Where next for manufacturing productivity research? Propositions based on exploratory empirical investigation

Abstract

The purpose of this research is to develop empirically grounded propositions for further research into UK manufacturing productivity. Interviews were conducted with managers from strategic, tactical and operational levels from four manufacturing sectors to produce case studies. A modified strategic alignment theory framework was used to code, compare and contrast narratives on perceived productivity antecedents, definitions, compatibility with the definition from the UK Office for National Statistics, and vertical alignment issues within and across cases. In addition it was found that different key antecedents can facilitate and/or prevent strategic vertical alignment. Discussion reveals complex nuances in perceptions of manufacturing productivity and using the modified strategic alignment theory / productivity antecedent framework. In revealing the alignment or otherwise of productivity definitions at different levels within the firm, the paper reveals nine propositions for future research including definitions, skills, metrics, performance measurement systems, people and system centric perspectives, value-added perspective of productivity and the role of innovation.

Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School
Aston University (General)
Funding Information: The authors would like to acknowledge support of the UK Economic and Social Research Council (ESRC), the Productivity Insights Network https://productivityinsightsnetwork.co.uk/ and the Industry and Parliamentary Trust (IPT, Houses of Parliament, UK) for
Uncontrolled Keywords: productivity,efficiency,strategic alignment,manufacturing,case study,Business, Management and Accounting(all),SDG 8 - Decent Work and Economic Growth
Publication ISSN: 1758-6658
Data Access Statement: Interview transcriptions are available as an anonymised ESRC dataset (MacBryde et al., 2019) and can be made available on request.
Last Modified: 18 Oct 2024 07:06
Date Deposited: 13 Aug 2024 14:59
PURE Output Type: Article
Published Date: 2024-07-27
Accepted Date: 2024-07-27
Authors: Clegg, Ben (ORCID Profile 0000-0001-7506-5237)
MacBryde, Jillian C.
Ball, Peter D.
Masi, Donato (ORCID Profile 0000-0002-4553-3244)
Mullen, Helen
Despoudi, Stella

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