- Title
- Supply chain sensing for competitive advantage: a dynamic capabilities and information processing perspective
- Creator
- Odukoya, Oluseye
- Relation
- University of Newcastle Research Higher Degree Thesis
- Resource Type
- thesis
- Date
- 2020
- Description
- Research Doctorate - Doctor of Philosophy (PhD)
- Description
- Identifying and anticipating changes in the market environment remain a key issue for organizations seeking to sustain their competitiveness. This is because of the increasing levels of volatility, uncertainty, complexity and ambiguity of today’s business environment as a result of globalization, advances in technology, and changing customer needs. Hence, firms are under pressure to be responsive to such dynamism. In order to be responsive, firms need to be able to transform existing capabilities. However, transforming capabilities takes time. Thus, engaging in the proactive activity of sensing provides firms with the time needed to transform capabilities in order to address environmental dynamism. Sensing is defined as the continuous scanning and generation of data about the business environment in order to detect strategic opportunities and anticipate potential threats (Helfat & Raubitschek, 2018; Teece, 2018b). Sensing requires probing, evaluating and translating data generated into valuable insights by continuously engaging in information processing activities, supported by internal organizational capabilities (Winter 2018). Sensing is one of the three components of dynamic capabilities – sensing, seizing and reconfiguring. Of the three components, sensing has received the least amount of research attention and very little theoretical development. Drawing on the dynamic capabilities theory (Teece & Pisano, 1994; Teece, Pisano & Sheun, 1997; Teece, 2007) and organizational information processing theory (Galbraith, 1973, 1974), this thesis explores the sensing element of dynamic capabilities by investigating the extent to which the supply chain may serve as a sensing mechanism. Therefore, in developing a research approach that spans both theory building and theory testing, this thesis follows a three-step research approach which includes (1) theory building; (2) theory refinement; and (3) theory testing. The first step aimed at theory building involved a review of extant literature to develop a preliminary theoretical model. The second step aimed at theory refinement involved refinement and validation of the preliminary theoretical model through a multiple case study approach. The multiple case study approach involved face-to-face interviews with executives of eight Australian manufacturing firms located in the Hunter Valley region of New South Wales, Australia. The third step aimed at theory testing involved an evaluation of the refined model through a survey of 421 Australian manufacturing firms. The firms were recruited through Qualtrics – an online survey recruitment platform. Findings from the case studies provide detailed insight into the importance of supply chain sensing capabilities in enabling firms to identify opportunities and threats in the business environment, resulting in the development of a refined research model. The initial research model argued that sensing performance affects firm performance. Findings from the survey showed that sensing performance had a significant but negative impact on firm performance. This finding was deemed to be theoretically not plausible. Consequently, it was decided to re-run the initial research model using insights from other studies. Specifically, the study draws on previous research that argued that the performance between strong and weak performers was different because they represented different populations (e.g., Powell, 1995). Using these insights, an alternative post hoc reframing was proposed and evaluated. This reframing revealed that there was evidence of significant different approaches to sensing based on performance. But the results were mixed. In light of these findings, this thesis concluded with several possible explanations that are left for other future research to investigate.
- Subject
- competitive advantage; dynamic capabilities; sensing; sensing performance; supply chain data; supply chain information; strategic supply chain management; supply chain sensing capabilities
- Identifier
- http://hdl.handle.net/1959.13/1410888
- Identifier
- uon:36252
- Rights
- Copyright 2020 Oluseye Odukoya
- Language
- eng
- Full Text
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