and empirical lessons for improving global logistics service providers’ performance

PurposeThe enormous impact of the COVID-19 pandemic showcases the key role of supply chain risk management (SCRM) in achieving and maintaining business performance, competitiveness and survival in the “new normal”. The purpose of this paper is to explore what impact the COVID-19 pandemic has had and may yet have on supply chains (SCs), which SCRM approaches have proved successful and how logistics service providers (LSPs) have applied the knowledge they have gained to improve their SCRM practices and resilience so as to prepare better for the next major disruption.Design/methodology/approachThis paper combines an extensive literature review with a multiple-case study of 10 internationally operating LSPs and how they have handled the impact of the COVID-19 pandemic so far. To bridge the research-practice gap, this study draws on the dynamic-capabilities view and provide insights that are valuable to both academia and practice.FindingsThis study provides empirical evidence on the severe impact of the COVID-19 pandemic on SCs, which has posed several challenges to LSPs. The study identifies eight factors that are critical to the adaptive capabilities of LSPs and, therefore, to their resilience in extreme conditions. The findings of this study show that these factors determine whether an SCRM system is robust and agile enough to allow an LSP to anticipate potential disruption and to respond fast enough when disruption occurs. Specifically, this study finds that robustness and agility demonstrably strengthen business performance, while learning from experience proves key to reconfiguring an SCRM design in response to acute disruption.Originality/valueThis paper is among the first to provide rich, empirical and practically applicable insights into the impact of the COVID-19 pandemic on business in relation to SCRM. These novel insights offer inspiring opportunities for further research.

Learning-based dynamic capabilities in closed-loop supply chains: an expert study

Purpose Product returns information gives firms an opportunity for continuous strategic adaptation by allowing them to understand the reasons for product returns, learning from them and improving their products and processes accordingly. By applying the Dynamic Capabilities (DCs) view in the context of closed-loop supply chains (CLSC), this study explores how firms can continuously learn from product returns information.Design/methodology/approach This study adopts a qualitative Delphi study-inspired approach. Experts from industry and academia are interviewed in two interview rounds. First round of interviews are based on extant research, while the second round allows the experts to elaborate and correct the results.Findings This study culminates into a conceptual model for incremental learning from product returns information. The results indicate incremental learning from product returns can potentially lead to a competitive advantage. Additionally, the authors identify the sources of information, capabilities along with their microfoundations and the manifestations of product return information. Three propositions are formulated embedding the findings in DC theory.Research limitations/implications This study supports extant literature in confirming the value of product returns information and opens concrete avenues for research by providing several propositions.Practical implications This research elucidates the practices, processes and resources required for firms to utilize product returns information for continuous strategic adaptation. Practitioners can use these results while implementing continuous learning practices in their organizations.Originality/value This study presents the first systematic framework for incremental learning from product returns information. The authors apply the DC framework to a new functional domain, namely CLSC management and product returns management. Furthermore, the authors offer a concrete example of how organizational learning and DC intersect, thus advancing DC theoretical knowledge.

Innovation-oriented dynamic capabilities of logistics service providers, dynamic resilience and firm performance during the COVID-19 pandemic

PurposeThe purpose of this paper is to use a theoretical framework to investigate the relationships between different innovation-oriented dynamic capabilities, dynamic resilience and firm performance among logistics service providers (LSPs) and in-house logistics departments of industrial companies during the coronavirus disease 2019 (COVID-19) pandemic.Design/methodology/approachThe conceptual theoretical framework relies on the dynamic capabilities framework (DCF) and the relational view (RV), which are rooted in the resource-based view (RBV). It is hypothesized that the dynamic capability to innovate reinforces the dynamic capability to adapt and to recover in highly dynamic and vulnerable environments during the pandemic. This allows LSPs to successfully create new services and respond to the changing market circumstances in terms of logistics service quality (LSQ) and firm performance. Data were collected from 83 LSPs and 30 in-house logistics departments via an online survey. The study determined the general strength and direction of the relationships between latent variables. A correlation analysis was utilized to establish statistical significance of the results.FindingsIn this study, a range of innovation-oriented capabilities for achieving more dynamic resilience were bundled in a conceptual framework and were found to be statistically significant for LSQ and firm performance. They are the capability to distribute new knowledge, to train employees effectively, to develop cross-functional collaboration within the firm, to develop inter-firm relationships with business partners on a long-term basis as well as to learn from rivals, and to pursue a win-win relationship with them.Research limitations/implicationsThe results of the study do not imply that the identified capabilities are the only ones relevant to increasing dynamic resilience during the pandemic. In October 2020, the COVID-19 pandemic was at different stages in different countries, so that the level to which firms were affected varied, and although the data were collected during one month only, due to the high dynamics of the pandemic, data were collected during different stages of disruptions, even among respondents in the same country. This study was set in the context of COVID-19, and it could not be proved whether the conceptual framework is generalizable to other crises or particular industries, but it would be worthwhile to examine this in the future. Finally, it was not tested whether LSQ mediates the relationship between innovative capabilities and firm performance during the pandemic.Practical implicationsThe results help managers with regard to their strategic and operational decisions in relation with COVID-19. These findings are useful for executives and logistics managers to improve these capabilities to gain a competitive advantage during pandemic and to find their strengths and weaknesses to develop critical capabilities for situations with a high turbulence and dynamic in their environment, and therefore provide a path for improvement.Originality/valueThis paper operationalizes a multi-theoretical conceptual framework in the context of logistics management (LM) and supply chain management (SCM). This conceptual framework was empirically tested.

Analysing developing countries approaches of supply chain resilience to COVID-19

PurposeThe Covid-19 pandemic has made it essential to explore the resilience factors specific to developing regions, not only because they pose threats of extreme poverty and offer a novel context but also because they play an important role in globalisation.Design/methodology/approachA mixed-method approach was undertaken to address this novel pandemic situation. First, an open-ended structured questionnaire was developed, and data were collected from three neighbouring emerging economies: Pakistan, India and Iran. Experts' perspectives on vulnerabilities, response measures, resilience and restoration of supply chain activities, and the role of social capital were collected. Second, building upon the findings from phase one of the studies, a quantitative structured questionnaire using the supply chain operational reference (SCOR) model was used to collect data in a structured manner. This quantitative data were further analysed using frequency and contingency analysis.FindingsThe findings from the first phase of the study inductively derive 36 resilience categories. Later, the contingency findings show that supply chain (SC) disruption is a major vulnerability for emerging economies, whereas solutions offered to combat it lay in the reconfiguration of resources, such as financial, technological, human, information and material. Additionally, supply network structure and social capital play an integral part in making SCs resilient against disruption.Research limitations/implicationsThe respondents comprise the academics/SC researchers, which make the findings interesting though they lack the industrial experts' perspectives, directly. Nevertheless, the propositions can be tested in industrial settings to see whether the results are limited to a specific industrial setting or are rather generalised.Practical implicationsSimilarly, practitioners and policy makers can incorporate the SCOR metrics/factors outlined in this study into their performance measurement systems and ensure continuous monitoring for firm's resilience.Originality/valueThe study offers a holistic understanding of the developing regions' approaches to Covid-19. The paper also takes a social capital perspective to explain firms' resilience in these emerging economies.

Supply chain resilience: A review, conceptual framework and future research

PurposeThe study identifies nine important research areas and critically maps the structural relationships among supply chain resilience (SCRES) dimensions, namely, vulnerabilities, capabilities, strategies and performance metrics. The analysis also revealed various influential authors, journals, institutions and trending articles, across SCRES literature.Design/methodology/approachThis study performs a bibliometric analysis of 771 articles published over the 32 years from 1988 to 2020, and network analysis in combination with content analysis of 90 most cited articles published in research fronts of SCRES.FindingsThe results demonstrate the underlying research areas within the SCRES, which are clustered into nine research themes: (1) conceptual development of SCRES, (2) recent developments of designing resilient supply chain (SC) networks, (3) focus on identifying drivers of SC vulnerability and risks, (4) impact of risks on network resilience, (5) risk assessment to avoid breakdowns/disruptions, (6) measuring resilience approaches/drivers to improve SC performance, (7) building resilient capabilities by integrating other SC dimensions, (8) quantification of SC network and (9) emphasis on developing robustness in SC networks.Practical implicationsThis research offers implications for classifying the works in literature based on bibliometric information and network analysis techniques. This can help researchers and practitioners to understand the prominent areas in SCRES and provide guidelines for future research in this area.Originality/valueThis study provides an overview of the evolution of SCRES over time in the domain of supply chain management and also outlines a future research agenda claimed by the trending articles to encourage further investigations in the field of SCRES.

Supply chain integration for middle-market firms: a qualitative investigation

PurposeThis research seeks to identify the motivations, means and outcomes of supply chain integration (SCI) among firms in the middle market (i.e. those with annual revenues between US$10m and US$1bn). These firms often interface with larger, more powerful firms in the supply chain – both suppliers and customers. Understanding how these firms are challenged and benefit from integrative mechanisms in supply chain relations can lead to better outcomes more often.Design/methodology/approachThe research utilizes an online focus group methodology featuring 39 participants. The participants were able to interact in written form with a professional moderator, as well as each other, over the course of three days.FindingsThe research presents evidence that firms in the middle market adopt SCI as a response to pressure from customers and suppliers. These firms also view technology as a primary means of achieving integration. Despite their disadvantageous size position relative to larger customers and suppliers, firms in the middle market achieved positive outcomes from integration.Research limitations/implicationsBecause of the specific context of middle-market firms, this research may lack generalizability. However, providing contextualization regarding firm size contributes specificity to the large number of studies detailing the challenges and benefits of SCI.Practical implicationsManagers of firms in the middle market should find value in this study as it explicates the possible benefits their firms may realize through integration with customers and suppliers. Moreover, this research outlines several of the possible means through which integration can be achieved. Further, managers in smaller and larger firms can better understand the motives and needs of middle-market companies with which they interact.Originality/valueDespite voluminous literature on SCI, this paper provides context-specific findings by isolating the implications of SCI to firms in the middle market.