Why the Same CRM Thrives in One City and Dies in Another

A consulting firm installs the same CRM platform in two companies in the same industry. Same software, same training materials, same implementation timeline. One company sees adoption rates above 80 percent within a year. The other watches its sales team treat the system like a mandatory data-entry chore, entering just enough to satisfy the manager. Same technology. Different organizations, different environments, entirely different outcomes.

I kept noticing this pattern when reading about organizational adoption in my comps preparation. The TOE framework from Tornatzky and Fleischer (1990) is the simplest lens for understanding why. It says technology adoption is shaped by three interacting contexts: the technological, the organizational, and the environmental. The technology context covers what innovations are available and what the firm already has in place. The organizational context covers firm size, management structure, human resources, and slack resources. The environmental context covers industry competition, regulatory requirements, and market uncertainty. Each context can facilitate or block adoption independently.

That sounds almost too obvious to be useful. Of course the technology itself matters, of course the organization matters, of course the environment matters. But the reason TOE has persisted in the IS literature for over thirty years is precisely that researchers and practitioners keep forgetting one of the three. Every "best practices" report about technology adoption I have read focuses on the technology and maybe the organization, then treats the environment as background noise. TOE says the environment is not background. It is a full context, equal in weight, and it can override the other two.

Consider the difference between small business CRM adoption and enterprise CRM adoption. A small business with five salespeople, a lean management structure, and a founder who makes every technology decision is not dealing with the same organizational context as a multinational with regional IT directors and a procurement process that takes eighteen months. The technology context differs too. The small business might be choosing between two cloud CRM products. The enterprise is choosing between platforms that have to integrate with legacy ERP systems, data warehouses, and compliance frameworks that predate the CRM conversation by a decade. The environmental context shifts even more sharply. A small business in an unregulated market faces different pressures than a financial services firm operating under GDPR, SOX, and industry-specific data retention requirements. The same CRM feature that is a convenience in one setting is a compliance obligation in another. When I read through adoption studies, the pattern is clear: context determines whether adoption becomes meaningful use or forced compliance.

Regulated industries make this especially visible. Healthcare organizations adopting electronic health records were not making a purely technological choice. They were responding to coercive isomorphism, external regulatory pressure from HIPAA and Meaningful Use mandates that DiMaggio and Powell (1983) would classify as the coercive type of institutional pressure. The environmental context, in TOE terms, included penalties for non-compliance and financial incentives for adoption. The technology was available, and many organizations had the resources. But the reason adoption happened at scale in healthcare was environmental pressure, not organizational readiness or technological superiority. Some hospitals implemented EHR systems that clinicians barely used outside mandatory documentation. They adopted because they had to, not because the technology fit their workflows or because the organization was prepared to absorb it. That gap between adoption and meaningful use is exactly what the TOE framework predicts but cannot explain by itself.

This brings me to the most important caveat about TOE. Tornatzky and Fleischer (1990) gave us a framework, not a theory. My comps professor put it bluntly: "It's a bucket, not a theory." TOE identifies three contextual buckets that matter for adoption, but it specifies no causal directionality, no mechanisms through which these factors operate, and no testable propositions about relationships among the three contexts. It tells you where to look, but not what you will find or why. This is not a flaw in the framework. It is the frame. TOE is useful precisely because it organizes your thinking before you theorize. But it cannot stand alone as an explanation.

When you pair TOE with institutional theory, you get a mechanism. The environmental context bucket in TOE becomes the entry point for coercive, mimetic, and normative pressures. The organizational context becomes the space where absorptive capacity, managerial support, and slack resources either amplify or dampen those pressures. The technology context becomes the terrain where perceived relative advantage and compatibility (from diffusion of innovation theory) either align with or contradict institutional signals. TOE organizes the factors. Institutional theory explains why they converge on the same technology. As I wrote about earlier, institutional isomorphism is why everyone copied everyone else's AI strategy. TOE tells you which context the pressure enters through.

The small business versus enterprise contrast also reveals something about where generic advice breaks down. Best-practice consulting reports love to prescribe "align technology with business strategy" or "secure executive sponsorship." Both are sound, and both sit comfortably inside the organizational context of TOE. But they ignore the environmental context entirely. A small business in a competitive market with no regulatory pressure faces mimetic isomorphism, the urge to copy successful competitors, without any coercive push. Their adoption is entirely voluntary and therefore entirely dependent on perceived benefit and organizational readiness. A regulated enterprise faces coercive pressure that makes adoption nearly mandatory regardless of perceived benefit. The same CRM adoption advice, "secure executive sponsorship," means something fundamentally different when the CEO's mandate is reinforcing an existing environmental requirement versus when it is trying to create momentum where none exists.

The DePietro, Wiarda, and Fleischer chapter inside the Tornatzky and Fleischer volume is the one most IS researchers cite when using TOE for IT adoption specifically. The standard citation convention uses Tornatzky and Fleischer (1990) for the framework overall, and the DePietro et al. attribution comes up when the question asks specifically about the IT adoption context within that volume. The point is the same either way: adoption is multi-contextual, and no single context explains the outcome.

I think the reason TOE keeps surfacing in my comps reading is that it names the thing that most technology implementation stories refuse to name. We want adoption to be about the technology. We want the better product to win. We want the features and the UI and the integration capabilities to determine the outcome. TOE says, not so fast. The technology context is one of three, and it may not even be the most important one. The organizational context determines whether the people in the firm can actually absorb and use what the technology offers, which is exactly what absorptive capacity addresses. Cohen and Levinthal (1990) showed that organizations with higher prior related knowledge learn faster from new external information. A firm that has never used data-driven decision making cannot absorb an analytics platform, no matter how good the platform is. I wrote about why bought tools alone fail when the organization has no prior knowledge to connect them to. The organizational context in TOE is where absorptive capacity lives.

The environmental context determines whether adoption is even a choice. In regulated industries, adoption is often a compliance requirement. In highly competitive markets, adoption can be a survival mechanism driven by mimetic pressure. In professional fields with strong normative standards, adoption signals legitimacy. As I discussed in a previous post about why institutions copy each other, these pressures are not about the technology at all. They are about conformity, legitimacy, and survival.

Where TOE falls short, and this matters for anyone using it, is the next step after identification. You have three buckets. You have factors in each bucket. Now what? TOE does not tell you how the factors interact, which ones dominate, or what mechanism connects a factor in the technology context to an outcome in the organizational context. For that, you need a theory of the mechanism. Institutional theory for legitimacy pressures. Structuration theory for how technology and practice co-evolve after adoption, something I explored when writing about how structuration theory explains why the same tool behaves differently across departments. Affordance theory for what the technology enables specifically for which actor with which goal. Absorptive capacity for differential learning. TOE gives you the landscape. These other theories give you the vehicle.

The practical takeaway is not complicated. If you are implementing technology in an organization, map all three contexts before you start. What technologies are available and compatible with existing infrastructure? What organizational resources, skills, and management support exist? What regulatory, competitive, and market conditions shape the decision? Then, when the same CRM thrives in one city and dies in another, you will not be surprised. You will know where to look. The question TOE cannot answer is why what you find in those buckets matters, and that is where the real theory begins.