A MEASUREMENT INSTRUMENT FOR INDIVIDUAL

INFORMATION COMPETENCY IN AN ENTERPRISE

INFORMATION ENVIRONMENT

Chui Young Yoon and Keon Myung Lee

College of Electrical & Computer Engineering, Chungbuk National University, 410 Sungbong-Ro (Gaeshin-dong)

Heungduk-gu, Cheongju city, Chungbuk, 361-763, South Korea

Keywords: Information Competency, Measurement Factor, Measurement Instrument, Measurement Process.

Abstract: An instrument that can efficiently measure individual information competency is presented to develop and

manage the information application ability of individual working in an enterprise information environment.

The measurement items are extracted from the major components of a competency. By factor analysis and

reliability analysis, a 14-item instrument is proposed to entirely measure individual information capability.

The tool’s application and utilization are discussed through a case study and the presentation of its results.

1 INTRODUCTION

Today, information technology (IT) progression

makes data resources and information systems (IS)

become firm’s critical strategic resources. (Wu et al.,

2005). The efficient utilization of IT in a firm is a

critical factor to effectively improve its task

performance and competitiveness in an information

environment. It is important for human resources

working in an enterprise information environment to

have the capability to effectively execute the given

tasks by applying their information systems to their

business. (Mathis and Jackson, 2000; O’Leary,

2002). An individual who directly executes his or

her business needs the ability to efficiently perform

individual tasks by applying IT and information

systems to his or her business in an enterprise

information environment.

Hence, this study presents an instrument to

measure the individual information competency,

which focuses on the entire information capability

that an individual can efficiently use information for

his or her tasks in an enterprise information

environment.

2 THEORETICAL RESEARCH

In previous literature, an end-user was defined as a

person who directly interacts with his or her

computer. (McHaney et al., 2002; Rondeau et al.,

2006; Wu et al., 2007). Based on these studies, we

can define an individual as a person who directly

interacts with his or her information systems.

In previous literature, competency was defined

as effective application of available knowledge,

skills, attitudes, and values in complex situations.

(Govindarajulu and Reithel, 1998; Bassellier et al.,

2001; Tanner, 2001). Namely, the major components

of a competency are knowledge, skills, concepts,

and development. Individual competency is used to

deal with the competence of a person, the collective

competency is used to deal with the competence

emerging from a group of persons, and global

competency is used to describe the organizational

ability of an enterprise. (Boucher et al., 2007).

By summarizing prior researches, an individual

information competency (IIC) can be defined as the

total capability that an individual can efficiently

apply information knowledge, skills, attitudes, and

values to his or her tasks to execute the given tasks

in an enterprise information environment. In other

words, IIC is defined as the total capability that an

individual directly interacts with his or her

information systems to efficiently perform the given

tasks through using an organizational data and

solutions on information systems. IIC is the entire

information capability that an individual can

effectively do his or her tasks on an enterprise

information system. Based on the definitions and

components of IIC, this study generated the 27

101

Young Yoon C. and Myung Lee K. (2010).

A MEASUREMENT INSTRUMENT FOR INDIVIDUAL INFORMATION COMPETENCY IN AN ENTERPRISE INFORMATION ENVIRONMENT.

In Proceedings of the International Conference on e-Business, pages 101-106

DOI: 10.5220/0003045601010106

 SciTePress

measurement items that can gauge IIC in an

enterprise information environment. (Govindarajulu

and Reithel, 1998; Bassellier et al., 2001; Tanner,

2001; Boucher et al., 2007; Torkzadeh and Lee,

2003; McCoy, 2001).

3 METHODS

Previous literature proposed methods to verify the

validity and reliability of the model construct. Most

studies presented two methods for a model construct

validation: (1) correlations between total scores and

item scores, and (2) factor analysis. (Brancheau and

Brown, 2002; McClelland, 1973; Boyatiz, 1982;

Jacobs, 2002). Torkzadeh and Doll (1999) and

Torkzadeh and Lee (2003) used correlation analysis

to verify the validity of the model construct. Etezadi-

Amoli and Farhoomand (1996), and McHancy et al.

(2002) utilized factor analysis to verify the validity

of the model construct. We verify the validity and

reliability of the instrument construct and extracted

adequate measurement items by factor analysis and

reliability analysis. The ratio of sample size to

number of measurement items (11:1) was above the

minimum (10:1) ratio suggested for factor analysis

by previous literature. (Torkzadeh and Lee, 2003;

Rodriguez et al., 2002). The measurement

questionnaire used a five-point Likert-type scale;

where, 1: not at all; 2: a little; 3: moderately; 4:

much; 5: a great deal. The questionnaire is

composed of two response domains: one is answer

to general data of respondents, such as degree, age,

gender, major field, industry and business

department, business position level and years of job

experience; the other is response to the measurement

items.

3.1 Sample Characteristics

A sample of 243 usable responses was obtained

from a variety of industries and business

departments, and from management levels. The

respondents in terms of business departments were

identified as strategy planning (21.1%), development

and maintenance (26.8%), business application

(38.4%), and administration support (13.7%). The

respondents identified themselves as top manager

(3.7%), middle manager (44.7%), and worker

(51.6%). The respondent had on average of 8.9 years

of experience (S.D. =1.118) in their field, their

average age was 32.9 years old (S.D. =6.473), and

their gender, male (79.8%) and female (20.2%).

3.2 Analysis and Discussion

Items were excluded when their correlation with the

collected item-total was < 0.5 or when their

correlation with the criterion scales was < 0.6.

(Torkzadeh and Lee, 2003; Rifkin et al., 1999;

McCoy, 2001). The correlations with the corrected

item-total and the criterion item were significant at p

≤ 0.01 and similar to those used by others in

previous researches. (Torkzadeh and Lee, 2003;

Rifkin et al., 1999; McCoy, 2001). After these

analyses, the first 27 measurement items were

reduced to 14 items, with 13 items were deleted. The

elimination was sufficiently considered to ensure

that the retained items were adequate measures of

IIC. The validity and reliability of the instrument

were verified by factor analysis and reliability

analysis. They were used to identify the underlying

factors or components that comprise the IIC

construct. These deletions resulted in a 14-item scale

for measuring IIC. Each of the 14 items had a factor

loading > 0.637. The reliability coefficients

(Cronbach’s alpha) of four potential factors had

values > 0.797, above the threshold recommended

for exploratory research. (Rodriguez, 2002). The

descriptions and loadings for the 14 items are

presented in Table 1 and Table 2.

Table 1: Factor loadings obtained from factor analysis.

0.659V26

0.732V19

0.756V23

0.779V17

0.794V16

0.811V12

0.872V18

0.699V11

0.741V13

0.765V08

0.881V10

0.637V03

0.762V06

0.794V04

Factor 4Factor 3Factor 2Factor 1

Factor Loadings

Variable

0.659V26

0.732V19

0.756V23

0.779V17

0.794V16

0.811V12

0.872V18

0.699V11

0.741V13

0.765V08

0.881V10

0.637V03

0.762V06

0.794V04

Factor 4Factor 3Factor 2Factor 1

Factor Loadings

Variable

To examine the reliability and validity of the

measures, we calculated the corrected item-total

correlations between each variable and its

corresponding factor. These correlations along with

alpha coefficients of each factor are presented in

Table 2. This also shows the alpha coefficients for

the measurement of factors if a measure was deleted

from the scale. These coefficients indicate the

relative contribution of a measure to the construction

of a scale for measuring a particular factor. They are

all in the acceptable range. Most corrected item-total

ICE-B 2010 - International Conference on e-Business

102

correlations were greater than 0.600, showing that

the individual measures are good indicators of their

corresponding factors.

Table 2: Corrected item-total correlations and the

coefficient alphas of 14-measurement items.

0.7120.679V19

Coefficient alpha for the above 3 items as a composite measure of

Factor =0.797

0.6120.648V26

0.7210.819V23

0.8020.735V17

Coefficient alpha for the above 4 items as a composite measure of

Factor =0.813

0.8490.821V16

0.7780.785V12

0.8170.841V18

Coefficient alpha for the above 4 items as a composite measure of

Factor =0.903

0.7360.789V11

0.7490.781V13

0.8120.744V08

0.8450.812V10

Coefficient alpha for the above 3 items as a composite measure of

Factor =0.823

0.6530.670V03

0.7910.721V06

0.7350.681V04

Alpha if item deleted

Corrected item-total

correlation

Variable

0.7120.679V19

Coefficient alpha for the above 3 items as a composite measure of

Factor =0.797

0.6120.648V26

0.7210.819V23

0.8020.735V17

Coefficient alpha for the above 4 items as a composite measure of

Factor =0.813

0.8490.821V16

0.7780.785V12

0.8170.841V18

Coefficient alpha for the above 4 items as a composite measure of

Factor =0.903

0.7360.789V11

0.7490.781V13

0.8120.744V08

0.8450.812V10

Coefficient alpha for the above 3 items as a composite measure of

Factor =0.823

0.6530.670V03

0.7910.721V06

0.7350.681V04

Alpha if item deleted

Corrected item-total

correlation

Variable

Hence, the measurement items, with a validity and

reliability, were extracted by carrying two analyses

as shown in Table 1 and Table 2.

4 MEASUREMENT

INSTRUMENT

These analyses classified the extracted items as 4

factor groups. These factor groups indicate the

potential major factors to measure the IIC. With

investigating the measurement items of each factor,

we generated the 4 potential factors as follows:

factor 1: information concepts; factor 2: information

knowledge; factor 3: information utilization; and

factor 4: information development. The 4 potential

factors are considered the major factors of the

instrument construct. Figure 1 shows the structure of

the measurement instrument based on the 4 potential

factors and 14 items. Each factor has three or four

measurement items as shown in Figure 1.

Information Concepts (IC)

IC04 Do you understand future information progress ?

IC06 Do you think that information is important for management activities ?

IC03 Do you consider ethics and morality when using information ?

Information Knowledge (IK)

IK10 Do you know your firm’s information systems ?

IK08 Do you know of the solutions of your firm’s information systems ?

IK13 Do you know security measures for your firm’s information systems ?

IK11 Do you know packaged application software in your firm’s information systems ?

Information Utilization (IU)

IS18 Can you perform your tasks in your firm’s information systems?

IS12 Can you use packaged application software in your firm’s information systems?

IS16 Can you use your information systems for e-Business and m-Business ?

IS19 Can you use a groupware solution to efficiently execute a team project ?

Information Development (ID)

IV17 Do you have obtained degrees or certificates related to information departments ?

IV23 Do you have completed the education and training related to information

departments ?

IV26 Do you have suggested the improvement of your firm’s information systems ?

Information Concepts (IC)

IC04 Do you understand future information progress ?

IC06 Do you think that information is important for management activities ?

IC03 Do you consider ethics and morality when using information ?

Information Knowledge (IK)

IK10 Do you know your firm’s information systems ?

IK08 Do you know of the solutions of your firm’s information systems ?

IK13 Do you know security measures for your firm’s information systems ?

IK11 Do you know packaged application software in your firm’s information systems ?

Information Utilization (IU)

IS18 Can you perform your tasks in your firm’s information systems?

IS12 Can you use packaged application software in your firm’s information systems?

IS16 Can you use your information systems for e-Business and m-Business ?

IS19 Can you use a groupware solution to efficiently execute a team project ?

Information Development (ID)

IV17 Do you have obtained degrees or certificates related to information departments ?

IV23 Do you have completed the education and training related to information

departments ?

IV26 Do you have suggested the improvement of your firm’s information systems ?

Measurement

Instrument of

IIC

Information

Concepts

(IC)

Information

Utilization

(IU)

Information

Knowledge

(IK)

Information

Development

(ID)

V04 V06 V03 V10 V13 V11 V18 V19 V17 V23 V26

V08 V16V12

Figure 1: Structure of measurement instrument.

4.1 Measurement Factors and Items

This instrument has 4 major factors to measure IIC

in an enterprise information environment.

Information concepts mean state of mind,

feelings, and belief related to IT. It includes the

measurement items that can identify individual

attitude on the future IT progress, IT importance for

a firm, and ethic and morality in using information

on an enterprise information system.

Information knowledge indicates complex

process of remembering, relating or judging

information to efficiently use an information system.

Namely, information knowledge represents IT

knowledge to effectively perform the given tasks on

an enterprise information system. It comprises the

items that can gauge IT knowledge related to

hardware, software, networks, and database for a

firm information system, knowledge of packaged

application software related to ERP, SCM, and CRM,

knowledge related to e-Business (B2E, B2C, and

B2B), and knowledge related to security measures in

a firm’s information system.

Information utilization is the ability that utilizes

information to perform specific mental or physical

tasks, and includes mental or cognitive skills.

Information skills mean the ability that an individual

utilize IT knowledge, solutions, and information

systems to his or her tasks. It contains the skills as

follows: utilization of network and server; use of

A MEASUREMENT INSTRUMENT FOR INDIVIDUAL INFORMATION COMPETENCY IN AN ENTERPRISE

INFORMATION ENVIRONMENT

103

packaged application software, such as ERP, SCM,

and CRM; use of the information systems for e-

business of the form B to E, B to C, and B to B; and

the skills to use the security measures in a firm’s

information system.

Information development refers to the endeavor

to improve knowledge and skills related to

information. It provides the potential ability to

efficiently improve IIC. It has the items that can

measure an individual mind on degrees and

certificates, domestic and overseas educations and

trainings, and suggestion for the improvement of

your information systems. This is the important

factor for the extension of information capability in

terms of the breadth and depth of IIC.

This instrument is a crucial theoretical construct

to measure an individual’s total information ability

that can efficiently do his or her tasks in an

enterprise information environment.

5 MEASUREMENT PROCESS

5.1 Framework of Measurement

Process

The measurement process has two main stages,

including the measurement stage and presentation

stage of the measurement results (Figure 2). The

measurement stage examines individuals by a

questionnaire based on 4 measurement factors and

14 items. The measurement results are analyzed by

extracting the measurement values of each factor

and by applying each weight value to the

measurement values of each factor.

The presentation stage provides the measurement

results based on each factor. The results are

explained by each measurement index extracted

from each factor. The interpretation of the results

presents the present states and problems of the IIC,

and the directions and methods to efficiently

improve the IIC based on the extracted measurement

indices.

5.2 Measurement Method

We used the weight values for each measurement

factor in order to develop an efficient instrument

considered the relative importance of each factor in

measuring IIC. The weight values, Table 3, were

extracted from the analysis results of the

questionnaire survey (AHP) for about 30 experts

working in our IT research center.

Start

Measurement Instrument

(IT Concepts, Knowledge,

Utilization, and Development)

Measurement

Item

Database

Performing

Measurement or Checking

Results ?

Measurement Execution

(4 Measurement Factors/14 Items)

Measurement System

(ID/PW)

Personal

Information

Database

Analysis of Measurement Results

(Extraction of Measurement Index)

Presentation of Measurement Results

(Problems and Improvement Methods)

Weight Value

Database

(4 Factors)

End

Measurement

Results

Database

Check

Perform

Start

Measurement Instrument

(IT Concepts, Knowledge,

Utilization, and Development)

Measurement

Item

Database

Performing

Measurement or Checking

Results ?

Measurement Execution

(4 Measurement Factors/14 Items)

Measurement System

(ID/PW)

Personal

Information

Database

Analysis of Measurement Results

(Extraction of Measurement Index)

Presentation of Measurement Results

(Problems and Improvement Methods)

Weight Value

Database

(4 Factors)

End

Measurement

Results

Database

Check

Perform

Figure 2: Measurement process.

The measurement method first calculates the

measurement values of each factor based on the

analysis results that an individual is tested by the

measurement items of each factor. It figures out the

measurement indices of each factor by multiplying

each weight value by the measurement value of each

factor.

Table 3: Weight values for each measurement factor.

0.22Information Development

0.33Information Utilization

0.25Information Knowledge

0.20Information Concepts

Weight ValueMeasurement Factor

0.22Information Development

0.33Information Utilization

0.25Information Knowledge

0.20Information Concepts

Weight ValueMeasurement Factor

The measurement index (MI) means the value

extracted by multiplying the weight value by the

measurement value. The sum of the measurement

indices of each factor becomes the individual entire

MI.

Hence, the measurement index (MI) of each

factor can be presented as Equation (1).

MFi

= MV

MFi

x WV

MFi

(1)

Where, MI

MFi

: Measurement index (MI) of the i th

Measurement Factor

MFi

: Measurement Value (MV) of the i th

Measurement Factor

ICE-B 2010 - International Conference on e-Business

104

MFi

: Weight Value (WV) of the i th

Measurement Factor

Here, the sum of the weight values of each factor

is 1.00 and i = 1, 2, 3 and 4 indicate four

measurement factors.

Therefore, the total MI can be defined as Equation

(2) by Equation (1):

Total MI = ∑ MI

MFi

i=1

(2)

Here, the i = 1, 2, 3 and 4 mean the four

measurement factors.

In this way, this instrument presents the

measurement results of IIC based on the total MI

and measurement indices of each factor. The

problems of the IIC are presented by the results. The

efficient methods to improve the IIC are also

provided by the total MI and measurement indices of

each factor.

6 CASE STUDY AND

DISCUSSION

This case study applied the developed tool to 137

workers working in “B” enterprise, Republic of

Korea.

6.1 Analysis and Discussion: Overall

Organization

We presented the measurement results of each

business department and overall organization. The

total MI of the overall organization was 62.73, and it

was quite high. The business application department

(BAD) and the administration support department

(ASD) were 65.27 and 63.16 as shown in Figure 3.

The measurement results of each business

department represented that the MI of the BAD was

higher than those of the other departments. This is

due to the ability to effectively accomplish their

tasks by frequently applying information knowledge

and systems to e-Business of the form B to C, B to B

and B to E, and the knowledge and abilities to utilize

the various solutions, such as ERP, SCM, and CRM

to effectively perform their business tasks on an

enterprise information system.

63.16

65.27

60.36

62.14

62.73

Total

Measurement

Index

Strategy

Plan

Department

Development

Maintenance

Department

Business

Application

Department

Administration

Support

Department

Figure 3: Measurement indices of each business

department and overall organization.

Figure 4 presents the measurement indices of each

factor for each business department within the

organization. The MI of the BAD in all

measurement factors was higher than those of the

other departments. Especially, the BAD was very

high level in information utilization. It indicates that

the BAD had the distinguished skills to utilize

information solutions and systems to efficiently

perform the given tasks. The strategy plan

department (SPD) was quite high in the information

development. It means that they completed the

endeavor to improve knowledge and skills related to

information

65.27

62.36

62.06

61.89

62.25

62.14

59.34

60.04

58.85

60.36

63.21

61.95

70.26

66.29

62.58

60.16

66.43

64.21

61.84

63.16

Total MI Information

Concepts

Information

Knowledge

Information

Utilization

Information

Development

SPD DMD BAD ASD

Figure 4: Measurement indices of each factor for each

business department.

6.2 Analysis and Discussion: an

Individual

The total MI of the individual was 64.89, and it was

a little high. Especially, the MI of the information

utilization was very high. This means the

outstanding skills to utilize the information

knowledge, solutions, and systems to his or her tasks

in an enterprise information environment. However,

A MEASUREMENT INSTRUMENT FOR INDIVIDUAL INFORMATION COMPETENCY IN AN ENTERPRISE

INFORMATION ENVIRONMENT

105

the MI of the information concepts and development

were low as indicated in Figure 6.

62.47

64.01

63.16

68.17

64.89

Total

Measurement Index (MI)

Information

Concepts (IC)

Information

Knowledge (IK)

Information

Utilization (IU)

Information

Development (ID)

Total

Measurement Index (MI)

Information

Concepts (IC)

Information

Knowledge (IK)

Information

Utilization (IU)

Information

Development (ID)

Figure 6: Measurement indices of an individual in the

BAD.

Therefore, this individual should make an effort to

improve the information concepts and development

to effectively raise his or her information

competency in general.

7 CONCLUSIONS

We presented an instrument that can efficiently

measure an IIC in an enterprise information

environment. This instrument includes structure,

concrete items, and measurement process and

method. This instrument has a nature as a global

standard across industries, and business departments

and positions.

Therefore, this study provides an instrument that

can measure IIC required to efficiently execute an

individual’s given tasks in an enterprise information

environment.

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