Narrative sequence methods offer the potential to advance research methods and develop a common vocabulary for theory development in international entrepreneurship. While variables-focused, variance-based methods currently dominate theory development, they are atemporal, yet entrepreneurship is what entrepreneurs do over time. We examine the assumptions of variance-based approaches and compare them to those of narrative methods, which leads to a discussion of the nature of causal mechanisms. We then illustrate the use of narrative sequence methods to identify some of the mechanisms underlying the internationalisation of an intermediary in the electronic component industry, where internationalisation is interpreted as a form of innovation and entrepreneurship. We illustrate how these methods, whose value is being increasingly recognised, allow us to introduce time, timing and temporal processes into the systematic analysis of business behaviour and evolution, and to generate usable knowledge for managers and policymakers. Copyright Springer Science+Business Media, LLC 2006Internationalisation, Mechanisms, Process, Research methods,

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This paper seeks to understand how we might identify the “underlying logics” and “deeper structures” that bring about change in phenomena. We argue that this represents a move from a classical perspective focusing on discrete exchange, and that this requires a processual or relational approach to understanding in contrast to a substantialist or variables-based approach. One way of advancing our understanding of the emergence of change is to consider the site of interaction. That is the interactional field where actors act and interact with other actors and entities as well as the broader environment; where resources are exchanged, imported or exported; where change is instigated and transferred across time and space. We suggest interactional fields are the sites of plasticity where change actually takes place. To understand the causal structure and processes taking place in an interactional field we draw on the concept of natural and social kinds. We discuss how interactional fields are located in time and space, which influence and are influenced by the trajectories of change and development. While we believe this applies to change in general we apply our thinking to organizational change.

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Purpose The rising of the sharing economy (SE) has lowered the barrier of purchase price to accessing many different products, thus changing the consumer decision paradigm. This paper addresses the challenge of assessing the life cycle impacts of SE systems in the context of this new consumer decision-making process. The paper proposes a methodological framework to integrate consumer preferences into the Dynamic Life Cycle Assessment (dynamic-LCA) of SE systems. Methods In the proposed consumer preference integrated dynamic-LCA (C-DLCA) methodological framework, system dynamics (SD) is used to combine consumer preference and the principal method, dynamic-LCA, which follows the ISO 14040 LCA framework. Choice-based conjoint analysis (CBCA) is chosen as the stated preference tool to measure consumer preference based on SE alternatives, attributes and attribute levels. CBCA integrates discrete choice experiments (DCE) and conjoint analysis features. Random utility theory is selected to interpret the CBCA results by employing multinomial logistics as the estimation procedure to derive the utilities. Derived utilities are connected in iterative modelling in the SD and LCA. Dynamic-LCA results are determined based on dynamic process inventory and DCE outcomes and then interpreted aligned with the SD policy scenarios. Results and discussion The C-DLCA framework is applied to assess the GHG changes of the transition to car-based shared mobility in roundtrips to work in the USA. Carpooling and ridesourcing are selected as the shared mobility alternatives based on different occupancy behaviours. Powertrain system and body style are employed as the fleet technology attributes and the latter as an endogenous variable. Dynamic-LCA results are generated considering the high battery electrical vehicle (BEV) adoption as the policy scenario, and results are measured against a service-based functional unit, passenger-kilometre. The model outcomes show a significant reduction in aggregated personal mobility-related dynamic-GHG emissions by transitioning to car-based shared mobility. In contrast to the use phase GHG emissions, the production phase emissions show an increase. The results highlight the importance of integrating consumer preference and temporality in the SE environmental assessments. Conclusions The proposed C-DLCA framework is the first approach to combine consumer preferences, SD and LCA in a single formulation. The structured and practical integration of conjoint analysis, SD and LCA methods added some standardisation to the dynamic-LCAs of the SE systems, and the applicability is demonstrated. The C-DLCA framework is a fundamental structure to connect consumer preferences and temporal effects in LCAs that is expandable based on research scope.