Background and Methods

The study population for my research on LM is the United States hospital industry; specifically emergency departments. Since a strong contextual understanding is important when studying organizational change processes (Pettigrew, 1990) and capabilities (Ethiraj et al., 2005), studying a single industry within a single country allows me to devote sufficient time to

understanding the complex social, cultural, operational and financial processes more deeply (Yin, 2009) and facilitate comparisons among multiple organizations (Fox-Wolfgramm, Boal & Hunt, 1998). While the study is focused in one industry and in one country, the hope is that further research in other industries and cultures will follow as part of a greater research stream of study post-thesis and permit enhanced analytical generalization to other areas of LM adoption.

Since I am exploring a relatively new research area, and not specifically attempting to determine causality between variables at this initial stage of my research, case studies are an appropriate methodology (McCutcheon & Meridith, 1993; Yin, 2009). “Case research has consistently been one of the most powerful research methods in operations management, particularly in the development of new theory.” (Voss et al., 2002); case study research lends itself well to building new theory and elaborating existing theory (Eisenhardt, 1989; Lee, Mitchell & Sablynski, 1999; Eisenhardt & Graebner, 2007; Yin, 2009). Since I had a pre- conceived idea of my descriptive model a priori to my case study research, the objective of this research phase was not purely inductive. However, my intention was to learn from interviewees to either confirm or refine the a priori model, thus an aspect of theoretical induction was a key objective of this research phase. Therefore, as a basis for inductive theory development, I used a multi-site case study design as a first stage in my research.

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Building on both Eisenhardt’s (1989) and Yin’s (2009) approaches to designing and building theory from case studies, I utilized a non-probability, information-oriented sampling (Flyvbjerg, 2006) of hospitals. The goal of information-oriented sampling is not the

representative capture of all possible variations, but to gain a deeper understanding of critical cases to facilitate the development of a descriptive framework for the research under study. Information-oriented sampling can be viewed as a technique of data triangulation: using

independent pieces of information to get a better fix on something that is only partially known or understood (Ragin, 1994). Information-oriented sampling enables the obtaining of information on unusually extreme or strategically (in relation to the phenomenon under study) critical cases and improves the understanding of the limits of existing theories (Flyvbjerg, 2006). This design explicitly captures the viewpoints of multiple stakeholders and controlled for potential biases from a single data type (Jick 1979; Eisenhart 1989; Yin 2009).

I conducted 70 one-hour interviews utilizing a semi-structured interview guide (see Figure 3.2) with actors (differentiated hierarchal standing, functional or departmental area, role in project, and experience in hospital) who had experienced diverse perspectives of the LM initiatives within their respective organizations. These interviews were the primary source of the case study data I collected. While I was not developing theory in a purely grounded theory method, the fundamental tenets (Corley & Gioia, 2011) of grounded theory (Glaser & Strauss, 1967; Corbin & Strauss, 1990) were followed permitting the gradual discovery of enhanced theory from the data (Glaser & Strauss, 1967). I continually searched to find consistencies and constancies within and across cases as a means to generate meaning from the data. I generated representative understanding and analytically generalizable insights that led, along with scrutiny of the scholarly literature, to theoretically-supported hypotheses and improvements to my basic

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FIGURE 3.2: CASE STUDY INTERVIEW GUIDE

What has been your role in the lean initiative at the organization? How long have you been involved?

How many hours per month have you dedicated to the initiative? In what way have those hours been allocated? How has your direct supervisor supported your efforts?

How would you describe your experience in the initiative to date?

How has this experience differed from other similar initiatives you have participated in or been effected by in the past?

In your own words, what are the key objectives of the Lean initiative at the organization?

How do the projects you have participated in contribute or fit in with those higher level objectives? Describe the process of the initiative you were involved in from opportunity identification to potential solution?

How is the effectiveness of the overall initiative and your project evaluated or assessed? How was the solution implemented or deployed? Was this effective?

What or who are the enablers of deployment? What or who are the barriers or inhibitors of successful implementation?

What is the plan or strategy for ensuring the successful ongoing longevity of the initiative?

How involved or visible has the senior management team been in the lean initiative? How involved is your own direct supervisor?

How has the patient experience been impacted by your project? What are the financial benefits of your project? What other tangible benefits are there?

What suggestions would you have to improve the speed of deployment? Ease of implementation? Long- term sustainability of the initiative?

Why is lean important to your hospital?

How has your involvement in this initiative shaped your thinking and approach to opportunity identification and problem solving?

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conceptual model. “Theory is emergent in the sense that it is situated in and developed by recognizing patterns of relationships among constructs within and across cases and their underlying logical arguments” (Eisenhardt & Graebner, 2007: 29). Implicit in grounded theory tenets is the assumption “that the people constructing their organizational realities are

‘knowledgeable agents,’ namely, that the people in organizations know what they are trying to do and explain their thoughts, intentions and actions” (Gioia, Corley & Hamilton, 2013: 17). The ultimate measure of the quality of my case study research (and the interviewees’ knowledge) rests on the fit between the empirical observations and the conceptual categories I report as informed by the data (Locke, 2001). This case study research enhanced my understanding and explanation of constructs, their relationships to each other and built a natural bridge to the confirmatory phase of my research where I empirically tested those hypotheses utilizing a larger sample surveying approach and structural equation modeling to generate findings.

I treated each individual case study location as a separately (Eisenhardt, 1989; Yin, 1989), yet as I progressed through the interviewing process, thematic patterns began to emerge which informed potential adaptation of my descriptive model. By conducting interviews at hospitals that were at various experiential stages of LM program deployment and with individuals with a variety of roles and exposures in those programs, I was able to observe

diversity in viewpoints that informed a more well-rounded perspective of the phenomenon. After the first three hospital case studies, I modified my conceptual research model. At the fourth and final case study, I used the same interview guide, but shared the proposed model at the end of the interview to gain additional perspectives on my emerging theory.

All hospitals and all interviewees were promised anonymity (Gioia, Corley & Hamilton, 2013) and as such I will not divulge their identities in this thesis. Letters of consent were signed

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by all interviewees prior to the interview and the promise of anonymity within the research and with their fellow hospital employees was guaranteed. Prior to consent being given, a researcher bio and letter of information (see Appendix A) was sent to all interviewees along with a copy of the consent form (see Appendix A) to be collected at the start of the interview. Consent forms were stored separately without any coding information on them. Interviewee identities and contact information was securely stored for potential subsequent communication purposes but not shared with anyone within the organization. I did not record the interviews (owing to confidentiality concerns), but I took extensive notes and subsequently transcribed them to electronic format (Microsoft Word) as soon as possible after the interviews. Data recorded electronically was subsequently stored on a password protected account on Ivey School of Business PhD server. A separate file with respondent position, initials and name was stored on my personal hard drive without data. Field notes were secured in locked office until backed up electronically and then shredded.These electronic interview notes are the case study exploratory data for my analysis.