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Purpose -The purpose of the paper is to present an empirical study on the logistics innovation capability and its impacts on the supply chain risk in the Australian courier firms. Based on the resource-based review, logistics innovation capability provides valuable insight into mitigating supply chain risks in the Industry 4.0 era. Design/methodology/approach -The research model focuses on the relationships between logistics innovation capability and supply chain risk. Partial least squares approach for structural equation modelling is used to validate the research model by empirically analysing survey data.Findings -The empirical result shows negative relationships between logistics innovation capability and supply chain risks. These relationships may imply that firms can mitigate the negative impacts of supply chain risks by developing logistics innovation capabilities. The findings demonstrate the applicability of logistics innovation capability for mitigating supply chain risks in the Australian courier firms. Originality/value -There are very few empirical studies on the mitigating supply chain risk through logistics innovation capability. The empirical results provide an insight into innovation management and risk management in logistics and supply chain. This insight offers practical guidance for developing and deploying logistics innovation capability to support and enable supply chain risk management strategies in the Industry 4.0 era.

Purpose Developing strategic relationships with third-party logistics (3PL) providers has long been one of the key challenges in automotive supply chains. The purpose of this paper is to propose a new approach for evaluation and indexing 3PL providers using the Kano model. Design/methodology/approach The statistical population used in this research comprises managers from the Iranian automotive industry. The Kano evaluation approach is used to analyze the data collected and to classify the criteria used in selection of the preferred 3PL providers. Findings The results suggest that the proposed framework, based on the Kano classification, can be a powerful tool for the automotive industry in evaluating 3PL providers. Moreover, the analyses indicate that 3PL providers need to improve their service offering in aspects that are to be found in the Kano model’s requirements, namely, must-be, one-dimensional and attractive. Originality/value This study contributes to the supply chain management literature by being the first to classify selection indices of 3PL providers in the automotive industry using the Kano model.

Transportation disruption, a common source of business interruptions, can cause significant economic loss to a lean supply chain. This paper studies a lean, two-stage suppliermanufacturer coordinated system where a sudden disruption interrupts the transportation network, creating delivery delays, and product quantity losses. We develop a model to generate a recovery plan after a sudden disruption occurrence, to minimize the negative impacts of the disruption. At the same time, given the computational intensity and problem complexity, three heuristics based on the delivery delay and fractional quantity loss caused by a sudden disruption are developed. We conduct a number of numerical experiments to validate our proposed solution methods, and a scenario-based analysis to test the model and analyse the impact of sudden transportation disruption under three disruption scenarios. The performance of presented heuristics against the Generalized Reduced Gradient method are compared. The results reveal that the proposed heuristics can generate a recovery plan accurately and consistently.

This study aims to propose and empirically test a behavioural model of consumer perceptions of country-of-origin, brand equity, brand preference and purchase intention in the context of fashion brands in Iran. To provide a detailed understanding of customers' perceptions of purchase intention, a survey study was conducted. The research model is validated, and the developed hypotheses are tested using a structural equation model (SEM). Country-of-origin is shown to be positively associated with brand equity. Consistent with expectations, our results reveal that brand equity influences brand preference and purchase intention. Findings also support the hypothesised relationship between brand preference and purchase intention. The present research is one of the pioneer studies that highlight the importance of purchase intention with regard to fashion brands in promoting a luxury market. This study contributes to the literature by developing and testing a comprehensive research model using SEM and offers important guidelines to international marketers who are planning to introduce their fashion brands to the Iranian market.

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Traditional clustering methods fail to accurately cluster the feature vectors of backers and recommend compatible crowdfunding projects mainly because of their sensitivity to the setting of the initial values. Following a hybrid machine learning approach, this study aims to provide a practical solution that can accurately match listed products/projects with registered backers through a crowdfunding platform. For this purpose, we examine how the Apriori algorithm can be used in conjunction with other tools to optimise traditional clustering and provide more accurate recommendations for crowdfunding projects. Focusing on potential projects listed in a major crowdfunding website, we first train the data obtained from the available list of backers. Through the association rules of the Apriori algorithm, we obtain the degree of association between the different backers of each project and evaluate the backers' final correlation strength according to their association degree obtained from various crowdfunding projects. The degree of association is used as a key index to cluster backers according to their similar characteristics. Next, we test the model and determine whether it can correctly classify the data in the test set based on the Apriori algorithm.Experimental results show that the applied model 90% accuracy, precision, and recall of the applied model. The proposed solution outperforms the other five benchmark methods in connecting the right crowdfunding projects to the relevant backers.

Despite the substantial efforts of governments in promoting sustainable development, there exists a considerable debate regarding the environmental policy making approach under information ambiguity and competition. This study investigates market competition between a green and a non-green supply chain (SC) under two government regulation policies, namely, selling price and production quantities. To tackle the policy making challenges, a fuzzy game theoretical model was employed in a centralized and decentralized SC setting. The results revealed that SCs always achieve a higher expected profit under a decentralized structure, regardless of the type of the governments intervention policy. Also, the government’s policy making success was found to be highly dependent on the channel leadership, market competition, and the SC structure. Our findings suggest that the policy makers’ objectives in reducing environmental pollution and increasing revenue are highly achievable, without risk of losing channel coordination and maximum level of efficiency.