TECHNOLOGY COMPONENT STATUS IN SMALL AND MEDIUM SIZED

ENTERPRISES: A STUDY OF THE MANUFACTURING SECTOR IN KEDAH

MAZRI YAAKOB

NOR HASNI OSMAN

RUSHAMI ZEIN YUSOF UUM College of Business

Universiti Utara Malaysia

ABSTRACT

This paper elaborates on four interrelated components of technology, namely

“Technoware”, “Humanware”, “Infoware”, and “Orgaware”, all of which has its own

unique elements. As many as 51 owners of small and medium sized enterprises (SMEs)

in Kedah were chosen as the main respondents for this study. SMEs were chosen

because SMEs are among the main contributors of the gross national product (GNP).

Information related to SMEs in Kedah was obtained through the SME Corp Malaysia,

FMM, and PKNK directories. The face-to-face interview and postal survey

questionnaire techniques were employed to get the required data. This research

endeavour aimed at establishing the status of technology components in SMEs by using

the technology component weighted measure adopted from Saaty, which is known as

Analytical Hierarchy Process (AHP) as the current technology status indicator of SMEs

in Kedah. The results of the analysis revealed a high tendency toward the adoption of

the Orgaware component, followed by Technoware, Humanware, and Infoware.

Keywords: Technology component; small and medium sized enterprise; manufacturing

sector; Analytical Hierarchy Process

INTRODUCTION

SMEs have given a significant contribution toward the national economy, more

specifically in the context of the Kedah state of Malaysia. This matter can be observed from the increasing numbers of newly established SMEs every year. According to the Central Bank

Report (Bank Negara Malaysia - BNM) and Enterprise and Establishment Consensus

(Consensus) for 2005, it was shown that 99.2% of the overall establishment of new businesses had totalled 518,996 SME businesses. The SMEs workforce totalled more than 3 million

workers and this group generated and added value of RM154 billion in 2003 (BNM, 2005).

Small and medium sized enterprises, or better known as SMEs, in Malaysia have experienced rapid development. This development has been mainly assisted by efforts of the

government through its initiatives and incentives. This matter is obviously highlighted through

the establishment of various government agencies that are directly involved in the in the development and spread of SMEs, such as Small and Medium Industries Development

Corporation (SMIDEC), National SME Development Council (NSDC), Small and Medium

Enterprise Bank (SME Bank), and many more. To ensure the rapid growth of SMEs is maintained, several strategic plans are also formed and included in the Third Industrial Master

Plan (2006-2010) and now in the Ninth Malaysia Plan (RMKe-9). The development and use of

science and technology in order to improve productivity is one of the important matters the

government has emphasised upon. In addition to the facilities and financial loans, various programmes like courses and training has been organised to give exposure, knowledge, and

skills to the SME operators.

However, there are still barriers to have caused some operators to not benefit from all

these golden opportunities. Even though the SME operators are widely aware of the need and

importance of high technology, the lack of financial funds to buy and own certain technologies

has become their main obstacle (Yip, 2007). The selection of suitable products or services that

are capable of giving a positive impact on the business and thus continue to contribute toward

business growth in the mid- and long-term have become major issues with SMEs. However, without the necessary in-depth skills to use computerised systems or investing in new

technology, then surely the effects of technology procurement or transfer would be very limited.

In finding a business solution, SMEs must be capable of evaluating their options based

on the strategies and requirements of the business in the long-term. Among the factor that

should be considered include those from the financial perspective, relationship management

between the customer and equipment, and also managing the supply chain, all of which would help the SMEs to automate processes, make profitable decisions, as well as to facilitate

company growth. According to Jantan (2004), other than acting as an agent of change, an

organisation or a firm generally makes the technology as the turning point in making a strategic decision. Therefore, technology development should not be taken lightly by the SMEs.

Previous studies had proven that technology development is among the most important

factors that can assist in the economic growth of a nation (Hirano, 1985; Choi, 1987; Subramaniam, 1987; Sharif & Ramanathan, 1991), country development, and also the industry

and organisation directly contributes toward the improvement of the quality of life of the

residents of a country (Sawers, Pretorius & Oerlemans, 2008). Other studies have shown that in order to ensure that the technology can help in improving the capability of the industry and

firms, the technology needs to be managed effectively and efficiently (Pretorius, 2006). Some

researchers stated that technology is the “wealth of [a] nation” (Sharif & Ramanathan, 1991).

From the literature review, there had not been much empirical research performed to

investigate the importance of each technology component in the industry, including the

manufacturing industry. Smith (2005) stated that in order to conquer a market segment, there needs to be an organised strategy to compete against rivals, and also the capability and resources

for effective implementation in innovative technology by the firm. Furthermore, Smith (2005)

defined that the resources of a company mentioned here refer to Technoware, Humanware, Infoware, and Orgaware. It was revealed that there are not many studies that focus on

technology components that contribute toward the success of an organisation in the

manufacturing industry. According to Sharif (1997), the important characteristics of the relationships of the four technology components have not been highlighted or been given the

due attention.

SMEs should be aware of the importance of these technology components that can help them to improve their businesses. Therefore, this study aimed at identifying the status or level of

importance of these technology components within the manufacturing industry. This write-up

will discuss the characteristics that define these types of technology components, the methodology as well as analysis used in investigating the importance of technology components

in the context of the SME manufacturing industry. It is hoped that the finding of this research is

able to assist the related parties in establishing the importance of these technology components

in investment and decision making.

LITERATURE REVIEW

Technology

There are various definitions for technology that has been previously discussed in academia. The definition or meaning of technology continuously changes from time to time

depending on the advancement of human understanding about technology and the changes that

are observed by a company or organisation (Jantan, 2004). The Webster dictionary defined technology as the use of practical science for trade or industry; a discipline related to arts or

science using scientific knowledge for solving a practical problem and a branch of knowledge

that involves industrial study, applied science, and engineering (Webster’s Online Dictionary,

2005). In general, technology is often related to equipment, tools, computers, and electronic

gadgets. However, technology is not limited to just physical machines only (Jantan, 2004).

Technology is defined as an integration of human aspect, knowledge, equipment, and

systems with the ultimate objective of improving the human way of life (Proterious, 2006).

Equipment and systems contain certain procedures for establishing knowledge. Meanwhile, knowledge creation is through training (Pretorious, 2006). Khalil (2000) and Jantan (2004)

further elaborated that technology is not just about the physical sense like equipment,

machinery, and others, but it is also about the non-physical, such as skills, experience, knowledge, and wisdom. Table 1 shows the definitions of technology by various researchers.

Table 1.

Technology definition by previous researchers

Penyelidik Definisi Teknologi Tahun

Rousseau An organisational phenomenon that refers to knowledge being used to perform a

task

1979

Zeleny Covers four interrelated components:

- hardware

- software - brainware

- know-how

1986

Price Know-how used in basic science or products, equipment, and process to achieve

the desired solution

1996

Khalil All knowledge about products, equipment, processes, methods, and systems used

to create goods or services by an organisation

2000

Narayanan A process, invention, method, or procedure where a social group creates

something that is needed by the organisation

2001

Technology Component

Zeleny (1986) used the term technology entity and Bhalla (1987) used technology

element. Both also stated that technology comprises entities/elements that are different from the

views of other researchers. Zeleny (1986) highlighted that each technology contains four entities, namely hardware, software, brainware, and know-how. Bhalla (1987) defined

technology as having several elements, which are physical things like tools, software aspects

including computer programs and information systems. Other technology components that have been revealed and agreed upon by other researchers went under different names and terms.

Leonard-Barton (1992) used the term technology dimension, Islam and Hossain (1999) termed it

as technology resource, while Autio (2006) used the phrase technology strategy and management aspect.

Masum (1992) explained Technoware, including all the physical facilities like

instrument, tools, generators, equipment, structure, and factory. Humanware consists of all the required needs, such as expertise, capability, agility, creativity, fortitude, hardworking,

perseverance, and wisdom. Infoware comprises all forms of facts, including designs, accounts,

specifications, observations, relations, similarities, charts, and theories. Meanwhile, Orgaware refers to the framework covering groups, budgeting, systems, organisations, networks,

management, and marketing.

Other characteristics of technology components, for example Technoware, refer to the

manifestation of physical technology, such as the car engine, microchip, and software package

to name but a few. Humanware refers to the individual technology expertise, while Infoware

contributes clearly about the physical manifestation, and finally Orgaware refers to the skills of the organisation and its manifestation in organisational processes and routines (Parhankangas,

Holmlund, & Kuusisto, 2003).

From another perspective, Autio (2006) stated Technoware refers to the hardware,

combination, and also design and Humanware refers to the human capabilities, capacities, and practice that influence that application of technology and self development. Infoware refers to

the software related to the hardware, which is the understanding of the task of a technology item

that is given, the knowledge on how to operate the said technology item for example the manual, understanding the related operational principles like physical science, and also the

technology that has been documented, for example patenting. Finally, Orgaware refers to the

competitiveness and capabilities of the organisation which is related to the development of new

applications and operations as a step for creating value for the customer.

Even though there are many different characteristics of Technoware, Humanware,

Infoware, and Orgaware that were described, most are similar with minor differences between the components of technology and also the characteristics of the technology components

themselves. Table 2 shows that characteristics of each technology component that were

identified and categorised into seven aspects (UN-ESCAP, 1989).

Table 2.

Technology component characteristics category

Component Category

Technoware Manual facilities, powered facilities, general purpose facilities, specific purpose

facilities, automatic facilities, computerised facilities, and integrated facilities

Humanware Operating abilities, setting-up abilities, repairing abilities, reproducing abilities,

adapting abilities, improving abilities, and innovating abilities

Infoware Familiarising facts, describing facts, specifying facts, utilising facts, comprehending

facts, generalising facts, and assessing facts

Orgaware Striving framework, tie-up framework, venturing framework, protecting framework, stabilising framework, prospecting framework, and leading framework

Source: UN-ESCAP (1989)

METHODOLOGY

Data and Sample

Based on the information that was obtained from SMIDEC, FMM, and PKNK, there were 305 manufacturing companies operating in Kedah. The list of names and addresses obtained from

these organisations became the research population frame. Based on Krejcie and Morgan

(1970), as many as 169 companies need to be chosen as the research sample. A total of 38 owners/managers or those who were involved in the management of the SME companies was

successfully interviewed. The questionnaire was also distributed by post, and only 13

respondents returned sufficiently completed questionnaires. Therefore, the total respondents for this survey were 51 respondents. According to Lam and Zhao (1998), as well as Cheng and Li

(2002), a large sample size is not mandatory in research that involves the use of AHP.

Research Analysis and Measurement Scale

The scale used in this research is the ratio scale, which is interval data arranged

beginning with the smallest number and ending with the largest (Piaw, 2008). The smallest number represents the smallest value while the largest number represents the largest value.

According to Piaw (2008), the ratio scale contains the true zero value and the distance between

scales are the same, so mathematical calculation can be performed.

In this research, the ratio scale in the form of percentages was used. The scale

arrangement starts at 0 and ends in 100 (marked at every five intervals). The values marked by

the respondent were adapted to the Saaty scale. The measurement for the technology

components in this research was based on Saaty’s method, which is also known as the AHP. It

is used for selecting and arranging 24 dimensions placed under four technology component categories according to the research subjects chosen among the SME operators in Kedah. This

method is flexible because it can conduct subjective evaluation on both qualitative and

quantitative factors. This research had taken the general approach used in AHP, which are

paired comparisons. Before the selection and arrangement of elements according to importance are performed, the respective technology components following the elements are measured

using the Saaty coupled scale. However, in order to achieve the objectives of this research,

modification of the measurement was performed.

Based on the recommendation by Saaty (1980), an issue or a problem is a complex

system and can be broken down into subsystems and thus be represented in hierarchical form.

The top most hierarchy is the overall aim and below it are several criteria and sub-criteria for each alternative. There are several phases during the use of Saaty’s method. Several researchers

had divided it into just two phases, namely the hierarchical design phase and evaluation phase

through the paired comparison (Barker, Shepperd, & Aylett, 1999; Santillo, 2000). There are also others who divide the method into three phases, which are system structuring, paired

comparison, and main synthesis (Choi, 2000; Shin, 2000). Furthermore, there are researchers

who divide the process into four phases, namely hierarchical construction, paired comparison, relative and alternative priority estimation (weight) criteria, and finally ranking in order of

importance (Drake, 1998; Frair et al., 1998; Choirat & Seri, 2001; Kinoshita, Sekitani, & Shi,

2001).

During this research, the approach by Liang (2003) was used as reference. Table 3

explains the five main steps for obtaining a weightage score using the AHP approach. These

steps were applied from Liang (2003).

Table 3

Explanation of steps to obtain weightage

Steps Explanation

Step 1:

Build hierarchical structure

Hierarchical structure in AHP is used to confirm the element and

alternative that are involved in decision making, or in other words, to

attain the objective. The built hierarchy depends on the complexity of the

problem that is being analysed and the elements, which should not be too

numerous in the hierarchy.

Step 2:

Perform paired comparison

in matrix form

Paired comparison is performed to obtain the relative importance values

for each element involved. The nominal scale introduced by Saaty

(starting from 1/9 to 9) is used to measure the relative importance value.

Step 3:

Obtain eigen vector and maximum eigen value

Significance is obtained from the eigen vector from the paired comparison

matrix, which measures the degree of importance for each element and at the same time, the value of the maximum eigen value (1) can be obtained.

This value is used to establish the consistency toward the comparison

being made.

Step 4:

Calculate the consistency

index (CI)

If the paired comparison matrix is consistent, the maximum eigen value

(1) should equal the number of elements being compared (n). Thus, the

difference can indicate the degree of consistency. The consistency ratio

(CR) is calculated to confirm the degree of consistency. The CI that is

presented in this research used the following formula:

CI = (λmax – n)/(n – 1)

If CI ≤ 0.1, the level of consistency is accepted. Otherwise, another

evaluation has to be performed.

Step 5:

Obtain overall weightage score

In AHP analysis, paired comparison is used to establish the importance

values for each element. By multiplying the eigen vector (criteria and sub-criteria – in the hierarchical structure), the overall wieghtage score can be

obtained.

Source: Liang (2003)

Decision Hierarchy

The first phase of the Saaty method is to present the problem in a hierarchical form that contains certain elements. Normally, the overall objective for a problem is placed on the top of

the hierarchy, as shown in Figure 1. At level 1, the elaboration of the problem into several main

criteria is performed, which is followed by further explanation if there exists at level 2 several sub-criteria. In the final level 3, all involved alternatives are listed. A decision hierarchy can

change and follow various forms following its suitability with the problem at hand.

Rajah 4.2: Hierarki keputusan

Figure 1. Phase 1 of the decision hierarchy

Comparison of each Element in Pairs (Coupled)

All elements found in the decision hierarchy at levels 1, 2, and 3 are measured using the

paired comparison (pc). The use of the Saaty scale, as explained in Table 4, aimed at evaluating the importance rate trend between two elements at the same level.

Table 4 Explanation of Saaty scale

Importance Definition Description

1

3

5

7

9

2,4,6,8

Same importance

Moderate domination

Strong domination

Stronger domination

Strongest domination

Mediating values

Elements i and j contributes equally to the objective

Element i is more important than element j

Element i is of strong importance compared to element j

Element i is of stronger importance compared to element j

Element i is of strongest importance compared to element j

There is give and take between the two scales

1

9,1

8,..,

1

2

If there is an occurrence where element j is more important

than element i, then follow the importance as stated above

Source: Saaty (1980)

After all elements were compared pair-wise, the evaluation matrix of dimension d x d

form. For example, if the elements at the second level consist of four criteria, then the matrix is a 4 x 4 matrix.

Then the comparison values between two different elements under the same criteria are

compared using the ratio concepts. Assume that element i has a value of 5 and element j equals 7, then the paired comparison value of element i toward j is 5/7. The same goes for when

Objective

Criteria

Sub-criteria

Alternative

Level 1

Level 2

Level 3

element j is compared to i, thus its value is 7/5, which is equal to 1/(5/7). This method still

maintains the interval concept like the Saaty scale.

Calculation of Relative Weightage for each THIO Component and Elements

The calculation of the weightage is through paired comparison matrices, which is A = (aij) = (wi /wj), where wi and wj are the ith and jth relative importance separately. Each entry A is

positive and fulfils aji = 1/aij = wj/wi . Matrix A is shown below:

A =

1,2 1,

2,1 2,

,1 , 1

1

1

1

n

n

n n n

a a

a a

a a

If matrix A is consistent, meaning that aij = aik /akj for each i, j, and k, then A is the arrangement unit because each row is a permanent multiple to the first row. This causes the

eigen value to cevome zero ((A – n1)w = 0) except one eigen value only, that is n because Aw =

nw where w = (w1, w2..., wn)kT

. The consistency formula is given as shown below (Saaty, 1990, 1999; Santillo, 2000).

Aw =

1

1 1

1 1 1

1

1

n

n

n n n

n n

n

A A

w wA w w

w wn nw

A w ww w

w w

If the values for each wi / wj cannot be obtained, then an estimation needs to be

performed. Therefore, matrix A can become inconsistent even though there exist intervals. This matter can be explained through the eigen value theory by Wilkinson (1965), which is often

referred to by users of AHP, including Saaty (1990) and Choi (2000) who stated that small

errors in concise eigen values can lead toward problems in eigen value in the form of Aw = λmaxw where λmax is the main eigen value to A that is no longer consistent but still has intervals.

Meanwhile, Shin (2000) refers to this matter as fuzzy nature that cannot be avoided.

Next, Saaty (1990) proved that λmax ≥ n for each positive interval matrix. Equilibrium

only occurs when matrix A is consistent. Therefore, relative importance depend on the relative

amplitude to component vector w, thus we need to normalise w by resolving the equality below

(Fogliatto & Albin, 2001; Saaty, 1999; Shin, 2000; Triantaphyllou & Shu, 2001):

1

1n

i

i

w

Measurement of Consistency Degree for Validating Decision

In order to measure the extent of consistency for each criterion that is compared, Saaty’s

method has produced CR values according to the following: CR = CI/RI

CI = consistency index

= (λmax – n)/(n – 1)

n = number of elements being compared

RI = random index

= average CI toward random interval matrix for the dimension from the scale

{1

9,1

8,..

1

2, 1, 2,..., 8, 9}

The value of each RI for each n is shown in Table 5.

Table 5

RI values for each different n value

N 1 2 3 4 5 6 7 8 9

RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45

Source: Saaty (1990)

If matrix A is consistent, then both CR and CI are zero because λmax – n = 0. In other

words, as A becomes more inconsistent, the values of CR and CI become larger. Thus,

comparisons performed paired-wise in each evaluation matrix are considered consistent if the CR value is less than or equal to 10% or 0.1 (Saaty, 1980; Saaty & Vargas, 1984).

A research performed by UN-ESCAP (1989) on the metal industry stated seven levels

of complexity with regard to the technology components. Other studies had not established these seven levels. Therefore, this research has adapted from UN-ESCAP (1989) by using the

relevant information in the context of SMEs.

As many as 24 elements (starting from T1-T7 for Technoware, H1-H3 for Humanware,

I1-I7 for Infoware, and finally O1-O7 for Orgaware) have been categorised according to the

respective technology components, which are as follows: i) Technoware

T1: Operations performed manually – for example using screw drivers, hammers,

hacksaws (manual facilities)

T2: Mechanical energy is used to add strength and operational control is performed fully

by operators – for example portable drills, hand-held polisher (powered facilities)

T3: Certain operations are performed using facilities and the operator controls operations

fully – for example lathe, grinder (general purpose facilities)

T4: Facilities are used for specific activities and the operator controls operations fully –

for example weaving machines (specific purpose facilities)

T5: Facilities are used for operations with minimum control by the operator where

corrective measures are performed by the operator – for example automatic distribution machines (automated facilities)

T6: Computer control used for analysis of environmental and adaptation characteristics in

order to achieve objectives before operations are started, so operator involvement is

at the very minimum – for example Computer Numerical Control (CNC)

(computerised facilities)

T7: The entire operation is integrated through the use of computer facilities where there is

virtually no involvement by the operators – for example using robots (integrated

facilities)

ii) Humanware

H1: Workers are able to handle Technoware without requiring high level skills – low-

skilled and semi-skilled workers (operating abilities) H2: Workers having capabilities in performing operations – skilled workers and

technicians (setting-up abilities)

H3: Workers with the expertise, skills, and capabilities in repairing, modifying, and

complementing all operations – for example technicians, engineers, and experts

(repairing, reproducing, adapting, improving and innovating abilities)

iii) Infoware

I1: All facts that explain the operation of facilities – for example models, pictures,

general brochures (familiarising facts) I2: Facts that give understanding on the basic principles behind the operational modules

– for example description of tools and processes (describing facts)

I3: Facts to aid in the selection and setup of facilities – for example tool specifications,

flowcharts (specifying facts)

I4: Facts that help in using facilities effectively – for example standard operating

procedure (SOP), work safety guides (utilising facts)

I5: Facts that give deep knowledge and understanding about the operating facilities – for

example process elaboration, planning, manufacturing management specifications

(comprehending facts)

I6: Facts that help in improving planning and facility usage actions – for example output

reverse engineering output, R&D in the form of product development information and process improvement (generalising facts)

I7: State-of-the-art information about facility usage for specific aims – for example

complete information about the latest development in the improvement of facility

design, performance, and usage (assessing facts)

iv) Orgaware

O1: Small business managed using small capital and small number of workers (striving

framework)

O2: Becomes a sub-contractor to a larger business (tie-up framework)

O3: Able to produce and market own product on a large scale (venturing framework)

O4: The organisation is able to introduce new products and find new market (protecting

framework) O5: The organisation is able to defend its market by increasing total products and improve

output quality (stabilising framework)

O6: The organisation continues to find new market space (prospecting framework)

O7: Dominates the market in certain fields and becomes the exemplary to rivals (leading

framework)

Each SME research evaluates these elements according to degree of importance using a

scale as mentioned above. Element evaluation is performed to observe the important elements based on the business that is performed. Using the Saaty method, this study can find a relative

weightage value for each element as well as rank them in order of importance. The initial steps

of using the Saaty method are shown as a hierarchy system, as shown in Figure 2.

1,1 1,2 1,3 1,24

2,1 2,2 2,3 2,24

3,1 3,2 3,3 3,24

24,1 24,2 24,3 24,24

Element 1 = T1

Element 2 = T2

Element 3 = T3

Element 24 = O7

a a a a

a a a a

a a a a

a a a a

Figure 2: Hierarchical structure of this research

Information According to Levels

Figure 2 points toward two types of elements needed by SMEs Studies, which are level

1 (THIO components) and level 2 (THIO elements). However, the main focus of the study is the

elements in level 2 consisting of 24 elements. Using the Saaty approach, paired-wise

comparisons need to be performed. If comparisons are performed for each element without considering the information in level 2, then we can get a paired comparison matrix as shown

below:

T1 T2 T3 O24

ai,j = relative importance value of dimension i over j; i,j = 1,2,3,...,24

a1,1, a2,2, a3,3, ... , a24,24 = 1; (i=j)

Numerical Illustration of Paired-wise Comparison Matrix

The following are the numerical illustrations of the paired-wise comparison matrix using the research data from the 3

rd SME Study, as shown below.

SME Study 1

SME Study rth SME Study r = number of SME

Level 1

Level 2

To establish the current technology status of SMEs in Kedah

Technoware Humanware Infoware Orgaware

T1

T2

T3

T4

T5

T6

T7

H1

H2

H3

I1

I2

I3

I4

I5

I6

I7

O1

O2

O3

O4

O5

O6

O7

i. THIO component hierarchy

T H I O

1 2 1/ 2 1/ 2T

1/ 2 1 1 1/ 2HA =

1/ 1/ 2 1 1 1I

1/ 1/ 2 1/ 1/ 2 1 1O

ii. THIO element hierarchy

a. Paired-wise comparison matrix for Technoware (T)

T1 T2 T3 T4 T5 T6 T7

T

T1 1 9 / 2 9 / 9 9 / 9 9 / 2 9 /1 9 /1

T2 1/(9 / 2) 1 2 / 9 2 / 9 2 / 2 2 /1 2 /1

T3 1/(9 / 9) 1/(2 / 9) 1 9 / 9 9 / 2 9 /1 9 /1

A T4 1/(9 / 9) 1/(2 / 9) 1/(9 / 9) 1 9 / 2 9 /1 9 /1

T5 1/(9 / 2) 1/(2 / 2) 1/(9 / 2) 1/(9 / 2) 1 2 /1 2 /1

T6 1/(9 /1) 1/(2 /1) 1/(9 /1) 1/(9 /1) 1/(2 /1) 1 1/1

T7 1/(9 /1) 1

/(2 /1) 1/(9 /1) 1/(9 /1) 1/(2 /1) 1/(1/1) 1

b. Paired-wise comparison matrix for Humanware (H)

H1 H2 H3

H

H1 1 9 /1 9 /1

A H2 1/(9 /1) 1 1/1

H3 1/(9 /1) 1/(1/1) 1

c. Paired-wise comparison matrix for Infoware (I)

I1 I2 I3 I4 I5 I6 I7

I

I1 1 1/ 2 1/ 9 1/ 9 1/ 4 1/ 4 1

I2 1/(1/ 2) 1 2 / 9 2 / 9 2 / 4 2 / 4 2

I3 1/(1/ 9) 1/(2 / 9) 1 1 9 / 4 9 / 4 9

A I4 1/(1/ 9) 1/(2 / 9) 1 1 9 / 4 9 / 4 9

I5 1/(1/ 4) 1/(2 / 4) 1/(9 / 4) 1/(9 / 4) 1 1 4

I6 1/(1/ 4) 1/(2 / 4) 1/(9 / 4) 1/(9 / 4) 1 1 4

I7 1 1/ 2 1/ 9 1/ 9 1/ 4 1/ 4 1

d. Paired-wise comparison matrix for Orgaware (O)

O1 O2 O3 O4 O5 O6 O7

O

O1 1 9 / 5 1 1 9 / 3 9 / 4 9

O2 1/(9 / 5) 1 5 / 9 5 / 9 5 / 3 5 / 4 5

O3 1 1/(5 / 9) 1 1 9 / 3 9 / 4 9

A O4 1 1/(5 / 9) 1 1 9 / 3 9 / 4 9

O5 1/(9 / 3) 1/(5 / 3) 1/(9 / 3) 1/(9 / 3) 1 3/ 4 3

O6 1/(9 / 4) 1/(5 / 4) 1/(9 / 4) 1/(9 / 4) 1/(3 / 4) 1 4

O7 1/ 9 1/ 5 1/ 9 1/ 9 1/ 3 1/ 4 1

Arithmetic Mean Weight and Consistent Values

The weight calculations for each THIO component and THIO element are based on arithmetic mean. This method is appropriate when the decision criteria have the same

measurement unit (Triantaphyyllou & Sanchez, 1997). This method is performed by changing

the comparison matrix f

ija with each subject to the weightf

iw . The following shows how the

weight values are obtained for each comparison matrix.

i) Obtain totals for each column

n

1,1 1,2 1,

n ,1 ,2 ,

,1 ,2 ,

1 1 1

A1 A2 A

A1

A

Total

coloum

n

n n n n

n n n

i i i j

i i i

Function f

a a a

a a a

a a a

The jth column total – j = ,

1

n

i j

i

a

i = (1, 2, 3,..., n)

ii) Divide the matrix value in each cell with the respective column total. The result is a normalised comparison matrix.

n

1,1 ,1 1,2 ,2 1, ,

n ,1 ,1 ,2 ,2 , ,

A1 A2 A

A1 / / /

A / / /

i i n i n

n i n i n n i n

Function f

a a a a a a

a a a a a a

iii) Obtain the weight factor through means of each row (eigen value)

n

1,1 ,1 1, ,

1, ,

n ,1 ,1 , ,

, ,

A1 A Means of each row

A1 / //

A / //

n ni n i n

j i j

j i

n nn i n n i n

n j n j

j i

Function f

a a a aw a a

a a a aw a a

Weight value is , ,/

n n

i i j i j

j i

w a a

row 1, ..., ni

Using the paired comparison matrix, the weight values obtained are as follows:

3rwA (0.869,0.732,1.206,1.384)

The paired-wise comparison matrix weight value calculation is repeated according to steps i) to iii) for all SME Studies. Generally, the values are as follows:

[ , , , ]

1 7 1 3 1 7 1 7

, , , ;

,..., ; ,..., ; ,..., ; ,..., ;

kT

r T H I O

kTT H I O T T H H I I O O

r A A A A A A A A

wf w w w w r

wA w w w w w w w w r

Next, the paired-wise comparison of consistency level that is performed for each SME Study at

level 1 (THIO components), is tested using formula. Using the paired-wise comparison matrix,

the following shows the weight values and consistency multipliers for the 3rd

SMEs Study:

3rwA (0.869,0.732,1.206,1.384)

λmax = 4.187; CI = 0.062; CR = 0.069

Meanwhile, for level 2 (THIO elements), the elements of the paired-wise comparisons are consistent, because the researchers follow the concept emphasised by Saaty (1999) during the

process of comparing, which is:

When ij jk ika a a , then the paired-wise comparison matrix dimension f

ija is consistent

and the principle eigen value, λmax equals fn , that is, the number of dimensions for each

function, ( max =fn ). Otherwise, it is an interval, ( ija =1/ jia ).

Comparisons performed by r = 3 is consistent because the consistency ratio value (CR)

< 0.1.

Average Weight for each Technology Component Dimension

The listing of the technology components is performed according to the highest scores

obtained from the multiplication of the average function weight wf THIO component with the

average element THIO weight wA . Among the previous research studies that use this approach

to obtain the final weight/score for each level are by Cheng and Li (2001), Dey and Gupta

(2001), as well as Jackson (2001). The average weight for each wf and wA is obtained using

geometric mean, and the technology component score is shown by the following formula:

Technology Component Score, kT =

4 28

1 1

x i jwK wD

where Ki = (T, H, I, O)

Dj = (D1,…,D7)

Note: D refers to the dimension for each criterion, which are THIO

FINDINGS

SME Studies in Technology Component Hierarchical Analysis

Firgure 3: Decision hierarchy for all 51 SME Studies

Figure 3 illustrates that decision hierarchy for the 51 SME Studies. It was observed that the

Orgaware component is the most important component, followed by Technoware, Humanware,

and Infoware. This research supports other previous studies by Jantan, Ismail, Ramayah, and

Hikmat (2001a), who found that much of the technology used in SMEs focuses on administrative technologies. In this research, administration is one of the elements included in

the Orgaware component.

SME

Study

Ranked in Order of Importance

Technology Component THIO Component Element

1. Orgaware

2. Technoware

3. Humanware

4. Infoware

(O-T-H-I)

1.H1

2.H2

3.T1

4.T2

5.T3

20.I1

21.I7

22.O2

23.T6

24.T7

To establish current technology status of SMEs in Kedah

Technoware: 0.261

T1: 0.050

T3: 0.049

T4: 0.047

T2: 0.050

T5: 0.034

T6: 0.017

T7: 0.014

Humanware: 0.238

H1: 0.120

H2: 0.069

H3: 0.049

Infoware: 0.225

I1: 0.026

I2: 0.032

I3: 0.032

I4: 0.039

I5: 0.037

I6: 0.034

I7: 0.025

Orgaware: 0.276

O1: 0.038

O2: 0.023

O3: 0.042

O4: 0.044

O5: 0.047

O6: 0.047

O7: 0.035

For the elements of technology component, the H1 element that is the unskilled and semi-skilled

workforce is in the first position, followed by H2, which is the skilled worker like technicians. This illustrated that the SMEs own and use a workforce that is unskilled, or semi-skilled, and

skilled for handling the facility, maintenance work, and the like. Without Humanware, each

organisational path and operations cannot be performed.

DISCUSSION

From this research, the involvement of Technoware component in SME studies is

dependent on the type of business that is performed, and also the financial source that is accessible. For example, SMEs get a lot of machine assistance from SMIDEC. This process is

known as ‛hire-purchase’. There are also organisations that like to use traditional methods,

based on the products that are manufactured. For the Humanware component, some SMEs

Studies did not have technicians because they get technical assistance from external parties or from the machinery suppliers. In relation to Infoware, information or facts used are not

widespread. For example, the flowchart for generating products is rarely documented and

shown. Finally relating to the Orgaware component, the framework for many organisations is influenced by location as well as the marketing strategy adopted. Since SMEs are still at the

early stages which use small capital, more complex facilities for making their work easier are

not affordable. They are ‘forced’ to use traditional or manual methods.

The phenomenon that is revealed through this research is related to the involvement of

technological components and elements in SMEs. The involvement of technology components

can be viewed from the weightage calculation perspective which illustrates the trend of SMEs in giving attention to a technology component. This trend may be different depending on the SME

status or category where the SMEs are placed. It is hoped that the results obtained can help give

benefit to several parties. Among them are the owners or SME operators, agencies that aid SMEs like KEDA and SMIDEC (no known as SME Corp Malaysia), financial institutions that

provide assistance like SME Bank, and last but not least the academicians who can further

investigate this field of knowledge.

For the SME owners or operators, the technology status of the organisation can be

explored further. A comparison can also be made with SMEs with different status levels that

have been established. This comparison can improve the competitive levels among the SMEs where they continue to improve their productivity from time to time. The obtained technology

status of SMEs can also help the assisting organisation like KEDA and SME Corp Malaysia in

forming their strategies more effectively toward fulfilling the needs of SMEs from time to time.

CONCLUSION

This research aimed at establishing the technology component status of SMEs in Kedah. Based

on the data obtained from an analysis using the method by Saaty, which is also known as AHP,

several strong trends were observed in the use of Orgaware, followed by Technoware, Humanware, and Infoware. Therefore, it can be concluded that the organisational skills and their

manifestation in daily routines and processes are important factors that need to be addressed

critically in SMEs.

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Websites

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