Abstract

Abstract
This study identified and characterized the factors influencing managers’ intentions to adopt collaborative robots (cobots) in manufacturing companies. Based on a conceptual framework that integrates three technology adoption theories (Diffusion of Innovation, Technology-organization-environment and Institutional theory) and following an exploratory qualitative research design, this paper identifies 39 factors influencing the intention to adopt cobots in three contexts (internal, external and technology). Twelve of these factors are new as contrasted with previous literature. The findings of this study can assist organizations in their process of adoption of cobots and in the development of managerial practices that consider the role of these factors. © 2020 Elsevier B.V.

Abstract
Purpose: This paper investigates the effect of the fit between supply and demand uncertainty (SDU) and supply chain responsiveness (SCR) (SC fit) on business and innovation performance in Brazilian companies. Design/methodology/approach: The study presented an analysis carried out on an empirical study based on a sample of 150 manufacturing companies. Business and innovation performance of companies with different types of SC fit (high–high and low–low fits) and misfit (positive and negative) are compared and discussed. Findings: The results indicated that SC fit had a positive effect on both business and innovation performance. Further analyses suggested that companies with SC fit present similar business performance, independent of the level of SDU that characterizes the environment where they compete, while companies in environments with higher levels of uncertainty tend to present superior innovation performance. Companies with positive and negative misfit present similar performance. Originality/value: An analysis of the literature showed that there is no consensus when it comes to the definitions and measurements of SC fit. The paper investigates the effects of SC fit on business and innovation performance, while previous empirical studies have mainly addressed its impact on financial performance. Moreover, this study compares the effects of two types of fit and two types of misfit and assesses SC fit in Brazilian manufacturing companies, analyzing the context of an under-researched reality. © 2020, Emerald Publishing Limited.

Abstract
Purpose: To study how supply chain decision makers gather, process and use the available internal and external information when facing supply chain disruptions. Design/methodology/approach: The paper reviews relevant supply chain literature to build an information management model for disruption management. Afterwards, three case studies in the vehicle assembly sector, namely cars, trucks and aircraft wings, bring the empirical insights to the information management model. Findings: This research characterises the phases of disruption management and identifies the information companies use to recover from a variety of disruptive events. It presents an information management model to enhance supply chain visibility and support disruption management at the operational level. Moreover, it arrives at two design propositions to help companies in the redesign of their disruption discovery and recovery processes. Originality/value: This research studies how companies manage operational disruptions. The proposed information management model allows to provide visibility to support the disruption management process. Also, based on the analysis of the disruptions occurring at the operational level we propose a conceptual model to support decision makers in the recovery from daily disruptive events. © 2020, Emerald Publishing Limited.

Abstract