Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

5.2 ECONOMICS AND BUSINESS, Business and Management.

Publication Details

Presented at the 20th European Conference on Research Methodology for Business Management ECRM 2021, 17 ‐ 18 June 2021. A Virtual Conference hosted by ACI and supported by University of Aveiro, Portugal.

Abstract

How might Absorptive Capacity (ACAP) (Cohen & Levinthal 1990,,Song et al. 2018) contribute to indigenous firm innovation and growth and how might the effects of this construct be evaluated at both firm and policy level? This paper demonstrates how a mixed methods research design and data analysis strategy can address the research question outlined above. Within the ‘mixed methods’ research genre, the design approach argued for here is for a ‘sequential mixed methods research’ approach. This is where one methodology is followed sequentially by another to add robustness to the overall findings from a study. The approach can also be described as a multi-phase research design depending on the number and type of research techniques utilised. Adopting this methodology however allows for data triangulation possibilities as the combination of archival data (secondary) and interview data (primary) gives complementary perspectives on the same proprietary dataset of cases (n=20)(Eisenhardt1989). Combining this triangulation of data with the proposed methodological triangulation can further strengthen the internal validity of the overall findings in the study. The data analysis strategy suggested here employs firstly an exploratory cross – case analysis (Yin 2018), using thematic coding (Saldana 2013) to identify the underlying ACAP mechanisms at play. This is then followed sequentially by a Qualitative Comparative Analysis (Rihoux and Ragin 2009). QCA is a data analysis technique which is used for determining which logical conclusions a data set supports. This proposed research design is applicable to complex research settings where a study can deliver findings on the ‘contribution’ of mechanisms underpinning ACAP (Cordero & Ferreira 2019), to the innovation and growth performance of the firm rather than assigning precise ‘attribution’ or impact measures to individual factors or variables.


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