Web 2.0 service adoption and entrepreneurialOrientation

Seongbae Lim • Silvana Trimi • Hong-Hee Lee

Received: 21 January 2010 / Accepted: 16 September 2010 / Published online: 7 October 2010 © Springer-Verlag 2010

Abstract The purpose of this study is to investigate the relationship between Web 2.0 service adoption and entrepreneurial orientation (EO). For this purpose, this article conducted multivariate analysis of variance (MANOVA) using Web 2.0 service adoption groups (high and low adopters) as an independent variable and EO as dependent variable, measured with four variables: innovativeness, risk taking, autonomy, and competitive aggressiveness. The results show that there are significant differences in EO, overall and for each dimension, between the two groups (high adopters/low adopters of Web 2.0). High adopters of Web 2.0 have a stronger EO in terms of all the four of the individual EO dimensions.

Keywords Web 2.0 · Service adoption · Entrepreneurial orientation · Social

networking · Innovativeness

1. Introduction

Web 2.0 that emphasizes ‘‘collaboration,’’ ‘‘participation,’’ and ‘‘openness’’ has been recently expanded, and related services have been broadly adopted worldwide not only by individuals but also by organizations.

S. LimBill Greehey School of Business, St. Mary’s University, One Camino Santa Maria,San Antonio, TX 78228, USAe-mail: slim1@stmarytx.edu

S. Trimi (&)Management Department, University of Nebraska- Lincoln, Lincoln, NE 68588-0491, USAe-mail: strimi@unlnotes.unl.edu

H.-H. Lee School of Business and Economics, Dankook University,126, Jukjeon-dong, Suji-gu, Yongin-si, Gyeonggi-do 448-701, Korea e-mail: honglee@dankook.ac.kr

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Companies are deploying Web 2.0 technologies, such as micro blogging, social

networking, wikis, and internal blogging, because they can dramatically improve

decision cycle times, organizational effectiveness, innovation, etc. Web 2.0, and

soon Web 3.0, appears to have become the new paradigm which brings

fundamental changes to the internal corporate value chain and their relationship

with customers. Furthermore, it is also changing the nature of competition by

restructuring the industry value chain. For example, the traditional framework

that assumes clearly demarcated roles between producers and consumers can no

longer be used to analyze the industry value chain since a consumer can

simultaneously be also a producer. App Store, Linux, Wikipedia, and

youtube.com are good examples. On the other hand, entrepreneurship education

for college students has been built to emphasize as a venue for educating young

people who can create their new ventures to boost the national economy in the

future. Entrepreneurial orientation (EO) has been identified as a fundamental

factor that influences how entrepreneurship translates into action (Lee S, 2000).

While entrepreneurship is related to ‘‘desire’’ for launching a venture firm, EO

is directly related to actual behavior and can be a critical factor for successful

venture creation. Previous studies regarding the individual adoption of

information technology (IT) have focused on such non-personal, non-intrinsic

factors as ‘‘ease of use, perceived usefulness, benefits, social norms,’’ and so

on. Considering that Web 2.0 is a new paradigm of voluntary collaboration,

participation, and openness by individuals, it would be appropriate and

meaningful that we look at Web 2.0 adoption related to the adopters’ personal

characteristics, such as EO. Thus, in this study we proposes that there is a

relationship between adoption of Web 2.0 service and EO because both Web 2.0

and EO function based on a strong ‘‘bottom up’’ rather than ‘‘top down’’ type

structure.

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2. Theoretical background and research model

2.1. Web 2.0

Web 2.0 is a new trend of creative utilization of web technologies rather than a specific technology or service. It does not coincide with any brand new or revolutionary technical innovation (Kim D, 2009), but instead uses a broad range of different technologies, applications, and functions for interactivity, networking, or user integration (Mrkwicka K, 2009). Depending on the domain under investigation, previous studies have defined Web 2.0 differently. (et,2006) believed that Web 2.0 is a philosophy that emphasizes collective intelligence, collaboration, and community services. (Anderson, 2007) suggested individual production and user generated content, harnessing power of the crowd, data on epic scale, architecture of participation, network effect, and openness, as the ideas behind Web 2.0. (McAfee, 2007) introduced improved collaboration, innovation, and connectivity as main benefits of using Web 2.0 services. Castelluccio (2008) suggested the collaborative environment and dependence on user created content as characteristics of Web 2.0. Cooke and Buckley (2008) viewed Web 2.0 as a set of tools that allows individuals to publish, share, and collaborate. (Kim D, 2009) suggested participation, collaboration, rich user experience, social networking, semantics, and interactivity as characteristics of Web 2.0. (Mrkwicka K, 2009) also viewed Web 2.0 as an enabling platform for user participation that focuses on philosophy of mutually maximizing collective intelligence, dynamic information sharing, and creation. Since Web 2.0 has been defined in diverse ways and often as a collection of new phenomena, there is no measurement for Web 2.0 acceptance or adoption. This study attempts to use individuals’ adoption behavior of Web 2.0 services as a measurement for Web 2.0.

2.2. Entrepreneurial orientation

(Miller, 1983) introduced the original framework of EO which included as dimensions of measuring entrepreneurship: innovation, proactiveness, and risk taking. Several subsequent studies used these three dimensions ( (Slevin, 1989); (Dess, 1996); (Lee S, 2000) ; (Kreiser PM, 2002) ; (Tarabishy A, 2005)). In a later study, (Dess, 1996) distinguished EO as the process, practice, and decision

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making activity that lead to new venture entry. In addition to the previous three dimensions of EO (innovativeness, risk taking, and proactiveness), they introduced two other dimensions: autonomy and competitive aggressiveness. These five dimensions of EO can be defined as follows:

(1) Innovativeness Tendency to engage in, and support new ideas, novelty,

experimentation, and creative process which may result in new products,

services, or technological processes.

(2) Proactiveness Taking initiatives by anticipating and pursuing new

opportunities and by participating in emerging markets.

(3) Risk taking Willingness to incur heavy debt or make large resource

commitments for the purpose of seizing opportunities in the market place for

high returns.

(4) Autonomy The independent action in bringing forth an idea or a vision and

carrying it through to completion.

(5) Competitive aggressiveness Propensity to directly and intensely challenge its

competitors to achieve entry into or improve positions in the marketplace and

outperform industry rivals.

(Lee S, 2000) , adopting the same five dimensions introduced by (Dess, 1996) , characterized EO as the process in which entrepreneurship is undertaken in terms of the methods, practices, and decision making processes for new entry into the market. In this study, we adopt (Dess, 1996) definition of EO. However, (Slevin, 1989) used the same items to measure both proactiveness and competitive aggressiveness since the characterization of these dimensions significantly overlaps. We also agree with this approach, thus in this study we excluded ‘‘proactiveness’’ and used only four dimensions to measure EO: autonomy, innovativeness, risk taking, and competitive advantage.

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2.3. Web 2. 0 and relationship of entrepreneurial orientation

(Castelluccio, 2008) emphasized that Web 2.0 has restructured the vertical structure of the traditional client–server/consumer–provider universe into a horizontal structure, where any consumer of content/information can also be a provider. In an organizational environment, (Chui M, 2009) compared the adoption behaviors of Web 2.0 technologies and enterprise systems application (ERP, CRM, and SCM), as summarized in Table 1. As shown in the table, while the adoption of enterprise systems is the result of top-down decision making, the adoption of Web 2.0 service is voluntary, bottom-up, that engages a broad base of workers. Thus, adoption of Web 2.0 services is a result of strong horizontal culture. Horizontal culture encourages entrepreneurial behaviors. This means that there could be a relationship between Web 2.0 adoption and EO, which is the intention of this study.

3. Research methodology

3.1. Research design and methodology

The proposed research model of this study is shown in Fig. 1. This study investigates the relationship between Web 2.0 adoption and EO. For the independent variable, Web 2.0 adoption, we divided the respondents into two groups: high and low adopters based on the average adoption score of five selected social networking services (SNS). As for the dependent variables, EO, we used the four previously discussed dimensions: autonomy, innovation, risk taking, and competitive aggressiveness. In this study, we could not include all kinds of Web 2.0 services, especially when even its definition is not clear, among many types of Web 2.0 services. Thus, we focused on only one, SNS which is the most popular Web 2.0 service and used by both individuals and organizations. We used SPSS 15.0 for the statistical analysis of this study.

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Table 1 Adoption behaviors of enterprise systems and Web 2.0

Enterprise systems application Web 2.0 service

Adoption decision Users assigned by management User groups can be formed unexpectedly

Mindset expected Users must comply with rules Users engage in a high degree

of participation

Degree of technology complexity Often complex technology Technology investment investment often a light weight overlay to existing infrastructure

Entrepreneurial Orientation

Fig. 1 Research model for MANOVA analysis

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Web 2.0:High Group Low GroupRisk takingInnovativenessCompetitive AggressivenessAutonomy

3.2. Instrument design and sample group

Data were collected from college students in South Korea, since the country is the world leader in terms of the Internet infrastructure and its applications to ubiquitous life and e-business (Lee, 2003). Because data collection from students was administrated during the class, we had 100% response rate: we gave out and collected 223 questionnaires. The questionnaire items for measuring EO dimensions and SNW were developed based on a thorough review of previous studies and interviews with ten practitioners involved in Web 2.0 services. The first draft of the questionnaire was developed as a mixture of items: to measure EO dimensions, items were taken from (Dess, 1996); and to measure Web 2.0 usage focusing on SNS, items were developed by authors of this study. Then, we conducted three pilot tests and significantly revised the questionnaire. The final version of the questionnaires was distributed to the sample groups.

3.2.1. Independent variable: Web 2.0 adoption

Since the five questions to measure SNS adoption were developed by the researchers, an exploratory factor analysis, and reliability analysis were conducted to confirm the unidimensionality of variables. As shown in Table 2, no problem was found in terms of construct validity. Cronbach’s a value was .85 satisfying the reliability test. We used the average score of the five questions about SNS adoption which was used to divide the respondents into two groups: high and low adopters of Web 2.0.

3.2.2.Dependent variable: entrepreneurial orientation (EO)

The questionnaire included 16 questions, based on previous studies, to measure:

(1) Innovativeness (2) risk taking (3) autonomy, and (4) competitive aggressiveness.

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Table 2 Result of factor analysis for Web 2.0

Factor Eigen value Variable Factor loading Operational definition

1 3.132 I like to make friends through SNS .806 Web 2.0 service adoption I am actively involved in a web-based virtual .769 service adoption community which is built around common interest such as games, sports, music, health, and life style I am actively involved in a web-based virtual .832

community which is built around the same affinity such as religion, ethnicity, gender, sexual orientation, and geographical location I like to upload my own stories, pictures, and .815 videos on the web sites to share them with online friends I enjoy sharing my own writings with online .731 friends

Table 3 Result of factor analysis for EO

Factor Eigen value Variable Factor loading Operational definition

1 4.604 I often think about inventing new products .803 Innovation I like to work where new ideas that I suggest .735 will be acted upon by decision makers I consider myself as a creative person .614

2 1.314 I don’t like conformists .734 Risk raking I would choose to invest money in an .704 entrepreneurial business as opposed to a more well-known business I would say that I am rather adventurous and .580 daring

3 1.094 I am persistent about completing projects .545 Autonomy I generally feel I am in charge of my own fate .857 My family and friends tend to see me as taking .867 the initiatives

4 1.042 I want to be near the top of my class .528 Competitive I enjoy playing sports or games with people .807 aggressiveness aggressiveness who are little better than I am I enjoy competing and doing things better than someone else .789

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For each question, a five point Likert type scale was used (1. strongly disagree, 2. disagree, 3. neither agree nor disagree, 4. agree, and 5. strongly agree). We ran exploratory factor analysis where four factors were extracted and used to measure the dimensions of EO as shown in Table 3.

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4. Result and discussion

4.1. Demographic characteristics of respondents

Before conducting MANOVA, correlation analysis was conducted among the dependent variables to check whether MANOVA was a proper tool for analyzing the data. As shown in Table 5, MANOVA can be used since the four dependent variables showed significant relationships among them.

4.2.2 Equality of covariance and error variance

Box’s M test was conducted to test the equality of covariance matrices between the two groups of low and high Web 2.0 service adopters. As seen in Table 6, the result (.058) was not significant, meaning that covariance matrices of the dependent variables are equal across the groups, and therefore MANOVA analysis is acceptable.

Table 4 Student class of respondents

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Class Frequency Percent Cumulative percent

Freshmen 38 17 17

Sophomore 38 17 34.1

Junior 104 46 80

Senior 31 14 94

Graduate student 12 6 100

Total 223 100.0

Table 5 Correlation among dependent variables

Innovativenes

s

Risk Taking Autonomy Competitive aggressiveness

Inoovativeness 1 .474* .214* .655*

Risk Taking .407* 1 .665* .654*

Autonomy .408* .562* 1 .665*

Competitive aggressiveness .409* .645* .236* 1

* P\.05

Table 6 Box’s test of equality of covariance matrices

4.2.3. Web 2.0 and EO (overall)

First, we tested the relationship between EO as a single factor (not divided into the four dimensions) and Web 2.0 adoption (divided into two groups: high and low adopters). As shown in Table 7, all the relevant values including Pillai’s Trace, Wilks’ Lambda, Hotelling’s Trace, and Roy’s Largest Root were significant at the 01 level meaning that there is a significant difference in terms of EO between the two groups, the high and low Web 2.0 adopters. To see if there was any violation of this MANOVA test, we used Levene’s test of equality of error variances. The results of the test, presented in Table 8, show that the assumption of the equality of the error variance of the two groups of the dependent variable was violated in two of the EO dimensions, autonomy, and competitive aggressiveness (P\.05). However, the failure to meet the assumption of equality of error is not critical to this MANOVA test, since the score was not very low and the sample size of the two groups was similar.

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Box‘s M 18.174

F 1.4889

df1 10

df2 2225456666261.5

Sig. .0589

4.2.4. Web 2.0 and EO in each dimension

The univariate test was conducted to measure the difference between the two adoption groups of Web 2.0 and each of the four dimensions of EO. As presented in

Table 7 Result of MANOVA test

Effect Valu

e

F Hypothesis df Error df Sig.

Web

2.0

Pillai‘s Trace .070 4.125 4.000 218.000 .003**

Wilks‘ Lambda .930 4.125 4.000 218.000 .003**

Hotelling‘s Trace .076 4.125 4.000 218.000 .003**

Roy‘s Largest Root .076 4.125 4.000 218.000 .003**

** P<.01

Table 8 Levene’s test of equality of error variance

Levene

statistic

df1 df2 Sig.

Innovativeness .048 1 221 .826

Risk taking .008 1 221 .927

Autonomy

Competitive

aggressiveness

4.753

3.942

1 221 .030*

1 221 .048*

* P<0.05

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Table 9 Result of univariate test

Source Dependant variable Type III

sum

df Mean Square F. Sig.

Web 2.0 Innovativeness 2.601 1 2.601 4.744 .030*

Risk taking 1.274 1 1.274 2.768 .098*

Autonomy 4.017 1 4.017 7.696 .006**

Competitive

aggressiveness

8.808 1 8.808 16.519 .000**

* P\0.05, ** P\0.01

Table 10 Descriptive statistics

Groups Mean Std. Deviation N

Innovativeness Low adopter 3.647

2

.76529 103

High adopter 3.863

9

.71856 120

Total 3.763

8

.74672 223

Risk Taking Low adopter 3.165

0

.66972 103

High adopter 3.316

7

.68579 120

Total 3.246

6

.68112 223

Autonomy Low adopter 3.491 .78222 103

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High adopter 3.761

1

.66692 120

Total 3.636

8

.73324 223

Competitive Low adopter 3.362

5

.78951 103

aggressiveness High adopter 3.761

1

.67527 120

Total 3.577

0

.75531 223

Table 9, the results show that significant differences are found in all the four

dimensions of EO (the risk taking dimension was at the .1 level of significance).

As shown in Table 10, the high adopter group showed higher mean values than

the low adopter group consistently across all the four dimensions of EO. The

gap between the two groups was larger for autonomy and competitive

aggressiveness as expected according to the MANOVA test results. These

results suggest that high adopters of Web 2.0 have higher EO than low adopters.

Furthermore, high Web 2.0 adopters showed a stronger mindset for innovation,

risk taking, autonomy, and competitive aggressiveness than low adopters.

5. Discussion and conclusions

The purpose of this study was to investigate the relationships between EO and

Web 2.0 service adoption. For this purpose, we measured the students’ adoption

of Web 2.0 service by focusing on SNS and measured their EO in four

dimensions. The result of this study showed that there were significant

differences in EO, overall, and for each dimension, between the high adopters

and low adopters of Web 2.0. We opters. can therefore conclude that students

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who adopt Web 2.0 are more entrepreneurial than those who do not. This result

provides important implications for practitioners and managers. Since the advent

of Web 2.0 technologies and services, organizations have focused mainly on

consumers’ adoption of Web 2.0 services and their behavior on the social

networking sites. These approaches have provided organizations with new

insights for understanding consumer behavior in the virtual space. Thus, they

have been able to leverage social networking sites for more effective customer

relationship management, marketing and public relations.

On the other hand, organizations have been much more resistant in adopting and allowing usage of SNS by their employees. Reasons for this are often cited as: reduced productivity, security issues, reputational risk, wasted bandwidth (cost), to mention just a few. However, the benefits from internal SNS usage for the organization can be far greater. SNS can effectively connect employees and knowledge workers, and organizations can use SNS as a tool for innovation and business process improvement. Web 2.0 tools can improve organizational performance by expediting the internal flow of knowledge and help generate innovative ideas much faster, because they effectively link employees across the organization (departments and geography), as well as with external collaborators.

IBM, for example, has created an internal social networking site, Beehive, which encourages communication within the organization. In Beehive, 60,000 employees exchange their ideas to create knowledge. Furthermore, it provides valuable mentorship connections for employees who need new knowledge by analyzing contents, human networks, and many other topics in the site (What’s afriend worth?, 2009).

As in the IBM case, an internal social networking site can become an effective tool for internal collaboration and innovation. Thus, the issue for organizations should not be if but how can they encourage their employees to participate in the organization’s internal social networking sites. Traditional adoption factors for enterprise information systems, such as ease of use and perceived usefulness, would not work as effectively for SNS adoption because those factors were validated for adoption of information systems based on management decisions. SNS adoption is an individual and voluntary decision by each employee, not a managerial decision, and it supports horizontal communication across the

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organization. Thus, we need to find other meaningful factors influencing employees’ decision to participate in internal SNS.

The results of this study strongly suggest that adoption of internal SNS, among other benefits, can be an important factor for improving organizations’ entrepreneurial culture. Encouraging employees for active participation in SNS can strengthen horizontal communication and collaboration culture in the organization, thus boosting EO (in all its dimensions: innovation, risk taking, autonomy, and competitive aggressiveness). This in turn will shorten innovation life cycles and decision making and increase the competitiveness of the organization. Creating extensive internal and external networks will bring not only more opportunities but also more risk which will require real entrepreneurial skills, thus further intensifying the importance of developing EO culture by organizations.

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