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Criteria for Adopting Information and Communication Technologies

2008 Edition

notes formebcenter

Business and Information Technologies Project

e-business center PwC&IESE edits a newsletter every fifteen days, available at www.ebcenter.org © 2008. e-business Center PricewaterhouseCoopers & IESE. All rights reserved.


2008 Edition

Authors:Prof. Sandra Sieber, Information Systems, IESEProf. Josep Valor, Information Systems, IESE

Collaborating authors:Prof. Evgeny Káganer, Information Systems, IESEProf. Francesc Miralles, Information Systems, UPF

Research assistant: Andrea Ramírez

Editor:Màrius Pellicer

This dossier is part of the Business and Information Technologies Project. For more information, please visit www.ebcenter.org/bit You can also find other projects at www.ebcenter.org/proyectos

notes fromebcenter


2008 Edition

Authors: Prof. Sandra Sieber, Information Systems, IESE

Prof. Josep Valor, Information Systems, IESE

notes fromebcenter

e-business Center PricewaterhouseCoopers & IESE

notes fromebcenter

Table of Contents

Introduction ........................................................................................................................... 3

1. Criteria for Adopting Technology and Theoretical Approaches ......................................... 5 1.1. Rational decision-making ........................................................................................... 6

1.2. Technology diffusion ................................................................................................... 8 1.3. Psychology of the decision-maker ........................................................................... 10

2. Criteria used in Spanish companies when adopting technology .................................... 13 2.1. Overall results: Comparison between large companies

and SMEs in 2007 ..................................................................................................... 14 2.2. Comparative analysis of the results by sector ......................................................... 24 2.3. Analysis of the main components ............................................................................ 32 2.4. Correlation of small and medium-sized companies

with each of the identified behavior patterns .......................................................... 35

3. Conclusions ...................................................................................................................... 37 4. Bibliography ..................................................................................................................... 39

Appendix .............................................................................................................................. 47

e-business Center PricewaterhouseCoopers & IESE3

Criteria for Adopting Information and

Communication Technologies

2008 Edition

Introduction

In the 1960s and 1970s, Information and Communication Technologies (ICTs) stormed onto the business scene. The main driving force behind these tech-nologies was the potential savings they promised, thanks to the possibility of automating arduous, repetitive manual tasks, such as drawing up and processing payrolls and accounting. Given this situation, the decision on whether or not to adopt a given technology was usually governed by the expected cost savings generated by certain technical features.

These days, however, ICTs play a much broader role in companies and have become a cornerstone of many companies’ competitive advantage. As such, technology supports, sustains and makes a decisive contribution to the growth of the business.

Depending on the context, a given technology may be implemented in a wide variety of ways and serve different purposes. Choosing one technology over another no longer depends merely on cost-saving criteria. Rather, it is a funda-mental issue for all executives due to the strategic implications of such a choice. Similarly, ICT management and governance are other key factors that deserve attention.

This report contains an analysis of the criteria used when adopting ICTs by the IS manager (information systems) departments in Spanish companies. The analysis includes not just the traditionally most important considerations – cost, technological features and costs of changing – but also other criteria that were not previously taken into account, such as the organization’s ability to imple-ment technological solutions and the presence of network externalities. Finally, it explores the importance of a third group of criteria related to the psychology of the decision-maker.

This document is organized as follows: The first section contains a brief survey of the theoretical framework on adopting technology, and the second part Presents

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the empirical results of a study on the criteria used when adopting ICTs by Spanish companies, which was obtained from a questionnaire-based survey




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1. Criteria for Adopting Technology and Theoretical Approaches

According to common wisdom, firms make decisions about adopting new informa-tion technologies by thoroughly evaluating the costs associated with bringing the technology into an organization against its expected performance benefits. If the latter outweighs the former, a positive decision is made. Yet, despite its simplicity and intuitive appeal, this scenario seems to reflect only one part of the story. In real life, firms often lack the internal knowledge to be able to carry out a reliable cost/benefit assessment. To overcome this, they have to rely on external sources, such as vendors, industry analysts and other adopters to provide the requisite informa-tion. While such information is plentiful in today’s marketplace, firms interested in adopting the technology often don’t know exactly how to interpret it. Firms make adoption decisions by calculating projected costs and revenues, and there is also a variety of more general, non-economic considerations. These non-economic determinants may be related to such factors as the firm’s organizational capabilities, the network externalities generated by the technology, as well as subjective factors affecting the decision-maker. All this turns making decisions about investing into new ITCs a messy business.

In this section, we provide a brief overview of the academic research on the sub-ject. Consistent with our earlier discussion, we distinguish among those theoretical approaches that attempt to understand the economic/rational determinants of adoption decision-making, those that focus on studying the process of design and implementation of innovations, and, finally, those that explore the decision-maker’s social and psychological drivers. By stressing some of the key insights within each of the three research streams, we hope to help the reader make better sense of how and why firms make decisions about whether or not to adopt a new technology.

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1.1. Rational decision-making

According to this theoretical perspective, adoption decision-making is based on the calculation of innovation utility. More specifically, this argument states that firms make adoption decisions by: (1) identifying relevant performance goals and objectives, (2) evaluating available technological alternatives with respect to how well they serve the goals (i.e., outputs); (3) evaluating technological alternatives with respect to their costs (i.e., inputs); and (4) selecting the alternative with the most favorable input/output ratio (i.e., utility). To make this theoretical jargon a bit more tangible, we discuss three concepts below that, in our opinion, play an important role in how firms evaluate the utility of ICT innovations.

Total cost of ownership (TCO). This is an often-cited factor in the academic lit-erature and a common tool used by vendors and IT managers in the industry. The cost of ICTs to an organization is not limited to the cost of technology acquisition. It also includes additional expenditures associated, for instance, with providing maintenance and technical support, switching over from an old technology to a new one, investing in end-user training, etc. The concept of TCO captures this plethora of costs by accounting for all relevant cost elements over the entire life-time of an ICT investment. TCO estimates show that the costs of hardware and software licensing fees make up only 8% to 15% of the total ICT investment, while the largest components of TCO are those attributed to technical support and system downtime.

Going back to the main theoretical argument of the rational decision-making pers-pective, we can say that the concept of TCO reflects the “input” side of the utility equation. In other words, it provides IT managers with a helpful decision-making tool to account for a wide range of diverse costs associated with bringing new technology into an organization.

Technological attributes. The term technological attributes, or features, is gene-rally used to describe the material properties of technologies. These properties include the functionality of the ICT solution, its hardware configuration, as well as general system-level characteristics, such as reliability, performance, security, scalability, etc. Features are often categorized into core and peripheral. Core fea-tures enable the main purpose that the technology is expected to fulfill. In con-trast, peripheral features, while improving and extending the user experience with

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the system, are not deemed essential. The term “bloated” software is sometimes used to describe an application overloaded with peripheral features.

Technological attributes perform several important functions in facilitating adop-tion decision-making. First, they enable comparison across various ICT solutions. Firms usually define their requirements and evaluate vendor proposals in terms of specific feature sets and system characteristics. Furthermore, core technolo-gical features provide the basis for setting boundaries between different product, or solution, categories in the crowded ICT marketplace. The Gartner Group, for example, establishes ICT categories based on a set of must-have solution functionalities. It then ranks vendors based on how well their systems perform in each of the functionality areas. Lastly, technological attributes serve as proxies for evaluating the projected organizational benefits of an ICT. For example, IT vendors may claim that their solution allows for seamless data integration across departments (i.e., a feature), which, in turn, helps the adopting firm streamline its workflow and achieve operational excellence (i.e., a benefit). In this sense, tech-nological attributes help the decision-maker to get a grip on the “output” side of the utility equation.

Lock-in. Another consideration that often enters utility calculations of a potential adopter is that of switching costs. When these costs are high, shifting from one technology to another becomes complicated and the company experiences a situation of lock-in (Shapiro and Varian, 1998). Lock-in may exist both at the level of a technology solution and at the level of a technology provider.

The academic literature distinguishes between internal and external lock-in. Internal lock-in can arise due to certain binding decisions made by the mana-gement of the adopting company, such as entering a long-term agreement with a technology provider. Massive investments in mission-critical legacy applica-tions and infrastructure also strengthen the company’s internal dependence on existing technologies. Besides, end users often face a steep learning curve that makes them resistant to new applications and that exacerbates internal lock-in. External lock-in, meanwhile, originates outside of the adopting firm and is usua-lly driven by forces within the ICT marketplace. When a single player dominates the market for a particular ICT solution, that player wields tremendous negoti-ating power over potential adopters and exerts full control over the evolution of the technology. The net result is a strong external lock-in effect, which usually

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overshadows all other rational adoption considerations, such as the technical superiority of the solution itself.

1.2. Technology diffusion

Apart from utility calculations, a number of other important factors affect how firms make decisions about adopting new ICTs. The theory of innovation diffusion (Rogers, 1995), a well-respected and widely used theoretical perspective, offers a more comprehensive view of the adoption decision-making process. It studies innovations and attempts to explain the evolution of new technologies and ideas from the moment of their inception to the moment when they are adopted and used. The key question the theory seeks to address is why some innovations enjoy widespread and ubiquitous usage while others fail to reach the masses.

Rogers summarizes five properties that characterize an innovation: 1) relative advantage; 2) possibility of observation; 3) compatibility; 4) complexity; and 5) possibility of testing. In the context of ICTs, these properties translate into the following questions that adopting firms face:

Relative advantages. Is the new system better than the system it is re-placing? What implicit risks does it entail?Possibility of observation. Will the results of implementing the system be visible to business people in the organization? Can they see how the system works and observe its impact on business processes and performance?Compatibility. Is the system consistent with the company’s policies and technological infrastructure?Complexity. Is the system easy for users to understand and learn? Does the IT staff have the capability to implement and maintain the system?Possibility of testing. Can pilot tests be made prior to implementing the system?

How well a particular ICT innovation scores on these five dimensions determines the likelihood of its widespread adoption.

Normally, the process of innovation diffusion moves slowly during the early sta-ges of adoption and picks up momentum as the number of users increases. For

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this reason, the company that adopts an innovation must take into account the characteristics of both the target population and its workers.

Since this progress takes place gradually, there is a degree of uncertainty that affects the results of the investment in ICTs. Uncertainty is a common feature in emerging sectors and those that intensively use technology. As the technological change becomes more radical or complex, there will be an increased need to train end-users. This will also lead to a greater level of uncertainty and, in the end, to increased difficulty adopting the innovation, even when the new technology is clearly superior.

Bearing in mind this framework, the adoption of a new technology is a process in which decision-makers might be influenced by both the organization’s capa-bilities and network externalities.

Organizational capabilities. The adoption of new technologies can be restric-ted if there are knowledge barriers. Complex technologies impose a burden of learning when being adopted (Fichman and Kemerer, 1997), especially when resolving technical problems proves tricky and magnifies the feeling of the ir-reversibility of the investment (Kogut and Kulatilaka, 2001).

Another factor related to the company culture that affects executives’ ICT deci-sions is uncertainty. Success when implementing a technological innovation is unpredictable, so companies must make their decisions based on their own expectations. Thus, decisions on adopting technology vary according to the decision-maker’s degree of risk aversion. However, the decision-making risk is also related to the ability of the companies’ budgets to allow for a degree of flex-ibility when experimenting for a certain period of time with a specific innovation with the purpose of checking to see whether it would be advantageous or not to definitively adopt it (Dedrick and West, 2003).

It is natural for companies to want to avoid risk, which leads them to consider technological capacities before other options. Thus, a particular system is not considered if it does not contain a series of functionalities. However, the more sophisticated the product’s characteristics compared to the technologies already on the market, the greater the time it will take to be implemented.

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Network externalities. For a user, if network externalities are present, the value of a technology grows with the total number of people who adopt it. Network extern-alities can be felt through two types of effects: direct and indirect. The direct effect occurs when the utility of directly consuming the technology increases with the total size of the user network. For example, the usefulness of e-mail increases for a user as more people adopt the technology. The indirect effect comes through the availa-bility of complementary goods. Thus, an individual who has bought a DVD player will benefit as more DVD players are sold because this will mean that more DVD titles will be available on the market. Thus, network externalities therefore affect the adoption of ICTs due to the expected benefits derived from adopting the new technologies.

Network externalities display a variety of features. First of all, the ultimate bene-fit of adopting the ICT will be determined not by the state of the technology at the present time, but rather by the decision-maker’s future expectations of the technology. What is more, increased profitability leaves a distinct pattern in the spread of technology that is known as “the winner takes all” (Shapiro and Varian, 1998). Both factors affect the adoption of ICTs since, in the presence of network externalities, many companies will aim to be the first in the market to acquire an innovation with the purpose of attaining the greatest number of users, thus taking advantage of the increase in the network’s value.

Employees’ skills determine the network externalities within companies (Hall and Khan, 2003). New technologies require employees to master new and complex skills. The workforce’s lack of skill constitutes a barrier to introducing new tech-nologies to companies because it constitutes an expense in terms of time and worker training. In order for companies to achieve growing, scaled profits, their workers must have the skills needed to use and to get the most from the tech-nological innovations implemented.

1.3. Psychology of the decision-maker

While the theory of innovation diffusion and the rational decision-making ap-proach provide a solid frame of reference for understanding how firms make ICT adoption decisions, both perspectives fail to account for some of the social influences and cognitive biases involved in this process. To make our discussion complete, we briefly outline these below.

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First, it is important to point out that firms do not make decisions in isolation. Instead, they closely monitor each other’s behavior and often engage in direct contact in order to exchange pertinent information. This social interaction gives rise to a number of interesting dynamics that, in the end, greatly influence the adoption decision. One such dynamic is described by the concept of “infor-mational cascading,” which takes place when a decision-making agent makes his or her decisions based on the information gathered from a third person. For example, an individual forms an opinion about a given product based on her own first-hand experience with the product; she then shares her opinion with another person. The second person, who does not have first-hand experience with the product, forms his opinion based on what the first person told him. He then relays his opinion about the product to a third person, and so on. Informational cascades take place when individuals ignore their personal information and mimic the decisions previously made by other agents (Kauffman and Li, 2003).

A concept related to “informational cascading” is that of inter-organizational imi-tation (Haunschild and Miner, 1997). Faced with uncertainty and a lack of first-hand knowledge about an innovation, firms often turn to copying what others in the industry are doing. In other words, the more widespread an innovation becomes within an industry, the greater the pressure on the adopting firm to ignore its local needs and simply follow the pack. Similarly, deployment of the innovation by large, reputable players usually spurs a wave of copycat adoption by firms that currently underperform and are on the lookout for a quick fix to their problems. In this sense, “success stories” promulgated by the media and consultants become a major driver for the spread of certain ICT innovations. The downside of this phenomenon is that such adoption is usually “mindless” in nature and results in a large percentage of failed implementations (Swanson and Ramiller, 2004).

A final concept that warrants attention concerns the supplier’s, or vendor’s, reputation. An ICT vendor known for its established technology, superb cus-tomer service and good implementation track record (however these are mea-sured) enjoys a “legitimacy” premium when a potential adopter scans the ICT marketplace for an appropriate solution. Vendors know this all too well and thus make significant efforts to build up and showcase their reputation by any possible means. A potential wrinkle here is that many of these means are prone to manipulation. In addition, from the point of view of the individual who makes

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the adoption decision, leaning on the vendor’s reputation minimizes the risk of damage to his or her reputation in case implementation problems arise down the line.

There are other theoretical approaches that focus on studying the adoption of ICTs by end-users. These approaches investigate individual perceptions of tech-nology usefulness, user-friendliness and task-technology fit. They also account for the impact of the decision-maker’s subjective norms, as well as the influence of peer pressure on his or her decision to adopt. In the context of ICT adoption by organizations, these considerations are important insofar as they reflect end-users’ opinions and preferences regarding the technology.




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2. Criteria used in Spanish companies when adopting technology

An empirical study of the criteria used when adopting information and com-munication technologies in Spain was carried out as part of the Business and Information Technologies Project (BIT) (1). The goal of this project is to obtain an indicator that enables us to describe the changes companies and industries all over the world have experienced in recent years with the introduction of new technologies. A second goal is to predict the future evolution of these technolo-gies.

To study the criteria used when adopting ICTs in Spain, a comparative analysis was made of the 2005 and 2007 surveys. These surveys were administered to IS managers (or to people in similar positions) in Spanish companies in different industries and of differing sizes. The goal was to compare the degree of impor-tance that the respondents gave to the set of 15 criteria used to make decisions on adopting ICTs that were used in the 2005 study (2). Table 1 shows the factors used for this study. Additionally, a comparison was made of the same period, 2005-2007, between large and small companies (SMEs) (3). The adoption criteria used in two of the most important sectors, manufacturing and services, were also analyzed.

(1) BIT is a project led by the UCLA Anderson School of Management and is being conducted in more than 20 countries, thanks to cooperation with major business schools around the world. IESE has directed the two editions of the Spanish chapter.

(2) Please see the study “Criteria Used When Adopting Information and Communication Technologies,” 2005, e-business Center, PricewaterhouseCoopers & IESE.

(3) For this study, large companies are those with more than 600 employees, while small and medium-sized companies are those with fewer than 600 employees.

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Table 1. Factors that affect CIOs’ decision-making when adopting ICTs

2.1. Overall results: Comparison between large companies and SMEs in 2007

Large companies clearly make their decisions on adopting technology based on economic rationality. For this reason, the costs this technology might generate is the most important criterion when weighing the decision. In contrast, for SMEs, the most important criterion seems to be risk avoidance, given that two of the criteria they consider most important are the existence of external support from the supplier and the supplier’s reputation.

Figure 1 compares how large companies and SMEs in 2007 rated the 15 deci-sion-making criteria used when adopting the technology included in the study. Many differences are apparent between the importance that large and smaller companies gave to each of these criteria. For example, 91% of the large com-panies and 79% of the SMEs considered making a decision based on cost ratio-nality to be important; this criterion was the most highly ranked among the large companies. In contrast, for SMEs, cost rationality came fourth in the hierarchy of criteria. Additionally, 85% of the large and 84% of the small and medium-

Rationaledecision-making

Total cost of ownershipTechnological characteristics Irrversibility of the adopted solution Incease independence form suppliers

Diffusion of innovation

Employees’ ICT skills Risk of failure by adopting a IT solution Standardization of the adopted solution Avoidance of radical changes Users’ skillsExistence of external support from supplier or other party

Psychology of the decision-maker

Opinions of colleagues or peer groupsSupplier’s reputation Belief that most of the industry will adopt this solutionUsers’ opinions or preferencesTop management’s opinion, if applicable

Source: “Criteria Used When Adopting Information and Communication Technologies,” 2005, e-business Center, PricewaterhouseCoopers & IESE.

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sized companies stated that the existence of external support from the supplier was important. This was the criterion that was most highly rated by SMEs when making a decision about adopting technology and the second-ranking criterion for large companies. Standardization of the solution to be adopted was the third most important criterion for large companies (80%) and the second-ranked for small and medium-sized companies (83%). In contrast, the supplier’s reputation was more important for SMEs than for larger companies; it was ranked third by SMEs (82%) but only seventh by large companies (72%).

Some decision-making criteria used when adopting technology were much more important for large companies than for SMEs; this was the case of employees’ current experience and skills with ICTs. Eighty percent of the large companies and 68% of the small and medium-sized companies believed this to be impor-tant. Users’ opinions and preferences were relevant for 75% of the large com-panies and 59% of the SMEs. Whether or not the solution was widely adopted in the sector was important for 53% and 44% of the companies, respectively. Likewise, SMEs gave more importance to criteria such as the irreversibility of the solution chosen (61% of the large companies compared to 76% of the small and medium-sized companies). In terms of the technical features of the technology, 60% of the large companies deemed this important compared to 65% of the SMEs. For users’ skills, the rates were 50% in the former and 56% in the latter; the opinion of colleagues and peer groups mattered to 49% and 66%, respec-tively. Finally, avoiding radical changes in work routines was important to 25% and 42%, respectively.

It should be kept in mind that there were other criteria that were equally impor-tant for both large companies and SMEs. For instance, upper Top management’s opinions and preferences were extremely important when making decisions for both large (75%) and small and medium-sized companies (72%). To a lesser extent, both groups believed it was important to gain further independence from suppliers - 52% and 50%, respectively - while the risk of making the wrong deci-sion was less important, with 49% in the former and 48% in the latter.

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Figure 1. Most important decision-making criteria used when adopting new technology in IT. Large companies and SMEs 2007

2.1.1. Comparative analysis of 2005 and 2007 taking all the companies into account

In 2007, Spanish companies pointed to the existence of external support from the supplier as the most important criterion when making a decision involving techno-logy adoption. Additionally, cost-based rationality and the standardization of the solution to be adopted remained the criteria that companies rated the highest.

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When comparing the results from all the companies regardless of size, there were several changes between 2005 and 2007 (Figures 2 and 3) (4) in the importance these companies attached to each of the criterion involved in adopting technology. However, none of these variations was statistically significant (5).

Figure 2. Technology adoption criteria. 2007

(4) The answers “very important” and “important” on the questionnaire for the question on adoption criteria have been included in the answer “important,” and the answers “not very important” and “not important at all” have been summarized in the answer “not very important,” as shown in the Figures.

(5) The t value obtained from the Z test for two proportions is greater than the t distribution value for a confi-dence level of 95%. The observed means are significantly different.

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Figure 3. Technology adoption criteria. 2005

For example, the percentage of companies that rated the existence of external support from the supplier as important was 87% in 2005 and 84% in 2007. The percentage that considered the costs of the technology important fell from 89% in 2005 to 83% in 2007, and the percentage of companies that gave importance to whether the technology they adopted was standard dropped from 92% in 2005 to 83% in 2007. There was also a drop in the percentage of companies that thought it was important to bear in mind the technical features of the technologies they were planning to adopt, which fell from 71% in 2005 to 64% in 2007. Likewise,


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the percentage of companies that considered it important to avoid radical changes in work routines fell sharply from 51% in 2005 to 38% in 2007. Meanwhile, the percentage of companies that took into account criteria such as users’ opinions and preferences rose slightly from 63% in 2005 to 69% in 2007. The percentage that regarded users’ skills as an important criterion in their decision-making also rose, from 50% to 55%. And the percentage that considered it important for the technological solution they adopted to also be widely adopted in their industry rose from 39% to 47%. Finally, the percentage of companies that valued the importan-ce of criteria such as supplier reputation, irreversibility of the solution adopted, top management’s opinions and the risk of making the wrong decision remained fairly steady.

2.1.2. Comparative analysis of large companies in 2005 and 2007

Most of the large Spanish companies in both 2005 and 2007 claimed that costs were the most important factor when deciding to adopt a technological solution. It is also important to note that no large company in 2007 believed that employees’ current experience and skills with ICTs was unimportant when making a decision to adopt a given technology. However, in 2007, fewer companies believed that their decision would lead to radical changes in their employees’ work routines.Figures 4 and 5 compare the ratings that the large companies gave to the 15 criteria on adopting technology contained in the study. The most important result of this comparison is the statistically significant drop in the percentage of large companies in 2005 that regarded it as important to take into account that the technology they were adopting might produce radical changes in work routines. This percentage halved, from 50% in 2005 to 25% in 2007, and the percentage that thought it was not important rose from 15% to 32%, respectively. Once again, cost-based rationality was confirmed as the most important criterion when adopting a technology, with 94% in 2005 and 91% in 2007. This criterion was followed by the existence of external support from the supplier (85% in both years) and the standardization of the solution to be adopted (94% in 2005 and 80% in 2007).

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Figure 4. Technology adoption criteria. Large companies 2007

* With a 95% significance level, we can say that the differences observed in the means were statistically significant.

Large companies rated the other criteria as important, although the percentage of importance they attached to each one changed. Thus, the percentage of large com-panies that took into account the supplier’s reputation as a criterion in their decision dropped from 81% in 2005 to 72% in 2007. The percentage that took into conside-ration the technical features of the technology fell from 77% to 60%, and the per-centage that said it was important to take users’ skills into account rose from 38% to 50%. In contrast, the percentage that rated Top management’s opinion as important rose only slightly from 71% in 2005 to 75% in 2007. Users’ opinions and preferences rose from 61% to 75%; those who considered it important to be more independent


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from their suppliers rose from 47% to 52%, and the percentage claiming that it was important for the solution to be adopted by the entire sector rose from 47% to 53%. It is also worth noting that the percentage believing their employees’ current experience and skills with ICTs an important criterion to take into account rose from 75% to 80%. In the case of this criterion, the percentage that considered it impor-tant in 2005 (7%) dropped to zero in 2007. Likewise, the percentage that thought that other criteria were important, such as the irreversibility of the solution adopted (63% in 2005 and 61% in 2007), the risk of making the wrong decision (51% in 2005 and 49% in 2007) and the opinion of colleagues and peer groups (49% both years), either experienced minor changes or remained the same.

Figure 5. Technology adoption criteria. Large companies 2005



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2.1.3. Comparative analysis of small and medium-sized companies in 2005 and 2007

SMEs still rank the following criteria as the most important to take into account when making a decision on adopting technology: the existence of external support from the supplier and the supplier’s reputation, cost-based rationality, the standardization of the solution to be adopted and the irreversibility of the solution adopted.

Figure 6. Technology adoption criteria. Small and medium-sized enterprises 2007


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Figure 7. Technology adoption criteria. Small and medium-sized enterprises 2005

Figures 6 and 7 show the rankings that small and medium-sized companies gave to the various criteria used when adopting technology during this period. There were slight changes in the percentage of SMEs that considered different criterion important; however, these were not statistically significant. For example, the per-centage of companies that considered the existence of external support from the supplier to be important dipped from 88% in 2005 to 84% in 2007. Those that ranked cost-based rationality high fell slightly from 85% to 79%; those that con-sidered the standardization of the solution important dropped from 90% to 83%; those that took into account the irreversibility of the solution adopted fell from 80% to 76%; those that believed that their employees’ current experience and skills mattered fell from 71% to 68% and users’ skills from 61% to 56%; those


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that deemed greater independence from the suppliers important dropped from 59% to 50%; and finally, those that aimed to avoid radical changes in the work routines fell from 52% to 42% in the respective years of the survey.

However, the percentage of SMEs that considered the supplier’s reputation important rose slightly from 76% in 2005 to 82% in 2007. Other considerations that small and medium-sized companies deemed more important in 2007 than in 2005 were the opinion of colleagues and peer groups, which rose from 51% to 59%, the risk of failing when making the decision, which rose from 42% to 48%; and the concern that the solution chosen would be widely adopted in the sector, which rose from 32% to 44%. Additionally, the percentage of SMEs that consi-dered other criteria important, such as Top management’s opinion or preference (73% in 2005 and 72% in 2007), users’ options and preferences (66% in both cases), and the technical features of the technology (66% in 2005 and 65% in 2007) all show minor changes.

2.2. Comparative analysis of the results by sector

For the sectoral analysis, the results from 2005 and 2007 were compared for all companies and for large companies and SMEs in the manufacturing and services sectors.

2.2.1. Comparative analysis of Spanish manufacturing companies, 2005-2007

Spanish manufacturing companies agreed in 2005 and 2007 (Figure 8) that the most important criterion to take into account when making a decision on adopting technology was the standardization of the solution to be adopted (96% in 2005 and 94% in 2007). Therefore, we can state that the companies in this sector are very interested in generating network externalities. Likewise, they also agreed to give less importance to avoiding radical changes in work routines. Only 35% in 2005 and 33% in 2007 regarded this criterion as important. There were also not statistically significant rises in the percentage of manufacturing companies that regarded the following criteria to be important: the existence of external support from suppliers or other third parties (from 79% in 2005 to 91% in 2007), the supplier’s reputation (from 71% in 2005 to 81% in 2007), the technical features of the technology (from 54% to 66%), users’ opinions and preferences (from

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54% to 64%), the opinions of colleagues and peer groups (from 46% to 61%), and users’ skills (from 42% to 55%). Likewise, the percentage of manufacturing companies that considered other criteria important such as Top management’s opinions and preferences and the risk of making the wrong decision, dropped slightly. Specifically, the former fell from 79% in 2005 to 67% in 2007, and the latter dipped from 58% to 50%.

Figure 8. Most important technology adoption criteria for manufacturing companies. 2005-2007

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2.2.2. Comparative analysis of large manufacturing companies, 2005-2007

In the case of large manufacturing companies (Figure 9), we can see that 100% clai-med that the most important criterion for them in both 2005 and 2007 was cost-based rationality. However, they also consider important standardization of the solution to be adopted (100% in 2005 and 92% in 2007). Furthermore, a slight upswing can be seen in the percentage that rate the following criteria as important: the existence of external support from the supplier (from 60% in 2005 to 92%), the supplier’s reputa-tion (from 60% to 85%), employees’ current experience or skills with ICT (from 60% to 85%), users’ opinions or preferences (from 40% to 62%), the technical features of the technology (from 40% to 69%), the opinions of colleagues or peer groups (from 40% to 62%), increasing independence from the suppliers (from 40% to 54%) and users’ skills (from 30% to 54%).

Figure 9. Most important technology adoption criteria for large manufacturing companies.

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There were also not significant drops in the percentage of large companies that con-sider the other decision making criteria to be important, such as: Top management’s opinions or preferences, which dropped from 79% to 67%, and avoiding radical changes in work routines, which fell from 50% in 2005 to 15% in 2007. When inter-preting these results, it should be kept in mind that the changes are not statistically significant.

2.2.3. Comparative analysis of manufacturing SMEs, 2005-2007

As shown in Figure 10, SMEs in the manufacturing sector attached greater importance to criteria related to the diffusion of innovation.

Figure 10. Most important technology adoption criteria for manufacturing SMEs. 2007

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For example, small and medium-sized companies considered the most important criteria worth taking into account to be the standardization of the solution they adopted (100% in 2005 and 92% in 2007) and the existence of external support from the supplier (93% in 2005 and 90% in 2007). Furthermore, it is worth poin-ting out that there is a slight, statistically not significant, rise in the percentage of SMEs that considered avoiding radical changes in work routines an important criterion to bear in mind when deciding to adopt technologies, rising from 21% in 2005 to 40% in 2007. There was a drop in the percentage that considered the following decision-making criteria important: the irreversibility of the solution adopted (from 93% in 2005 to 78% in 2007), top management’s opinions and preferences (from 79% to 63%), employees’ current experience and skills with ICTs (from 79% to 65%), increasing independence from suppliers (from 71% to 63%), and the risk of making the wrong decision (from 64% to 47%).

2.2.4. Comparative analysis of Spanish companies in the services sector, 2005-2007 For service companies, cost remained very important when making decisions about adopting technology, but whether the technological solution they adopted was standardized mattered less to them in 2007 than in 2005.

When comparing the percentage of companies that rated the 15 criteria consid-ered in this study to be important (Figure 11), we can see that for companies in the services sector, the most important criteria when deciding to adopt a techno-logical solution were cost-based rationality (92% in 2005 and 81% in 2007) and the existence of external support from the supplier (79% and 85%). Likewise, there were statistically significant drops in the percentage of services companies that gave much importance to criteria such as the standardization of the solution to be adopted (from 98% to 77%). There was also a statistically not significant drop in the percentage that gave importance to avoiding radical changes in work routines (from 54% to 39%).

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Figure 11. Most important technology adoption criteria for services companies

* With a 95% significance level, we can say that the differences observed in the means were statistically sig-

nificant.

2.2.5. Comparative analysis of large Spanish companies in the services sector, 2005-2007

In the case of large companies in the services sector (Figure 12), the most reveal-ing result is that decision maker in this sector, the standardization of the solution to be adopted lost a great deal of importance. The percentage that considered this criterion important dropped from 96% in 2005 to 74% in 2007. This differen-ce was statistically significant.

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Likewise, we can see that cost-based rationality (89% in 2005 and 93% in 2007) and the existence of external support from the supplier (85% and 81%, respec-tively) were the criteria they considered the most important. We also see a drop in the percentage of companies that regarded the following criteria as important: the supplier’s reputation (from 81% to 68%), the technical features of the tech-nology (from 78% to 57%), the opinions of colleagues and peer groups (from 56% to 45%), and avoiding radical changes in work routines (from 41% to 30%). It should be kept in mind, however, that these changes were not statistically significant.

Figure 12. Most important technology adoption criteria for large services companies


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2.2.6. Comparative analysis of Spanish companies in the services sector, 2005-2007

SMEs (Figure 13) attached a great deal of importance to issues such as the exis-tence of external support from the supplier (91% in 2005 and 78% in 2007), the supplier’s reputation (81% in 2005 and 83% in 2007), cost-based rationality (91% in 2005 and 78% in 2007) and the standardization of the solution to be adopted (96% in 2005 and 77% in 2007).

Figure 13. Most important technology adoption criteria for services SMEs

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In contrast, there were slight, statistically not significant changes in the percentage of SMEs in the services sector that rated the following criteria as important: emplo-yees’ current experience or skill with ICTs, which rose from 61% in 2005 to 71% in 2007; top management’s opinions or preferences (from 65% to 71%); the technical features of the technology (from 57% to 69%); the opinions of colleagues and peer groups (from 48% to 59%); the risk of making the wrong decision (from 35% to 45%); and the belief that the solution would be widely adopted in the sector (from 30% to 43%). There was also a decline in the percentage of SMEs that deemed the following criteria important: the irreversibility of the solution and avoiding radical changes in the work routine, with the former dropping from 83% to 71% and the latter from 65% to 42%.

2.3. Principal components analysis

It has always been said that small and medium-sized enterprises behave in a different way from large companies. In Spain, a country where there is a tradition of smaller-sized companies, a study of the factors that influence how they make their decisions about adopting technology attracts even greater interest. This fact, added to the difficulty of comparing the results for 2005, in which all com-panies were surveyed (large as well as small and medium-sized ones), has led to a reconsideration of the objectives for this 2007 analysis. It has been decided to take into account only the results obtained from the small and medium-sized companies.

Using the principal components analysis enables the behavior of companies to be explained in terms of their decisions regarding the adoption of information and communication technologies. This analysis enables the criteria of the survey to be categorized into various groups that define different types of behavior. (6) In Appendix 1 there is a schematic showing the application of the principal com-ponents analysis.

The results obtained from using this set of statistical tools show that there are five relevant types of behavior in the processes of adopting ICTs by small and medium-sized Spanish companies. The types of behavior identified are as follows: 1) beha-

(6) “Criteria for Adoption of Communication and Information Technology,” 2005, e-business Center, PricewaterhouseCoopers & IESE.

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vior based on systems’ compatibility and vendor independence; 2) skills-based behavior; 3) “copycat/conservative” behavior; 4) behavior based on conservative obidience and 5) cost-based behavior. (See Table 2)

The first type of behavior is based on system compatibility and vendor indepen-dence and is related to four of the criteria set out in the questionnaire: the irrever-sibility of the adopted solution, standardization of the adoptes solution, existence of external support from supplier or other party and increase independence from suppliers. Companies basing their decisions on this type of behavior are mainly interested in being compatible, having good external support and minimizing lock-in by having greater vendor independence.

The second type of behavior based on skills is directly related to the current experience and ICT skills of the staff and to users’ skills and preferences. Companies that make decisions about technology adoption based on this type of behavior are keen to avoid the obstacles to technology adoption that could be caused by a lack of experience or ICT skills on the part of the staff and, in this way, benefit within the company from the external user community. The decisions of these companies are also heavily influenced by the views and wishes of their customers.

The third type of behavior identified is so-called “copycat/conservative” behavior and this is defined by the psychological parameters of the decision-maker: the opinion of colleagues and related work groups, the belief that the solution should be adopted on a majority basis within the sector, and the risk of making the wrong decision. The heads of IT in companies behaving in this way use streams of information and make their decisions based on data gathered from third par-ties. They copy decisions previously made by other companies in the sector in order to minimize the risk of losing their reputation.

The fourth type of identified behavior is that of conservative obedience and is directly related to parameters such as the opinion or preference of senior top management and vendor reputation. The decision-maker, in companies beha-ving in this way, is basically interested in reducing the risk to his own reputation within the company, taking into consideration the opinions of management and the vendor’s own reputation.

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The fifth and final type of behavior identified is that based on cost, which is direct-ly related to the criteria, technological characteristics and total cost of ownership. Even so, it is inversely related to the criteria of avoiding fundamental changes in working practices. Decision-makers in these companies will pay a great deal of attention to the costs incurred by introducing ICTs and to the evaluation of the technical features of ICTs. They will place little importance on the potential impact of introducing technology into the working practices of their companies.

Table 2. Variables associated with each behavior pattern identified

Increase independence from suppliers Existence of external support from supplier or other party Standardization of the adopted solution Irreversibility of the adopted solution

Users’ opinions or preferences Employees’ ICT skills Users’ skills

Opinions of colleagues or peer groups Belief that most of the industry will adopt the solution Risk of failure by adopting an II solution

Top management’s opinion, if applicable Supplier’s reputation

Technological characteristics Total cost of ownership Avoidance of radical changes

Relation with the original variables

Component 1 Component 2 Component 3 Component 4 Component 5

Original variables:Criteria for adoption used in the survey

Extraction of components

Behavior based on the compatibility of the systems and independence from suppliers

Behavior based on skills

“Follower-conservative” behavior

Behavior based on conservative obedience

Behavior based on costs

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2.4. Correlation of small and medium-sized companies with each of the identified behavior patterns

Although the most important decision criteria for those responsible for IT in small and medium-sized companies was the availability of external support from the vendor, their decisions were nevertheless not governed by a single type of behavior. It is therefore possible to find a very wide range within each type of behavior.

Table 3. Percentage of small and medium-sized companies associated with each type of behavior

Table 3 shows the relationship between small and medium-sized enterprises and the behavior patterns identified by the principal components analysis based on the decision-making criteria for technology adoption. The statistical analysis indi-cates that those who make decisions in 25% of small and medium-sized Spanish companies forget about their personal opinions and adopt technology based on decisions made previously by other companies in the same sector (“copycat/con-servative” behavior). Moreover, 21% of them have a clear preference for the adop-tion of standards for which the vendor offers external support in order to reduce the risk of the decision being irreversible. At the same time, they try to achieve greater independence from vendors. For those responsible for IT in 19% of small and medium-sized companies, it is important to retain a good reputation within the company, which is why, when they come to make a decision regarding the adoption of technology, they pay great attention to the preferences of senior top management. They also make sure that the vendor has a good reputation (behavior based on conservative obedience). Yet, the decisions of those in charge of IT in 19% of small and medium-sized companies are driven by technology costs and

Type of behavior Percentage of SMEs that identify with this behavior

Behavior based on the compatibility of the systems and independence from suppliers

21%

Behavior based on skills 16%

“Follower-conservative” behavior 25%

Behavior based on conservative obedience 19%

Behavior based on costs 19%

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technical features, quite apart from whether their decision causes radical changes in the company’s working practices (cost-based behavior). Finally, in 16% of small and medium-sized companies, the person in charge of making decisions about the adoption of technology studies the viability of its adoption for the workforce and the preferences of the company’s customers (skills-based behavior).

Despite the fact that a comparison was not made with the results of the 2005 sur-vey, it is worth noting that the results of all of the companies in 2005, just like the small and medium-sized companies in 2007, both conclude that the “follower-conservative” behavior was the most common type of decision-making conduct (26% in 2005, and 25% in 2007) of those responsible for IT decisions.




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3. Conclusions

This empirical study on the criteria for adopting information and communication technologies among Spanish companies reveals that both in 2005 and 2007 the key factors in decisions concerning the incorporation of new ICTs were: the prospective costs generated by the newly adopted technology, the existence and reputation of support staff among suppliers, and the standardization of the tech-nological solution to be adopted. In the meantime, it seems that between 2005 and 2007 concerns among IT managers of large companies about the disruptive effect that the adoption of new technologies might have on work activities signi-ficantly diminished.

The study also revealed that in both 2005 and 2007 a major priority among IT managers of companies in the manufacturing sector was to seek compatibility between the various technological solutions they had adopted, for which they received active support from suppliers. By contrast, IS managers of services companies appeared to lose a certain amount of interest in the standardization of technological solutions between 2005 and 2007. Instead, it was the cost of new technologies that had the greatest influence on their decisions.

From our analysis of the ICT adoption criteria in small and medium-sized enter-prises, which was based on the evaluations provided by the respective compa-nies’ IT managers, we can identify five key behavioral components that impact on their decisions regarding the incorporation of new technologies. They are, respectively: a desire to improve the compatibility of the systems and thus redu-ce the company’s dependence on suppliers, a concern about skills development, conservative adaptation to established methods and systems, conservative-follower behavior, and worries about the scale of costs involved.




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Appendix

Principal component analysis

This statistical method is primarily used to analyze qualitative data, such as the ratings given by the IS managers heads to the 15 variables that are part of this study. Principal component analysis is a method of extracting factors that is used to form non-linear combinations of the variables observed. The first component has the maximum variance and the following components gradually refer to smaller portions of the variance. The components are not correlated with each other.

Applying principal component analysis to this study enables us to explain com-panies’ behavior relative to their decisions about adopting ICTs by analyzing a reduced group of variables obtained by applying this methodology. As a result, it makes it easier to study the 15 variables on criteria used when adopting ICT included in the questionnaire, now called original variables, by reducing them to just five variables that contain relevant information on strategic decision-making behavior, called components.

The principal components chosen (see Table A) are those with eigenvalues grea-ter than one: eigenvalues indicate the amount of variation in the original values encompassed in each component. The choice of these five components enables us to reduce the complexity of the data with a loss of 43.86% of the information, as the first five components capture 56.14% of the variability.

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Table A. Principal component analysis.

Once the main principal components are chosen, the next step is to extract the information they provide on the decision-making behavior. The extracted com-ponents bear a close relationship to the original variables in the study, yet at the same time they allow these variables to be grouped to help identify the most important variables for the IT heads IS managers and determine their decision-making behavior. The relationships between the components and the original variables are established by studying the rotated component matrix. Table B presents the results with the original variables.

Table B. Rotated component matrix

Original variablesComponents

1 2 3 4 5

Users’ preferences or opinions -0.177 0.634 0.126 0.151 0.019

Employees’ current experience or skill with ICT 0.024 0.776 0.079 0.009 -0.024

Total cost of ownership 0.140 0.339 -0.046 0.306 0.598

Users’ skills 0.155 0.676 -0.168 -0.149 0.091

Avoiding radical changes in work routines 0.241 0.418 0.213 -0.304 -0.476

Increasing independence from suppliers 0.561 0.283 0.069 -0.295 0.236

The technical features of the technology 0.169 -0.038 0.312 -0.224 0.668

The opinion of colleagues or peer groups 0.019 -0.032 0.768 -0.039 0.129

The existence of external support from the supplier or other third party 0.573 -0.138 0.331 0.160 0.063

The standardization of the solution to be adopted 0.675 -0.107 0.305 0.181 0.047

Upper management’s opinion or preference, if expressed 0.053 -0.003 0.094 0.797 0.022

The supplier’s reputation 0.491 0.014 0.205 0.561 0.067

The irreversibility of the solution to be adopted 0.795 0.097 -0.077 0.044 -0.018

The belief that the solution will be widely adopted in the sector 0.178 0.113 0.623 0.140 0.032

The risk of failing when making the decision 0.277 0.070 0.432 0.274 -0.243

Component Eigenvalues Percentage variance

Cumulative percentage

1 3.06 20.37 20.37

2 1.90 12.67 33.04

3 1.26 8.37 41.41

4 1.14 7.59 49.00

5 1.07 7.14 56.14

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The values presented in the matrix are the correlations between the original varia-bles and the principal components. There are differing degrees of relationship between the original variables and the principal components, so it is important to choose the variables with the highest correlation with each component. This will allow us to discover the strategic behavior of companies.

Table C summarizes the variables that correlate most closely with the five com-ponents:

Table C. List of principal components and original variables

Variable

Component 1

Increase independence from suppliers Existence of external support from supplier or other party Standardization of the adopted solution Irreversibility of the adopted solution

Component 2 Users’ opinions or preferences Employees’ ICT skills Users’ skills

Component 3Opinions of colleagues or peer groups Belief that most of the industry will adopt the solution Risk of failure by adopting an II solution

Component 4 Top management’s opinion, if applicable Supplier’s reputation

Component 5Technological characteristics Total cost of ownership Avoidance of radical changes

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