Date of Award

Fall 12-1-2017

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Technology Management

Department

College of Technology

Abstract

This research brings together two streams of thought for first-line manager decision-making. The first is the quality system model, in particular, Lean operations. The second is Stakeholder Theory. Both streams have been identified as ways to improve value of the organization. Previous studies disagree regarding whether Lean and Stakeholder theory can work together. The potential problem of having a poor balance of Stakeholders and Lean waste is that exclusive focus on one may result in less awareness of the other, in which case value can be lost by the organization. This research investigates if both Lean waste and Stakeholder salience share a common language in the literature using data mining. This research surveys organizations that perceive themselves as Lean and have multiple diverse Stakeholders to determine whether Lean wastes and Stakeholder salience (priority) are considered the decision-making process. A Z-test compares proportions of Lean waste considered to proportions of Stakeholder salience. An ANOVA is done to see if organization type, position of a person within the organization, organization size, geographic location, or lean management maturity has an effect on the priority assigned to Stakeholder salience or Lean waste variants when making decisions. The final phase of this research is a proposed decision-making instrument that will weigh Stakeholder salience and Lean waste variants on an equitable level for First-line Managers’ decision-making. The major findings of this research are that Lean waste variants and Stakeholder salience are considered in decision-making but that Stakeholder salience is more important. This is iv independent of various factors. Stakeholder mapping using salience values adjusted for Lean waste provides a visually enhanced balanced approach allowing the decision-makers to know the impact of both, facilitating more precise input to their decision-making process. More precision in the decision-making process can lead to results that create improved value for the organization.

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