PurposeUsing the assumptions of the resource-based view, relational view and swift, even flow theories and the overarching principles of supply chain management, the study aims to test the role of information technology (IT) capability (cross-functional application, supply chain application and data consistency) in enabling supply chain integration (SCI; internal, customer and supplier integration) and the impact of SCI on firm's operational performance in terms of quality, delivery, production cost, inventory level, customer service and product-mix flexibility.Design/methodology/approachThe structural equation modeling approach is used to test theoretical predictions underlying the relationship among dimensions of IT capability, SCI and operational performance based on data obtained from senior executives of 108 large manufacturing firms listed in the Tokyo Stock Exchange.FindingsThe results suggest that IT capability has positive impact on SCI, except for data consistency, which is found to have negative impact on internal integration. The results further indicate that SCI, especially customer integration, has positive and significant impact on all operational performance indicators.Practical implicationsThe findings inform future initiatives associated with the SCI improvement via specific IT capabilities. When undertaking such initiatives, managers are advised to consider the differential impact of the following IT capabilities on SCI: cross-functional applications, supply chain applications, and data consistency capability.Originality/valueThe study makes an empirical contribution to the body of knowledge by demonstrating the value of the multidimensional representation and analysis of IT capability, SCI, and operational performance given a differential and even opposed influence by some of the dimensions in specific business contexts.

The general assignment problem is a classical NP-hard (non-deterministic polynomial-time) problem. In a warehouse, the constraints on the equipment and the characteristics of consecutive processes make it even more complicated. To overcome the difficulty in calculating the benefit of an assignment and in finding the optimal assignment plan, a simulation-based optimization method is introduced. We first built a simulation model of the warehouse with the object-oriented discrete-event simulation (O2DES) framework, and then implemented a random neighborhood search method utilizing the simulation output. With this method, the throughput and service level of the warehouse can be improved, while keeping the number of workers constant. Numerical results with real data demonstrate the reduction of discrepancy between inbound and outbound service level performance. With a less than 10% reduction in inbound service level, we can achieve an over 30% increase in outbound service level. The proposed decision support tool assists the warehouse manager in dealing with warehouse worker allocation problem under conditions of random daily workload.

We find that avatar design can reduce algorithm aversion, which is the tendency of decision makers to ignore advice received from an algorithm after the algorithm makes an error. When the facial features of an avatar exhibit high levels of competence, algorithm aversion can be reduced relative to no avatar or a less competent-looking avatar. Humanizing the financial advice from an algorithm with an avatar that promotes the perception of competence effectively reduces algorithm aversion and can enhance reliance on the financial advice of robo-advisors.

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