Rise and Fall of an Information Technology Outsourcing Program: a qualitative Analysis of a Troubled Corporate Initiative

 
Tensions and gaps in outsourcing diffusion literature.
Rogers’s (2003) criticisms of 
innovation-diffusion research included pro-innovation bias, individual-blame bias, and recall 
problems. Innovation-diffusion research often suggests a pro-innovation bias that all members 

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of a particular group should rapidly adopt the innovation. The individual-blame bias is a 
tendency to emphasize individual responsibilities and factors versus systemic causes for failures 
or successes. Recall problems can occur during data gathering as researchers ask individuals to 
remember when they first encountered, adopted, or rejected an innovation. Alternatives to avoid 
this problem include surveying or interviewing potential adopters at multiple phases throughout 
the process, or even right at the point of adoption if possible (Rogers, 2003). 
While Rogers (2003) considers different biases in diffusion studies, Lunblad (2003) 
suggests the theory focuses primarily on diffusion and adoption by individuals rather than 
organizations, and therefore does not go far enough to address “whether and how the 
characteristics of an innovation interact to affect its adoption within organizations, or whether 
organizational type, size, or industry affect adoption” (p. 57). The dominance of “why” and 
“what” outsourcing-diffusion studies discovered in this literature review (i.e., Loh & 
Venkatraman, 1992; Hu et al., 1997) versus studies considering the impacts of “how” 
outsourcing strategies diffuse in organizations (i.e., Beverakis et al., 2009) would seem to 
support this criticism. If so, it suggests there is a research opportunity to extend Rogers’s work 
deeper into organizational studies by describing “the interaction between the innovation, the 
adopter, the social system, and the other influencers of adoption” (Lunblad, 2003, p. 59). 
McMaster and Wastell (2005) provide some of the sharpest criticism of Rogers’s 
innovation-diffusion framework by suggesting it is a modernistic grand narrative used for 
“
explaining and making sense of the world, and hence legitimating the existing order” (p. 388) 
and a collection of pseudo-scientific claims grounded in worldviews justifying colonial 
exploitations (
McMaster 2001). In the latter claim, McMaster (2001) suggested that 
characteristic colonialist behaviors, such as conquering, settling, and exploiting, parallel 

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“diffusionism” in practice. 
Rogers (2003) classified adopters into a normally-distributed bell curve of five 
categories: innovators, early adopters, early majority, late majority, and laggards. Where Rogers 
suggested these categories represented individuals’ rate of adopting new innovations, McMaster 
(2001) posited it as more accurate to flatten these groups into a binary pair of innovators and 
recipients. In the realm of this research, McMaster’s criticism suggests that the diffusion-theory 
(and isomorphism) approach is a type of “digital-age colonialism.” Thus, relying on a diffusion-
theory approach to change or innovation adoption downplays the impact of human foibles and 
costs common within the corporate domain. 
Beverakis et al. (2009) conducted a case study of one large multinational firm’s 
(ComputerInc) decision to enter into a large ITO agreement. While it did not directly reference 
Rogers’s (2003) innovation-diffusion framework, the authors did investigate the drivers behind 
the strategy and explored its unintended consequences. The strongest drivers for ComputerInc’s 
strategy were increasing competitiveness and reducing costs. The notable consequences caused 
by how ComputerInc executed its strategy included: survivor’s guilt among employees who did 
not lose their jobs, low employee morale, and communication problems. The authors suggested 
the consequences of ComputerInc’s outsourcing strategy impeded its ability to improve its 
competitive position and operations efficiency. 
Additional studies related to this dissertation include Hong and O’s (2009) case study of 
one Chinese firm’s failed attempt to outsource a portion of its IT department. The authors 
concluded that power inequalities and identity gaps between in-house and outsourcing staff 
created significant tensions between the two firms, which lead the cancellation of the entire 
outsourcing initiative. Clott (2007) focused on the experiences of mid-level project managers 

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tasked by senior management to implement offshore outsourcing arrangements. The project 
managers (each working at a different U.S. firm) suggested that their senior executives focused 
on achieving employee reductions but provided little communication or direction of the overall 
strategy. While these project managers did have some access to senior executives to report their 
progress, they frequently needed to “operate in an uncertain environment that requires them to 
process information which is complicated, novel, ambiguous or dynamic” (p. 491). Lacity and 
Rottman (2009) conducted a similar, albeit more comprehensive, study focused on project 
managers responsible for implementing outsourcing strategies. Their research concluded that the 
largest cause of outsourcing failure was firms understaffing the internal teams who were 
expected to implement the outsourcing strategies. 

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CHAPTER TWO 
THE SOCIAL THEORY OF INFORMATION TECHNOLOGY OUTSOURCING 
This chapter provides a review of the relevant analytic theory and how it is employed in 
this research. The discussion begins with organizational culture and power. Concepts in this 
section include Bourdieu’s habitus, capital, and fields (1972/1977, 1979/1984, 1983/1986, 1993), 
Lincoln’s taxonomies and anomalies within social structures (1989), Jackall’s (2010) 
bureaucratic ethic of corporate managers, and Harvey’s (1988) “Abilene Paradox.” In the next 
section, I discuss moral careers in information technology. Concepts in this segment include 
Goffman’s dramaturgy and impression management (1959) and moral career (1961), technical 
labor commodification and deskilling (Braverman, 1998), and infocentrism and information 
technology outsourcing (Brown & Duguid, 2000). I close the analytic theory discussion with a 
review of Kuhn’s (2012) structure of scientific revolutions. I give significant attention to the 
paradigm, puzzle solving, normal science, and anomalous elements of scientific revolutions.