Attributes Influencing B2B Customer Valuekau.diva-portal.org/smash/get/diva2:422548/FULLTEXT02.pdf · delivery, packaging, certificates, supporting service and after-sales service

Karlstad Business SchoolHandelshögskolan vid Karlstads universitet

Important attributes

influencing B2B customer value

in the EMS market

Karlstad Business SchoolHandelshögskolan vid Karlstads universitet

Alexandra Lutz

Van Nguyen



in the EMS market

Business Administration

Master Thesis

15 ECTS

Term:

Supervisor:

Karlstad Business School Handelshögskolan vid Karlstads universitet



Spring 2011

Hans Lindkvist

Abstract The thesis presents a study on important attributes which should be considered by the supplier

in buying situations in the electronic manufacturing services (EMS) market. Hence, the im-

portance level of attributes is investigated to see which attributes are more or less important

when business-to-business (B2B) customers place an order. This can be interpreted as the

relationship between the created value and the accompanying cost. For the success of this

research work, both the qualitative and quantitative methods need to be applied. The impor-

tance of nine aspects is examined including: payment term, warranty, brand, product quality,

delivery, packaging, certificates, supporting service and after-sales service. To identify which

one is significant, a classification of the twenty-three attributes covering the nine aspects is

conducted using Kano’s evaluation table. The findings through this research indicate that de-

livery, product quality and supporting service are the three most important aspects. A focus on

these aspects is supposed to help the company to get value for the customers and also bring

significant benefits for that company.

Key Words: customer value, B2B customers, electronic manufacturing services market

Acknowledgements We would like to thank Karlstad University for offering us an opportunity to be MBA stu-

dents at the Karlstad School of Business. We would like to express our sincere gratitude to

our supervisor Hans Lindkvist for his support and critical comments throughout this thesis.

His knowledgeable supervision really helped to complete this thesis.

We also thank Olle Hulteberg, Managing Director of the company EDC AB, for giving us the

chance to write our master thesis based on an empirical study. We are grateful to Niklas Niord

for his continuous guidance. His thoughtful and gracious approach helped us easily discuss

any problems with him. We would like to thank the EDC employees for their support through

the data collection of the survey and for providing us valuable information. We are grateful to

Martin Löfgren, Claes Högström and Poja Shams for interesting discussions of research me-

thodology. We would also like to acknowledge the survey respondents for their time and ef-

fort to make this thesis possible.

We would like to express gratitude to our parents Hung Nguyen and Mai Vu, Irmgard Lutz

and Manfred Lutz, our sisters Phuong Nguyen, Manuela Lutz and Irina Lutz, and especially

Viet Vu, Nhung Nguyen and Mohammed Toufiq Rizwan for their encouragement that helped

us much to accomplish this thesis.

Table of Contents vi

Table of contents List of Tables ....................................................................................................................................................... viii

List of Figures ....................................................................................................................................................... ix

1 Introduction ........................................................................................................................................... 1

1.1 Research Problem .................................................................................................... 1

1.2 Purpose of the Study ................................................................................................ 2

1.3 Research Question.................................................................................................... 2

1.4 Theoretical Background ........................................................................................... 2

1.5 Thesis Outline .......................................................................................................... 2

2 Research methodology .......................................................................................................................... 3

2.1 Qualitative and Quantitative Method ....................................................................... 3

2.2 Measurements .......................................................................................................... 4

2.3 Statistical Methods ................................................................................................... 4

2.3.1 Likert scale........................................................................................................... 5

2.3.2 Kano model .......................................................................................................... 5

2.3.3 T-test .................................................................................................................... 8

2.3.4 Spearman’s rho .................................................................................................... 9

2.4 Data collection ......................................................................................................... 9

2.4.1 Primary and secondary data ................................................................................. 9

2.4.2 Samples and resource ........................................................................................ 10

2.5 Questionnaire process ............................................................................................ 10

2.6 Reliability and Validity .......................................................................................... 12

3 Theoretical Framework ...................................................................................................................... 13

3.1 Business to Business (B2B) Market....................................................................... 13

3.1.1 Characteristics of the B2B market ..................................................................... 13

3.1.2 Problems in the B2B market .............................................................................. 14

3.2 Buying behavior in the business-to-business market ............................................. 14

3.2.1 Business Buying Situations ............................................................................... 14

3.2.2 Business Buying Process ................................................................................... 15

3.3 Customer Value Creation in the B2B market ........................................................ 16

3.3.1 Influences on buying decisions .......................................................................... 16

3.3.2 Customer Value ................................................................................................. 17

3.4 The Supply Chain................................................................................................... 18

3.4.1 Supply Chain Management ............................................................................... 19

3.4.2 Customer Value Creation in the Supply Chain.................................................. 20

4 Empirical Findings and Analysis ....................................................................................................... 21

4.1 EDC Company ....................................................................................................... 21

4.2 Data Overview ....................................................................................................... 21

4.3 Analysis of the nine main aspects .......................................................................... 22

4.4 Analysis of the Twenty-Three Attributes ............................................................... 23

4.4.1 Evaluation Table ................................................................................................ 23

4.4.2 Classification of the Attributes .......................................................................... 24

4.4.2.1 An Overview of Statistical Significant Classifications ................................. 24

4.4.2.2 Statistical Significant Classifications for the Two Customer Groups ........... 27

4.4.2.3 Relationship between Turnover and Classifications ..................................... 28

4.4.3 Better-Worse Analysis ....................................................................................... 29

4.4.3.1 Delivery ......................................................................................................... 29

4.4.3.2 Supporting Service ........................................................................................ 30

4.4.3.3 Certificates..................................................................................................... 30

4.4.3.4 After-sales Service ........................................................................................ 31

4.4.3.5 Product Quality.............................................................................................. 31

4.4.3.6 Warranty ........................................................................................................ 32

4.4.3.7 Packaging ...................................................................................................... 32

4.4.3.8 Brand ............................................................................................................. 32

4.4.3.9 Payment Term ............................................................................................... 33

5 Conclusion ........................................................................................................................................... 35

5.1 Summary of the main findings ............................................................................... 35

5.2 Recommendations for EDC ................................................................................... 36

5.3 Limitations of the Study ......................................................................................... 37

References ............................................................................................................................................................ 39

Appendix .............................................................................................................................................................. 42

List of Tables viii

List of Tables

Table 2-1 Alternative Kano evaluation table (Kano et al. 1984, Berger et al. 1993, Lee

and Newcomb 1997, Högström 2011) 8

Table 4-1 Importance ranking of the nine aspects 22

Table 4-2 Overview of the attributes’ classification 26

Table 4-3 Overview of the turnover in small- and large-scale companies 28

Table 4-4 Preferred payment time 33

Table 4-5 Correlation between turnover and preferred payment time 34

List of Figures ix

List of Figures

Figure 2-1 Five-level Kano questionnaire (Löfgren & Witell 2008) 6

Figure 2-2 The nine aspects 11

Figure 3-1 The supply chain (adapted from Lyson & Gillingham 2000) 18

Figure 4-1 Comparison of the evaluation tables 23

Figure 4-2 Better-worse diagram 29

Figure 5-1 Customer value creation in EDC’s supply chain 36

Introduction 1

1 Introduction

During the last 50 years, an increasing need for outsourcing at original equipment manufac-

turers (OEM) led to the development of the electronic manufacturing services (EMS) market.

The EMS companies are the ones which have the responsibility of designing, assembling,

producing and testing electronic components (Globalspec 2011). These components are inte-

grated or assembled with others components and mechanisms for producing products for end-

customers. A typical product for the EMS industry is printed circuit board which is utilized

for electronic equipments such as refrigerator, laser machine, computer etc. Getting an order

for an electronic product, the EMS companies are in the majority of cases not only responsi-

ble for the manufacturing but also for setting a design that fulfills the OEM’s requirements.

As a business-to business market, the customers in the electronic manufacturing services in-

dustry are also organizations that buy from other organizations. Buying process and buying

behavior is as usual as for business-to-business markets. (Datamonitor 2010, Gentry & Elms

2009).

Nowadays, being competitive is crucial for a business. This is also true for the EMS market.

Changing conditions and demands in a market require high adaptation of companies, not only

to the changes but also to customers’ needs. Thus, it is necessary to know what customers’

demands are and which products customers want to buy.

1.1 Research Problem

In the EMS market, the constant development of electronic technology results in growing

markets of electronic products and a large number of competitors. Gaining high market share,

retaining old customers and finding new customers seem to be a difficult task and a unique

way to survive in the current severe market. The role of creating value for customers is there-

fore extremely important. According to Slywotzky (1996), implementing strategies based on

value will bring success for organizations. (Khalifa 2004). Day (1990) urged “superior” cus-

tomer value creation is considered as a prerequisite to survive in a competitive market (Huber

et. al 2001). Creating customer’s value requires much effort of all sections in a company.

Bringing superior value to customers is an effective strategy to compete over a company’s

competitors. However, value creation is in accordance with the cost. An investigation in find-

ing out which important factors bring value to customers and are accompanied by cost, is an

interesting topic. According to Ghauri & Grønhaug (2005), it is hard to make an important de-

cision if we do not have deep researches on a particular aspect.

Introduction 2

1.2 Purpose of the Study

The purpose of this study is to find out the most important attributes which have influences on

buying decisions of customers. We also try to figure out attributes that can bring value for

customers.

1.3 Research Question

In order to create value for B2B customers in the EMS market, the research question is de-

signed as follows:

In the EMS market, which are the most influencing attributes that bring value for the

B2B customers but drive also the accompanying cost?

1.4 Theoretical Background

The theoretical background for the study is based on theories concerning the value creation

for customers in a business-to-business market. The understanding of B2B market is mostly

based on Kotler (2003) and Hutt and Speh (2010). The value creation for the B2B customers

refers to Kotler (2003) and Porter (1985). This is explained in the context of the supply chain,

based on Stevenson (2009), Slack et al. (2007) and Porter (1985).

1.5 Thesis Outline

The thesis is presented in five chapters. The first chapter gives a general introduction of the

thesis, research problem, thesis purpose and research questions. Research method, data collec-

tion and questionnaire procedure are introduced in the second chapter. In the next chapter,

theoretical framework is discussed to help the readers understanding basic concepts and theo-

ries connected to the study. For example, we explain the concepts of customer value creation,

B2B market, buying process and supply chain. These concepts are used as a basis for the em-

pirical research later on. The fourth chapter is reserved for presentation of the empirical find-

ings, analysis and discussions of the research outcomes. Nine aspects are explored to find

attributes which are more or less important in the B2B customers’ perspective. This chapter

also provides brief information about the EDC company. The conclusion chapter summarizes

our study and presents recommendations for EDC. Limitations and suggestions for further stu-

dies are also given in the last chapter.

Research methodology 3

2 Research methodology

The second chapter focuses on presenting an overview of the used methodology. Different

ways of data collection and the process of questionnaire are provided.

2.1 Qualitative and Quantitative Method

Selecting a method for a business research depends strongly on what should be investigated

(David 2010) and how data is collected (Ghauri & Grønhaug 2005). This selection should be

based on study objective and research problem (Jankowicz 1991). Basically, one research

method is chosen for one study. However, researcher can also combine several methods for a

single study. For example, both quantitative and qualitative methods (Ghauri & Grønhaug

2005) have been used in a single study in business and management (Bryman & Bell 2007).

This helps the researcher improve the generality of the study outcomes. Applying a mixed

method, the researchers can obtain not only statistical information in quantitative study but

also procession analysis in qualitative study (Bryman & Bell 2007). In several studies, it

seems difficult to select either quantitative or qualitative approach for research. This is very

common in the study where self-completion questionnaire is employed (Bryman & Bell

2007). The researchers feel unconfident if they only use the questionnaire for their data analy-

sis. Thus, qualitative method should be used as a semi-structure interview or observation to

get more knowledge about the research topic.

In this thesis, a combination of some research methods is employed. The qualitative method is

used throughout the data collection process. For analysis, the Kano model is used as the qua-

litative approach to assess customers’ perspective (Wassenaar et al. 2005 & Rivière et al.

2006). In addition, a likert scale to measure the degree of importance of attributes is applied

as the quantitative approach. This approach is supposed to bring more effective results for this

research. We aim at combining the advantages of both methods to bring the most effective

results of this study.

On one hand, the qualitative approach mainly emphasizes on words during data collection

(Bryman & Bell 2007) and is more descriptive (Reichardt & Cook 1979, Ghauri & Grønhaug

2005). An advantage of this method is the in-depth understanding to investigate insight of a

phenomenon. Qualitative research is regarded as a flexible and unstructured method (Ghauri

& Grønhaug 2005). However, due to the subjective and vague characteristics, this method

may result in inaccurate outcomes. In addition, the qualitative method is not transparent since


the results obtained with this method do not indicate explicitly what a researcher has accom-

plished. (Ghauri & Grønhaug 2005)

On the other hand, the quantitative approach refers to numbers (Bryman & Bell 2007), mea-

surements and statistical analysis (Ghauri & Grønhaug 2005). This method is evaluated to be

logical and focusing on facts (Reichardt and Cook 1979). The four main elements in a quan-

titative research are measurement, causality, generalization and replication. Measurement

which is a great concern in quantitative method will be discussed in the latter part. Causality

is mostly unconcerned in description. However, causality focuses mainly on explaining, ex-

ploring the reasons of a phenomenon. It also focuses on explaining what is happening. Gene-

ralization refers to the outcome of the research. When a researcher selects a sample, he/she

categorizes the sample instead of sending a survey with “whole population”. The reason is

that he/she expects the outcomes to be useful for a specific circumstance. A good point in this

method is the replication, i.e. we can avoid the bias of findings. Researchers can hardly influ-

ence the result towards their point of view or expectation. However, self-completion ques-

tionnaire and structured interview result in some inaccurate findings since we do not know

exactly the respondents’ awareness about the questions. Thus, the respondent’s behavior may

be at variance with their answers (LaPiere 1934, Bryman & Bell 2007). However, seeking the

relationship between variables may be impossible.

2.2 Measurements

Measurement is required in empirical studies. The quality of data collection is affected by

chosen measurements (Ghauri & Grønhaug 2005). Among different scales of measurement,

ordinal scale is chosen in combination with the Kano model as our major scale to seek if a

factor A is more or less important than another factor B. This refers to a small decreased re-

liability by using the t-test which is arguable because of its high robustness against unful-

filled assumptions.

Tendency measurements including mean and mode are selected for data analysis. Mean is

used to seek the average value while mode helps us to explore the most common value.

(Bryman & Bell 2007)

2.3 Statistical Methods

Besides the mentioned methods in the following chapter, additional analyses like e.g. a factor

analysis, were conducted. This aimed to find further relations between the attributes and also


to identify other aspect groups as the contemplated ones. However, probably due to the limita-

tions in the sample size, no definite results could be found. Therefore, this is not further dis-

cussed in this thesis.

2.3.1 Likert scale

Likert scale is commonly chosen for conducting the questionnaire. Selecting a number of

points in likert scale is still a controversial issue. This research applies 10 point likert scale to

improve the validity of the data collection (Brace 2008). Coelho & Esteves (2007) urged that

10 point likert scale was better than 5 point one since more available information may be pro-

vided and customers’ discrimination may be decreased. Thus, we can prevent error respond-

ing. Moreover, the customer can answer easily with larger range (Brace 2008). It is supposed

that more space should be required for more points. However, 10 point likert scale is appro-

priate for online surveys where there is no need for additional space and the professional de-

signs of online surveys make the surveys look shorter than normal.

The respondents were asked to rank the level of importance from the scale of 1 to 10, where 1

means “not at all important” and 10 is equivalent to “extremely important”. Using likert scale

can determine mean and mode. Besides, several multiple choice questions are also given in

our survey.

2.3.2 Kano model

The Kano model is mainly selected in this study. This model is appropriate to researches re-

lated to management such as quality management, employee management and service man-

agement. Product development, business planning and strategic thinking should also be ap-

plied Kano’s methodology (Witell & Löfgren 2007). The Kano model helps us to find out the

important attributes to meet the demand of customers (Xu et al. 2008). Managers can there-

fore focus on such attributes to enhance company’s business performance (Löfgren & Witell

2008). According to the five-level Kano questionnaire, each attributes comprise two ques-

tions: functional form question and dysfunctional form question. The former refers to the cus-

tomer’s response if a given feature is present whereas the latter implies the customer’s re-

sponse if a given feature is not present. (Kano et al. 1984, Berger et al. 1993, Löfgren & Wi-

tell 2008). An example of the question can be seen on Figure 2-1. Five categories for the an-

swer can be conceived as follows (Kano et al. 1984, Löfgren & Witell 2008):

1. Attractive quality (A): This attribute shows the customer’s satisfaction if it is fulfilled.

However, the customers do not feel dissatisfied if it is not fulfilled


2. One-dimensional quality (O): This attribute indicates customer’s satisfaction if it is

fulfilled. Conversely, the customers feel dissatisfied if it is not fulfilled. This element

also shows that the more value the company can bring and meet the customer’s de-

mand, the more satisfaction the customers have.

3. Must-be quality (M): This attribute is “taken for granted” if fulfilled but dissatisfac-

tion if not fulfilled. The attribute receives lots of expectation from the customers.

4. Indifferent quality (I): The customers’ answers seem to be neutral. This attribute does

not show exactly either the customers feel satisfied or dissatisfied.

5. Reverse quality (R): This explains a ‘high degree of achievement’ leading to dissatis-

faction of the customers.

The letter “Q” stands for “Questionable” in Figure 2-1. According to Kano et al.,(1984), the

customers might understand the question, however, they answered ambiguously. For example,

a customer may answer “like” in both functional and dysfunctional form of one question.

(Löfgren & Witell 2005)

Due to the fact that the Kano model can only direct to a qualitative assessment of attributes

(Wassenaart et al. 2005, Riviere et al. 2006, Xu et al. 2008), statistical analysis using SPSS

should also be applied. Likert scale is utilized to make sure getting in-depth results, i.e. there

is a combination of quantitative and qualitative methods.

Figure 2-1 Five-level Kano questionnaire (Löfgren & Witell 2008)


In this thesis, twenty three attributes are presented covering nine aspects: product quality, cer-

tificates, supporting service, packaging, delivery, warranty, after-sales service, brand and

payment. Investigating into the Kano evaluation table helps to know which answer belongs to:

‘Must-be ‘(M), ‘Attractive’ (A), ‘One-dimensional’ (O), ‘Indifferent’ (I), ‘Reverse (R) or

‘Questionable’ (Q) There are also additional measurements for the Kano model: category

strength, total strength and evaluation rule. (Kano et al. 1984, Löfgren & Witell 2005)

According to Lee and Newcomb (1997) and Löfgren and Witell (2005), category strength

(CS) is calculated by the difference between the percentage of the highest and the next-

highest category:

CS = % Highest category – %Next-highest category

Total strength (TS) is evaluated by the total percentage of the ‘Must-be’, ‘Attractive’ and

‘One-dimensional’ categories as follows:

TS =(M + A + O) ∗ 100%

M + A + O + I + Q + R

Evaluation rule is appropriate in the certain circumstance where there is little difference in

terms of percentage between the highest category and the next-highest category. The re-

searcher will look at the degree of the categories using the evaluation rule given in Matzler et

al. (1996):

M>O>A>I

In this study, better-worse diagram is also explored to get a clear picture of the importance of

the attributes and the customer’s satisfaction. (Beger et al. 1993, Löfgren & Witell 2005).

Berger et.al. (1993) indicated how to define the better axis and the worse axis by:

Better =A + O

A + O + M + I

Worse =O + M

A + O + M + I

The highest value in the “better” and “worse” axes is 1. The more value is close to 1, the more

the customer satisfied. This can be interpreted as follows. Customers think that they feel satis-

fied if the company can provide that attribute. Those attributes, which are close to 1 in both

“better” and “worse”, also indicates the importance in the customer’s decisions to order the

product ( Löfgren & Witell 2005).


Table 2-1 Alternative Kano evaluation table (Kano et al. 1984, Berger et al. 1993, Lee and

Newcomb 1997, Högström 2011)

Quality Attribute �

�

Dysfunctional

Fun

ctio

nal

1.Positive 2.Expect 3.Neutral 4.Accept 5.Dislike

1.Positive Q A(Q*) A A O

2.Expect R(Q*) Q(I***) A(I***) O(I***) M

3.Neutral R I I I M

4.Accept R I I I(Q**) M

5.Dislike R R R R Q

Notes: A = Attractive, O = One-dimensional, M = Must-be, I = Indifferent, R = Reverse, Q = Ques-

tionable. No* = Categorisation according to Högström (2011), * = Categorisation according to Lee

and Newcomb (1997), ** = Categorisation according to Berger et al.(1993), *** = Categorisation according to Kano et al. (1984)

Table 2-1 shows different evaluation table proposed by different researchers. The original

evaluation table, which is called Kano evaluation table, is suggested by Kano et al. (1984). A

few years after, some researchers changed several cells on the table in combination with dif-

ferent analyses. This change roots from the “illogical answering combination”. According to

Kano et al. (1984), Cell 1-1 and Cell 5-5 are categorized to ‘Questionable’ since customers

have positive feelings with both dysfunctional and functional questions (Högström 2011).

Based on this logic, Cell 2-2 and 4 – 4 should be categorized into ‘Questionable’ instead of

the ‘Indifferent’ classification (Berger et al. 1993, Lee and Newcomb 1997, Högström 2011).

Kano et al. (1984) has categorized Cell 2-1, Cell 3-1 and Cell 4-1 into ‘Reserve’. However in

Lee and Newcomb’s perspective (1997), Cell 2-1 is placed in ‘Questionable’ category.

Figure 2 points out an increase in the ‘Attractive’ and ‘One-dimensional’ categories but a de-

crease the in ‘Indifferent’ category in the other evaluation tables compared to the original Ka-

no evaluation table. This leads to a replacement of ‘Must-Be’-‘Attractive’ combinations by

‘Must-Be’-‘One-dimensional’ or ‘One-dimensional’-‘Attractive’ combinations (Högström 2011).

2.3.3 T-test

With the help of a t-test, statistically significant differences between the classification agree-

ments for the attributes are figured out.


A significant level of 0.05 is selected to explore the reliability of the attributes. This means

that the probability of considering a classification of an attribute as significant even if this is

not true, is 5%. With a probability of 95%, the classification does not show any mistakes. Fur-

thermore, the classification was also tested to a significance level of 0.10, which relaxes the

classification condition.

The application of the tests requires independent samples. This requirement is met because

the composition of the customer groups has been done independently. Furthermore, the ob-

servations should follow a normal distribution. For this purpose, the Kolmogorov-Smirnov

test or the Shapiro-Wilk test can be used. The Shapiro-Wilk test is usually applied for small

data sets because of its higher validity than the Kolmogorov-Smirnov test. Nevertheless, the

Kolmogorov-Smirnov test is chosen for pragmatic reasons. This is justified by the high ro-

bustness which the t-test shows against this requirement. Since the variances of the observed

values for the population are unknown, it is necessary to ensure that the variances are equal.

This is tested using the Levene's test. (Bortz 2005, Bamberg et al. 2008)

2.3.4 Spearman’s rho

Spearman’s rho is applied since it is appropriate for exploring the strength of correlation be-

tween two variables in an ordinal scale. Spearman’s rho calculates values in the range from 0

to 1, the more positive the value is and vice versa (Bryman and Bell 2007). According to re-

searchers’ experience, it seems that Spearman’s rho has lower value in comparison to Pear-

son, which may be more suitable for nominal data.

2.4 Data collection

2.4.1 Primary and secondary data

Both primary and secondary data are employed in the thesis. The primary data used for the

analysis chapter is retrieved from the interviews and the questionnaire. Such data collected

from the questionnaire is somehow appropriate when we investigate in buying behavior, cus-

tomer’s attitude and management decision for a specific product (Ghauri & Grønhaug 2005).

This can help us to answer directly the questions of interest. However, the weakness of this

method is time consuming for data collection. The secondary data is gathered from academic

books, published articles and reliable Internet resource. Some information is provided on the

EDC webpage.


2.4.2 Samples and resource

Choosing the number of samples in a survey is a debatable question in business researches,

especially in students’ studies. According to Bryman & Bell (2007), “the larger the sample

size, the greater the precision”. This means that the more samples in the survey lead to less

sampling errors. However, due to the limitations of time and cost, it is difficult for students to

obtain a large number of respondents. According to Bamberg (2008), the minimum response

rate in a small population is about 30 respondents. This rate is a sufficient population for

analysis and can bring valid results. There is a fact that the response rate currently inclines

towards decreasing, especially for studies relied on e-mail. The response rate to an e-mail

survey is approximately at 25% to 30% (Yun & Trumbo 2008). The calculation for the re-

sponse rate in a survey is suggested as follows (Bryman & Bell 2007):

Response rate =Number of usable questionares ∗ 100%

(Total sample – Unsuitable members of the samples)

In this thesis, the potential and existing customers of EDC are involved as samples for the

study. Before the questionnaire is delivered to the B2B customers by email, the list of cus-

tomers have been provided by EDC.

2.5 Questionnaire process

The first step of our process is to carry out five semi-structure interviews with the existing

customers of the EDC. Due to time consuming and distance, we conducted three phone inter-

views and two face-to-face interviews. For a semi-structured interview, interviewer gives pre-

pared questions to respondents in a flexible way. Depending on how the interview is going

on, the interviewer can arise additional questions for the respondents. Semi-structured inter-

view helps to get knowledge of the manufacturers, the market of interest and the practical

issues associated with our research. This assures that crucial factors of business practice are

not missed. Semi-structured interview may also be useful for questionnaire design and contri-

bute significantly to the success of the self-completion questionnaire (Bryman & Bell 2007).

The next step is to create the self-complete questionnaire that the customers can complete

without any guidance of interviewers with flexibility in time and space (Bryman & Bell

2007). The survey began with some general questions about the respondents and the compa-

nies, then followed by ranking the importance of the nine aspects and answering Kano ques-

tions concerning the twenty three attributes. The last part asked the respondents to rate the

importance of the attributes using a likert scale. In order to collect as many information as

Research methodology

possible and due to the fact that the first and the last parts including the importance rankings

of the aspects with respect to the attributes,

out using a ‘force answer’ option. The importance rankings can be analyzed separately.

After the draft questionnaire is accomplished, it is piloted to the EDC employees. This co

siders as an informal testing

information anyway. The questionnaire is also supposed to be piloted on the electronic trade

fair to see if the content of the questionnaire needs to be revised. Hence, we select the Sw

dish electronic trade fair in from 23 to 24 March in Göteborg for testing. Piloting the que

tionnaire is extremely crucial since we discovered a lot of mistakes. Several vague questions

have been adjusted and some explanations have been added to the specific words

respondents can understand them in the right direction.

The questionnaire was then delivered to the respondents via e

10). With support from EDC, two groups of customers could be examined: existing customers

who are currently purchasing products manufactured by EDC, and potential customers, who

may know EDC but have not placed any order of any EDC products.

consists of 227 existing customers

(50%) and 36 of the potential customers

from the existing customers

for the analysis of the importance ranking. Only 33 and 14 respons

potential customers are proper for the Kano model analysis.

sent to the customers to increase the

in contact with their customers, also made an e

naire. The online survey has

In this research, nine crucial aspects are figured out which may provide value for customers

and influence also the cost

tomers. The aspects are further divided in 23 attributes (Appendix


of the aspects with respect to the attributes, the online questionnaire has been designed wit


After the draft questionnaire is accomplished, it is piloted to the EDC employees. This co

informal testing (Bryman & Bell 2007) and such kind of test provide us useful


fair to see if the content of the questionnaire needs to be revised. Hence, we select the Sw

tronic trade fair in from 23 to 24 March in Göteborg for testing. Piloting the que


have been adjusted and some explanations have been added to the specific words

nd them in the right direction.

The questionnaire was then delivered to the respondents via e-mail (Appendix

With support from EDC, two groups of customers could be examined: existing customers

are currently purchasing products manufactured by EDC, and potential customers, who

may know EDC but have not placed any order of any EDC products. The used customer panel

consists of 227 existing customers and 98 potential customers. 112 of the existing

of the potential customers (37%) opened the online survey

from the existing customers and15 observations from the potential customers were utilizable

for the analysis of the importance ranking. Only 33 and 14 responses from the existing and

are proper for the Kano model analysis. Several reminder e

sent to the customers to increase the reliability of the research. The EDC employees who were

in contact with their customers, also made an effort to request them completing the questio

naire. The online survey has been performed for three weeks.


(see figure2-2). Thus, these affect the buying

rther divided in 23 attributes (Appendix A1).

Figure 2-2 The nine aspects

11


the online questionnaire has been designed with-


After the draft questionnaire is accomplished, it is piloted to the EDC employees. This con-

2007) and such kind of test provide us useful


fair to see if the content of the questionnaire needs to be revised. Hence, we select the Swe-

tronic trade fair in from 23 to 24 March in Göteborg for testing. Piloting the ques-


have been adjusted and some explanations have been added to the specific words so that the

(Appendix A5-1 to A5-

With support from EDC, two groups of customers could be examined: existing customers

are currently purchasing products manufactured by EDC, and potential customers, who

The used customer panel

of the existing customers

opened the online survey. 50 observations

from the potential customers were utilizable

es from the existing and

Several reminder e-mails were

The EDC employees who were

ffort to request them completing the question-


. Thus, these affect the buying behavior of B2B cus-


2.6 Reliability and Validity

The most crucial characteristics in the quantitative method are reliability and validity. The

former refers to the stability of measurements and the exact of indicators. Exploring the inter-

link between variables is regularly employed in business research since errors commonly ap-

pear more than usual and this affects the result analysis. The latter pays attention on whether

the indicators reflect the issues of interest or not. (Ghauri & Grønhaug 2005)

The internal validity deals with the concern if the used measurements in a study and the find-

ings are reliable. The external validity refers to if the findings of a study are also valid for the

whole population. This is influenced by the way of choosing a representative sample. (Bry-

man & Bell 2007) Including existing and potential customers in the sample aims to assure the

representativeness of the sample. Lynch (1999) states, external validity can be explained

through the degree of which the findings of a study represent the theoretical background.

Assuring the validity of a research is extremely essential since the research outcome can then

be used (Ghauri & Grønhaug 2005). To gain more validity of the study, multiple indicators

are mostly used instead of single indications in the questionnaire. Using such measurement

can decrease the number of random errors. In addition, this can be assured the fundamental

aspects are understandable. If the customers misunderstood an indicator, there are still others

to explain and make the aspects more explicit to understand. Using a single indicator seems to

be too general and only investigates in one aspect. However, a single indicator is somewhat

employed in the questionnaire where a single question is sufficient to acquire the essential

data. (Bryman & Bell 2007). Several efforts were undertaken to ensure the validity and relia-

bility of the study. Throughout the data collection and creation of the questionnaire, these

were e.g. the conducted interviews and the questionnaire testing.

Theoretical Framework 13

3 Theoretical Framework

This chapter is a discussion of theories. An investigation into B2B market, buying behavior of

B2B customers is mentioned. Value creation for B2B customers and supply chain are also

presented in this chapter.

3.1 Business to Business (B2B) Market

The B2B market covers all commercial business interactions that take place between business

organizations. The business-to-business customers are organizations that demand products

and services for their own business from other organizations. These are businesses, institu-

tions and the government (Hutt & Speh 2010). Due to the fact that at least one organization is

needed to produce products or provide services to end-customers, the business-to-business

market shows high total revenue. (Kotler 2003)

3.1.1 Characteristics of the B2B market

B2B markets differ from business-to-customer (B2C) markets in several terms e.g. advertis-

ing and buying processes. Kotler (2003) mentioned the following typical characteristics:

A company in the B2B market has usually fewer buyers. This means that there are less B2B

customers than those in the business-to-customer market. B2B customers buy relatively large

amount which results in a small number of large buyers generating the main part of the pur-

chases. Furthermore, a close supplier-customer relationship is to contemplate. This is shown

by a high level of cooperation between the involved companies. Customized solutions are

usual and the supplier becomes more and more integrated.. Due to the connections of the B2B

market demand with the B2C market demand, the marketers may not only focus on the de-

rived demand but also have to consider the development in the end-customer market. In addi-

tion, this is an inelastic demand, especially in a short-term consideration not strongly influ-

enced by price changes. However, it is a fluctuating demand which results in an acceleration

effect since a change in the consumer market can have a stronger effect on the business mar-

ket. Due to a more complex buying process, a professional purchasing is to state involving

special tools.

As part of the purchasing, many people are involved and several buying influences that the

supplier should be aware of, affect the decisions. Due to this complex process and the in-

volvement of many people, multiple sales calls are needed to acquire new business-to-


business customers. A direct purchasing is often to contemplate. This reduces the risk of mi-

sunderstandings which could lead to defects and later recalls. The B2B market shows also

reciprocity in the business relations. Thus, business buyers sell also their products to their

suppliers. Another characteristic of the B2B market is the leasing of equipment that requires

much budget and place.

3.1.2 Problems in the B2B market

Regarding the specific characteristics of a B2B market, different problems can occur. For a

company in the global market, the internet is not only a chance but also a challenge. Due to

the increase in the importance of internet, it becomes necessary for the supplier to have an

attractive online presence and “get listed in the major online catalogs or services, develop a

strong advertising and promotion program, and build a good reputation in the marketplace”

(Kotler 2003, p.230).

The close supplier-customer relationship in the B2B market leads often to customized solu-

tions (Kotler 2003) that may be valid for only a single buyer. The higher the customization of

the product is, the higher the risk of creating dependence on the business buyer and of wea-

kening the supplier’s negotiation power in this relation is. Suppliers are sometimes expected

to change their procedures (Kotler 2003). If the requested adaptation to the customer happens

in an extensive way, it could be aggravated to establish new relationships with other customers.

3.2 Buying behavior in the business-to-business market

“Organizational buying behavior is […] defined as the decision-making process by which

formal organizations establish the need for purchased products and services, and identify,

evaluate and choose among alternative brands and suppliers” (Webster & Wind 1972, p. 2).

3.2.1 Business Buying Situations

Depending on the kind of order, the decision-making process varies in complexity, requires

information and time. Kotler (2003) differentiates three buying situations:

• Straight rebuy: Products are ordered from a known supplier. To get this order, the

supplier has to ensure the required level of quality of the purchased products.

• Modified rebuy: There are small changes concerning product specification or con-

tract terms. Negotiation is required. This may be a situation for new suppliers to get


the order, especially when the former suppliers‘ quality do not meet the customers’

demands.

• New task: New order is placed for the first time. This situation requires the most in-

formation and the most decisions depending on the risk and the cost of the order.

The decision time, the required information and the complexity of the buying process are low

in a straight rebuy situation and high in a new task situation.

3.2.2 Business Buying Process

The new task buying process in a business-to-business market can be separated into several

stages: awareness, evaluation, trial and adoption (Ozanne & Churchill 1971). In other buying

situations, the buying process will be shorter than in a new task buying situation.

Robinson et al. (1967) described this process in eight stages and they are so-called buygrid

framework:

Problem Recognition

1. General Description of Need

2. Product Specifications

3. Supplier Search

4. Acquisition and Analysis of Proposals

5. Supplier Selection

6. Selection of Order Routine

7. Performance Review

Decisions are taken in each stage. At first, the problem needs to be recognized. This means

that a specific product or a service is needed for a solution e.g. fill a lack of a product needed

for the own manufacturing or find a substitute product for a too expensive actually used one.

On the second and third stage, it is to define what is needed. This includes general product or

service characteristics and quantity. Furthermore, the technical details are determined. De-

pending on the buying situation, the needed time and amount of involved people varies on this

stage. The next step is to search for possible suppliers and collect information. Even if rec-

ommendations from other business customers are possible, the participation in trade shows is

very important and should be consider.


Furthermore, the internet plays a big role on this stage. Direct extranet is the connection be-

tween supplier and customer, buying alliances and company buying sites where orders are

requested and placed directly. During the fifth stage, qualified suppliers are required to make

detailed quotations according to the order request. These are evaluated and it is also common

to lead the suppliers hold formal presentations for setting up also a personal contact. The deci-

sion about the supplier is taken in step six. In order to choose the most appropriate supplier,

an evaluation is conducted. For this, the buyer determines which attributes are preferable for

the supplier in combination with their relative importance. Thus, the supplier is assessed

based on the value that this supplier would bring to the B2B customer. Ranking the supplier

values displays the most attractive suppliers. After the supplier selection, the order specifica-

tions e.g. quantity, delivery and service terms, are to negotiate and determine. The last stage

contains a performance control on a regular basis which functions as decision basis about on-

going relationship with this supplier. Therefore, the buyer could evaluate the supplier consi-

dering specific criteria, calculate the cost resulting out of a supplier’s poor quality level or

evaluate the supplier based on the end-customers’ satisfaction. (Kotler 2003, Hutt & Speh 2010)

3.3 Customer Value Creation in the B2B market

In every business, making profit depends on customer’s buying decision. Thus, understanding

what influences the buying process is as necessary as understanding what customers want.

This is valid for both business-to-customer markets and business-to-business markets.

3.3.1 Influences on buying decisions

Based on the model of organizational buying behavior by Webster and Wind (1972), the buy-

ing behavior can be understood as a multilevel approach influenced by environmental (e.g.

social responsibility concerns, demand), organizational (e.g. internal policies, organizational

structure), interpersonal (e.g. negotiation abilities, social skills) and individual factors (e.g. job

position, age, interests, risk awareness).

Kotler (2003, p. 219) states that especially in a new task situation, the business buyer has to

decide about “product specifications, price limits, delivery terms and times, service terms,

payment terms, order quantities, acceptable suppliers, […] the selected supplier”, warranty,

maintenance, repair terms etc. Therefore, the degree to which the business buyer perceives

these attributes as fulfilled, is a major influence. However, Minahan () found out through a

study that price is a crucial influencing factor.


3.3.2 Customer Value

As part of the sixth stage of the buygrid framework, B2B customers assess the supplier value.

The supplier value depends on attributes which are relevant for the buyer and would bring

value. The selection and the importance rating of the attributes for the evaluation depend also

on the buying situation (Lehmann & O’Shaughnessy 1974).

Thus, it is assessed which supplier provides the highest value to the customer; that is, the

highest customer value,

In order to be the selected supplier, suppliers aim to offer products and services that provide

high customer value. For this, it is essential to figure out what is important for the customers

and which attributes the product or service should provide.

Based on a study by Anderson et al. (1993), an overview of the different customer value as-

sessment methods is given in the following.

1. Internal engineering assessment: Based on a internal laboratory tests, the product

performance is compared with the one of the closest competitor’s product.

2. Field value-in-use assessment: Customers are asked to assess the value of the dis-

played different product attributes for a new product and a competitor’s product.

3. Focus-group value assessment: The values of potential products with different de-

signed attributes are assessed in a focus group.

4. Direct survey questions: Regarding one market offering, customers assess value to

different changed attributes

5. Conjoint analysis: Customers state their preferences between products with different

designed attributes.

6. Benchmarks: Regarding a benchmark and a new market offering, customers are

asked to price for the new market offering.

7. Compositional approach: Regarding a product with several attributes, customers are

asked to assess value to the different possible design alternatives of the attributes.

8. Importance ratings: The different attributes of a product shall be rated according to

their importance to the customer.

Which method is used depends on factors as e.g. the market or the available budget.

Theoretical Framework

3.4 The Supply Chain

Including a relationship perspective production process of products or services, the supply

chain is an adequate approach. Stevenson (2009, p. 511) states that “a supply chain is the s

quence of organizations - their facilities, fu

ducing and delivering a product or service”.

centers, retail outlets or offices, activities and functions e.g. to forecasting and purchasing.

(Stevenson 2009) The complexity and amount of involved organizations varies depending on

the product or service.

In a general perspective, supply chains include suppliers, manufacturers, distributors, further

producers, retailers and the consumers (Nagurney 2006). A

the figure 3-1. The presented supply chain can be understood as a the sequence of single o

ganizations.

Figure 3-1 The supply chain (adapted from Lyson & Gillingham 2000)

In a more modern understanding, one

chain. This is displayed through the responsibility areas. After getting the material provided

by the supplier, the manufacturer would be responsible for procurement, manufacturing, st

rage and distribution. The customer, e.g. a further manufacturer, would receive the produced

output and sell this via a retailer to the end

customer could also cover this task. The overlapping responsibility areas demonstrat

task division between the organizations in the supply chain are not fixed and depend on the

negotiated contracts.

Understanding the creation of a product or service as one on

needed businesses from the raw materi

assigned to at least one supply chain. Through the supply chain, the connection between the

participating organizations is done. Within the supply chain, three different flows can be ide

tified: product / service flow which shows the creation and production of the product or se

vice from the raw material to the end

manager can make decisions based on facts, and the cash flow which includes the monetary

The Supply Chain


chain is an adequate approach. Stevenson (2009, p. 511) states that “a supply chain is the s

their facilities, functions, and activities - that are involved in pr

ducing and delivering a product or service”. Facilities refer to e.g. warehouses, distribution


9) The complexity and amount of involved organizations varies depending on


producers, retailers and the consumers (Nagurney 2006). A basic supply chain is presented in

1. The presented supply chain can be understood as a the sequence of single o

The supply chain (adapted from Lyson & Gillingham 2000)

In a more modern understanding, one organization would overtake more tasks in the supply


by the supplier, the manufacturer would be responsible for procurement, manufacturing, st

ion. The customer, e.g. a further manufacturer, would receive the produced

output and sell this via a retailer to the end-customer. A retailer is not always needed and the

customer could also cover this task. The overlapping responsibility areas demonstrat


Understanding the creation of a product or service as one on-going process and displaying all

needed businesses from the raw material to the end customer-product, every company can be


participating organizations is done. Within the supply chain, three different flows can be ide

/ service flow which shows the creation and production of the product or se

vice from the raw material to the end-customer product, the information flow through which


18


chain is an adequate approach. Stevenson (2009, p. 511) states that “a supply chain is the se-

that are involved in pro-

Facilities refer to e.g. warehouses, distribution


9) The complexity and amount of involved organizations varies depending on


basic supply chain is presented in

1. The presented supply chain can be understood as a the sequence of single or-

The supply chain (adapted from Lyson & Gillingham 2000)

organization would overtake more tasks in the supply


by the supplier, the manufacturer would be responsible for procurement, manufacturing, sto-

ion. The customer, e.g. a further manufacturer, would receive the produced

customer. A retailer is not always needed and the

customer could also cover this task. The overlapping responsibility areas demonstrate that the


going process and displaying all

product, every company can be


participating organizations is done. Within the supply chain, three different flows can be iden-

/ service flow which shows the creation and production of the product or ser-

customer product, the information flow through which



value for activities, services or goods in the two other flows. The financial flow can be seen as

a counterpart to the information and product/service flow. (Lyson & Gillingham 2000)

3.4.1 Supply Chain Management

Stevenson (2009, p. 512) defines Supply chain management as “the strategic coordination of

business functions within a business organization and throughout its supply chain for the pur-

pose of integrating supply and demand management”. Slack et al. (2007, p.402) explain

supply chain management as “a holistic approach to managing across company boundaries”

while these companies are “related to each other through upstream and downstream linkages”.

Purposes of supply chain management are to obtain an efficient and effective management of

supply and demand; sourcing and procurement of materials and services, transformation ac-

tivities and logistics are the major tasks (Stevenson 2003). With the aim of fulfilling custom-

ers’ requirements by providing adequate products with a reasonable price, Slack et al. (2007)

mention five operations performance objectives: quality, speed, dependability, flexibility and

cost. Quality depends significantly son the quality that was performed on every step of a

supply chain. Speed refers to short lead times and fast delivery which can be achieved by, e.g

holding high stocks. Speed can also be understood as the consuming time to manufacture a

product or provide service. It also means the time required in a supply chain. Dependability

considers the interlink between the organizations. is interpreted as an interlink between organ-

izations. On-time delivery and delivery of the right ordered amount are to reach. Flexibility

covers the ability to handle changes and unpredicted happenings from both customer and sup-

plier sides. Cost is mainly to contemplate as the transaction cost that includes the cost for pro-

duction of the product or service. Few suppliers facilitate the supply chain and have an impact

on cost reduction.

The traditional supply chain was not interlinked and the output was not always adapted to the

customers’ needs. The supply chain management creates an interlink between the single parts

of the chain and aims to reach a smooth process.

Further trends in supply chain management today are to recognize (Stevenson 2003):

Reevaluation of outsourcing Firstly, a reason for outsourcing was a cost reduction based on

lower labor cost. This was especially valid for globally performing companies. The reevalua-

tion leads to a consideration of other reductions such as a decrease in costs for transportation,

inventory, stock, port handling and duty by also outsourcing these responsibilities. However,

the outsourcing can prolong the lead times and diminish the flexibility.


Inventory management Companies focus more on recording, controlling and planning.

Processes are designed smoothly with the goal of having few breaks in the flows.

Lean supply chains Stock times and waiting times are considered as profit loss due to not used

capacity and cost for the needed facilities. Concepts such as Lean-production and just-in-time

are of high importance. Involving the suppliers closer in the processes and ordering from few

certified suppliers ameliorates the quality of the whole supply chain.

Sustainability An increase in demand of a raised environmental and sustainable attitude is not

only to state in business-to-customer markets but also in business-to-business markets.

3.4.2 Customer Value Creation in the Supply Chain

The delivered product is bought to fulfill a need of the buyer. Therefore, the buyer seeks sup-

pliers to acquire the product that is most likely to satisfy on a high level. As mentioned earli-

er, the buyer tries to get the product that brings them the biggest value. With this knowledge,

the supply chain can also be understood as several value chains; that is, value is added

through the processes. In the supply chain the single value chains are interlinked from one

supplier to the next until the consumer. (Stevenson 2009, Porter 1985) Stannock and Jones

(1996) refer to value chains as a value adding process on a linear path from raw material to

end-customer product. After-service is also included.

Every activity, facility and function adds value to the product or service (Kotler 2003). Con-

templating the output that offers one supplier within the supply chain, additional value can be

created by increasing the quality of the offered services and products, by decreasing the cost

for the same level of quality or by overtaking additional activities, functions or the responsi-

bilities for facilities to an appropriate price. Thus, Porter (1985) names cost leadership as one

way to gain competitive advantage. The second way is differentiation which is related to a

higher provided value to the customer.

The actual trends in the supply chain management open new possibilities for getting a com-

petitive advantage against competitors through additionally added customer value. Regarding

the reevaluation of outsourcing, suppliers can offer to overtake more parts of the supply

chain, e.g. distribution and storage of the output. Good inventory management in combination

with established lean supply chains can affect the lead time, and delivery time in a positive

way. A focus on sustainability efforts may result in stronger existing sup-customer relation-

ships and even attract new customer. Furthermore a high level of fulfillment of the objectives

of supply chain management could have a positive effect on the supplier’s attractiveness for

the B2B customer.

Empirical Findings and Analysis 21

4 Empirical Findings and Analysis

A brief introduction about EDC company is provided. In the following, the nine aspects and

twenty-three attributes are examined to find out which ones are more important and which

ones are less important from the point of view of the B2B customers of EDC. This chapter

combines the empirical part, analysis and discussion of the study. The methodologies men-

tioned in the second chapter are here applied. The data collected through the survey “Impor-

tant attributes influencing B2B customer value in the EMS market”, are analyzed. A critical

discussion is also given in this chapter.

4.1 EDC Company

Established in 1983, Elektronik Data Cad (EDC) started the business as an unemployment

project with only five staffs. Quite soon electronics became the dominant part. The EDC

group today consists of three companies EDC in Munkfors and GEME in Tallinn both with

complete full scale volume production facilities and Fabec in Gothenburg with sales and mar-

keting function and a mainly small scale service, repair, prototype production and smaller

volume production. EDC is striving to become as one of the five EMS companies gaining the

highest profit margin in Sweden. Last year, the EDC-group had a turnover of 150 MSEK .

EDC is currently manufacturing electronic and electromechanic products, for example, com-

plete box build products, main boards, printed circuit board, and so on. EDC delivers compo-

nents to B2B customers all over the Nordic countries. Examples of customers of EDC are

Thoreb, Electrolux, Rolls-Royce, Megger, etc… The main objectives of the company are to

provide the customers not only the high quality components but also the best solutions to re-

duce cost, focus on competence and core business. The company aims at gaining a stable

position in the market and a sustainable long-term development.

EDC aims to have best practice in lean production, which helps EDC to be cost effective.

Moreover, EDC is constantly seeking opportunities to provide a wide range of products and

added value services. This implies that the company facilitates to take account of more steps in the

supply chain, e.g. the products for the end-customers (not only PCBs) and the logistic services.

4.2 Data Overview

As mentioned in the chapter questionnaire process, the survey “Important attributes influen-

cing B2B customer value in the EMS market” was delivered to 325 customers concerning the


electronic manufacturing services market. For the data analysis, the collected data has firstly

been examined. The validity, responsibility and usability are briefly evaluated. Several cus-

tomers from both groups had not answered the questionnaire completely, skipped some ques-

tions or not answered an important part in the Kano model analysis. Furthermore, some cus-

tomers have shown their disinterest in completing the survey due to e.g. a lack of time or the

use of the English language. This has resulted in a decrease in the utilizable data of the exist-

ing and potential customers to 50 and15 observations, respectively, for the analysis of the

importance ranking. Only 33 and 14 responses from the existing and potential customers are

proper for the Kano model analysis.

4.3 Analysis of the nine main aspects

To get a general overview of the importance of the different aspects, the customers have been

asked to rank nine aspects according to the importance to them. Calculated by the mean value,

table 4-1 shows the importance ranking for all customers and for the two customer groups.

The data indicates that the ranking for all customers and for the existing customers is identic-

al. For the potential customers, the order is almost the same. However, the aspect ‘brand’

moves from the position 9 to 5. This could be related to the fact that the reputation of a com-

pany is a crucial factor for the potential customers when choosing a new electronic manufac-

turing service company. The potential customers have no self-experienced information about

the product quality, reliability and other important factors of the new supplier. In contrast,

54.5% of the existing customers consider ‘brand’ as the least important. This result is proba-

bly out of the fact that the existing customers group is aware of both the supplier and the

product. ‘Product quality’ is always the most important aspect as more than 84% of the exist-

ing customers and potential customers have selected. ‘Delivery’ is the second concern of the

existing customers and potential customers with 66.7% and 71.4% chosen, respectively.

Table 4-1 Importance ranking of the nine aspects

Ranking All customers

Existing customers

Potential customers

1 85.1 % Product quality 84.8 % Product quality 85.7 % 2 68.1 % Delivery 66.7 % Delivery 71.4 % 3 31.9 % Supporting services 30.3 % Supporting services 35.7 % 4 19.1 % Certificates 21.2 % Certificates 21.4 % 5 27.7 % Warranty 27.3 % Brand 21.4 % 6 27.7 % Payment 27.3 % Warranty 28.6 % 7 29.8 % Packaging 24.2 % Payment 28.6 % 8 29.8 % After-sales services 27.3 % Packaging 42.9 % 9 44.7 % Brand 54.5 % After-sales services 42.9 %


Due to the low response rate and the relatively high number of aspects to rank, the middle

positions may show not reliable findings. This conclusion can also be shown by the data it-

self. Comparing the mode of the different aspects leads to an ambiguous order. Thus, only the

ranking positions 1, 2 and 9 are to contemplate.

4.4 Analysis of the Twenty-Three Attributes

The second part of the analysis covers the classification of the twenty-three attributes which

are integrated into the Kano model. Since the number of responses of the potential customers

is only about half of the existing customers, all samples are taken into account. In case of not

explicit findings, two customer groups are analyzed separately.

4.4.1 Evaluation Table

In order to get best results, four different evaluation tables as shown in table 2-1, are used for

the classification of the attributes. To compare the different evaluation tables, the mean for

each evaluation specific category is calculated; that is, the average of the self-stated impor-

tance values of all attributes. The stated importance value of one attribute is calculated by

counting the amount of respondents who categorized this attribute into the contemplated cate-

gory, and by using the average self-stated importance of the attribute via summing up the res-

pondent’s according self-stated importance. This was conducted according to the approach

presented by Högström (2011).

Figure 4-1 Comparison of the evaluation tables

0

1

2

3

4

5

6

7

8

9

10

M O A I R Q

according to

Högström (2011)

according to

Lee & Newcomb (1997)

according to

Berger et al. (1993)

according to

Kano et al. (1984)


Even if there are no big differences in the total stated importance for the different categories,

it can be stated that compared to the three other tables the amount of ‘Indifferent’ attributes is

higher when using the evaluation table according to Kano et al. (1984) (see Appendix A2).

Compared to Kano et al. (1984) table, the three alternative evaluations lower the total stated

importance of the categories ‘Attractive’, One-dimensional’ and ‘Indifferent’ which results in

an aligned outcome with the evaluation rule M > O > A > I (Högström 20111). This leads to

the decision that Kano et al.’s (1984) table is not the best for this analysis. Berger et al.’s

(1993) table is also not applied because of an increased total stated importance of the category

‘Questionable’ which is also not in line with the mentioned evaluation rule. Regarding the

total stated importance, the results of the evaluation tables of Högström (2011) and Lee and

Newcomb (1997) differ only for the category ‘Attractive’. Thus, Högström’s (2011) table is

selected for this data analysis due to the higher total stated importance in one category.

4.4.2 Classification of the Attributes

The findings of our research are summarized in table 4-2 (see also Appendix A3-1 and A3-2

for the customer groups). In the first classification, the manual categorization using the res-

ponses of the Kano questions and the chosen evaluation table shows eleven ‘Indifferent’, sev-

en ‘One-dimensional’ attributes, and one combination of ‘One-dimensional’ and ‘Attractive’.

To assess the reliability of these outcomes, a t-test on an α-level of 5% is conducted. The clas-

sification of 8 out of 23 attributes is significant. To increase the amount of significant classi-

fied attributes, a test on an α-level of 10% is carried out. Thus, four additional attributes can

be categorized significantly. Examining the total strength and the category strength supports

the classification in most cases. However, due to the small amount of response, questionable

answers are considered critically. This may be interpreted by slightly reducing the reliability

of the concerned attributes. In total, only nine single respondents have categorized attributes

as ‘Questionable’ and these answers are distributed over several attributes. This shows that

the respondents mostly understood the questions and the “Questionable” could also result out

of a mistake.

4.4.2.1 An Overview of Statistical Significant Classifications

Regarding the significant classifications, only two attributes are categorized as ‘One-

dimensional’: ‘management certificates’ and ‘flexibility in changing delivery time’. This

means that the customers attach importance to these and the company should provide these

attributes to fulfill the customers’ expectations. Otherwise, a lack of these attributes results in

dissatisfaction of the customers. ‘Management certificates’ seem obviously essential in busi-


ness companies, especially in the EMS market. ‘Management certificates’ such as ISO 14000:

2008, ISO 9001: 2008 may help the companies to govern more efficiently and operate more

professionally. For this reason, there is no surprise if the customers feel satisfied when this

attribute is fulfilled. In case where the companies cannot give this attribute, the customers do

not feel dissatisfied. At the stated importance of 7.21, the customers may tend to consider this

attribute quite important. The result of ‘flexibility delivery time’ attribute reflects that the cus-

tomers somehow desire to have the possibility of changing the delivery time. This may ex-

plain that the customers still have end-products available in the warehouse. Thus, they are

going to lessen the productivity and expect to delay the delivery time. Alternatively, the in-

creasing demand of the end customers leads to a lack of finished products in the warehouse.

In this case, a sooner delivery is expected. The stated importance at 7.93 proves the high im-

portance and the necessity of this attribute. This may also indicate that the customers would

be willing to pay at a higher price if EDC can provide this attribute. As classified in an ‘At-

tractive’ category, the ‘functionality recommendation’ will create additional values to the cus-

tomer but a lack of it will not cause a negative impact on the customers’ perception. This can

be interpreted that the customers may accept a higher price for the products if the supplier can

give some comments on e. g. how the PCBs should be. The recommendation can also be a

changing in position of the components for more effective functionality of the product. How-

ever, stated importance of 6.77 shows that the customers may not think this attribute is ex-

tremely important.

Nine attributes are significantly categorized as ‘Indifferent’: ‘upgradability’, ‘safety certifi-

cates’, ‘shipped in pallets’, ‘more than average fragile protection’, ‘more than 12 months war-

ranty’, ‘repair service’, ‘spare parts handling’, ‘well-known brand’ and ‘discount if payment

partially in advance’. This can be understood as follows. The customers look at these

attributes in a neutral perspective while evaluating their importance, considering the created

value and the accompanying cost. However, these attributes are not unimportant as the aver-

age stated importance of 5.73 indicates. A deeper analysis is conducted in a combination with

the better-worse diagram later on.

The remaining eleven attributes cannot be assigned significantly to one specific category.

These attributes are categorized into the combinations of ‘Must-be’, ‘One-dimensional’, or

’Indifferent’. The reason for this may be that different customer groups are consisted in the

contemplated customer panel.


Table 4-2 Overview of the attributes’ classification


The classification of attributes into one category or combination may not be absolute. There

can always be a change over the time and this is even expected. ‘Indifferent’ category may

gain importance and merge into the ‘Attractive’, then into the ‘One-dimensional’ and finally

into the ‘Must-be’ area (Kano 2001). Especially a description as combination could indicate a

change in the future. In the electronic manufacturing service market which is known as a rela-

tively young industry, the customers’ requirements may not be clearly defined and the devel-

opment is going on.

4.4.2.2 Statistical Significant Classifications for the Two Customer Groups

Conducting the classification according to Högström’s (2011) evaluation table for a single

customer group brings significant outcomes for three additional attributes.

The attribute ‘possibility of manufacturing more than the mounted PCBs’ is classified as a

combination of ‘Attractive’ and ‘Indifferent’ for all customers. At an α-level of 5%, the diffe-

rentiated analysis shows a classification as ‘Attractive’ for the existing customers and as ‘In-

different’ for the potential customers. Existing customers seem to be interested in outsourcing

to the supply chain of EDC. This means that these customers not only want to require EDC

manufacturing needed products but also cover e.g. some logistic tasks or services relating to

the end-users. The ‘potential customers’ seem to be neutral about this attribute. As a ‘potential

customer’, the lack of own experience with EDC and the fact that a new order is usually quite

explicitly defined, may have an impact on these findings. Furthermore, a demand for manu-

facturing more than the mounted PCBs may appear later on when a customer-supplier relation

is established.

Two further attributes can be reliably categorized as ‘One-dimensional’, even if not for both

customer groups: ‘Quality Certificates’ for the ‘existing customers’ and ‘Discount for large

order quantity’ for the ‘potential customers’ are at significant levels of 5% and 10%, respec-

tively. Regarding the discount attribute, ‘potential customers’ seems satisfied if the company

offers a discount. Otherwise, they feel unsatisfied. This is also indicated by the stated impor-

tance of 7.07. Even if the ‘discount for large order quantity’ can not be significantly classified

for the existing customers, the combination of ‘Must-Be’ and ‘One-dimensional’ intends that

a missing of this attribute will lead to dissatisfied existing customers. The ‘existing custom-

ers’ set relatively high value on the ‘Quality Certificates’ with a stated importance of 7.55. A

lack of this attribute could also be interpreted as a decrease in the quality level of the prod-

ucts. Therefore a categorization of ‘One-dimensional’ seems obvious.


4.4.2.3 Relationship between Turnover and Classifications

In order to see if there is a difference between small-scale and large scale companies, a ques-

tion of the range of turnover has been delivered. Small-scale companies are defined by those

with the turnover of lower than 100 million SEK and a large scale companies are determined

by those with the turnover of over 100million SEK. A correlation between the turnover and

the importance of twenty three attributes are investigated. The table 4-3 illustrates that nearly

half of the respondents (44.7%) taking part in the questionnaire are currently working in

small-scale companies (21 respondents). The remaining 25 respondents are from large-scale

companies (53.2%). There was one missing answer for the turnover question.

Overall, both small and large scale companies have the same perspectives in the importance

of these studied attributes. However, concerning ‘shipping the products in pallets instead of

boxes’ (F11), ‘Indifferent’ and ‘Attractive’ categories have been classified in small-scale

companies and large-scale companies, respectively (see Appendix A4). This is explainable

since the small-turnover companies may not have excessive money; these companies only aim

to buy the products with standard packaging.

Table 4-3 Overview of the turnover in small and large-scale companies

What was the turnover during the last fiscal year? Frequency Percent Valid Percent Cumulative

Percent

Valid up to 100 MSEK 21 44.7 45.7 45.7

over 100 MSEK 25 53.2 54.3 100.0

Total 46 97.9 100.0

Missing System 1 2.1

Total 47 100.0

In their viewpoint, they seem not concern and tend to pay at higher price to get this value. In

contrast, the large-turnover companies are more interested in this attribute. They feel satisfied

if this attribute is present but they still feel fine if this one is not. Examining the attribute

‘more than 12 months warranty’ (F17), it is classified as ‘Indifferent’ by the small-scale com-

panies but as a combination of ‘Indifferent’ and ‘Reverse’ by the large-scale companies. One

part of the companies may consider this attribute always as neutral and a part of the large-

scale companies considers this attribute even as dissatisfaction if provided. This may be ex-

plained by the fact that it was asked about the created value related to the accompanying

cost. Large-scale companies have more negotiation power and can request to get an ex-


tended warranty without paying a higher price for the ordered product. Thus, this attribute is

classified as ‘Reverse’.

4.4.3 Better-Worse Analysis

To visualize the classification of the 23 attributes and the distribution of them, a further analy-

sis is conducted. Only four among the six possible categories are depicted, a classification of

‘Reverse’ or ‘Questionable’ is not possible. All 23 attributes are presented through a better-

and a worse-value which are calculated without taking into account the ‘Questionable’ and

‘Reverse’ answers. The better-worse diagram is presented in figure 4-2. At first look, the

attributes seem to be concentrated in the middle of the diagram, i.e. mostly in the areas of

‘Indifferent’, ‘One-dimensional’ and a few in ‘Attractive’. This confirms the Kano model

classification, even if the numbers of the attributes in the categories are not the same. These

differences result in the different calculation which considers only four different categories.

The attributes are mostly located around the diagonal of the diagram and are centered in the

middle. Approximately 50% of the attributes are classified as combinations.

Figure 4-2 Better-worse diagram

4.4.3.1 Delivery

Examining the better-worse diagram with regard to the nine different aspects show that the

different attributes of the aspects are quite closely located. All ‘delivery’ attributes are in the

‘One-dimensional’ quadrant. Thus, ‘delivery’ is a very important factor that companies should

F1

F2F3

F4F5

F6

F7

F8

F9F10

F11

F12

F13

F14

F15

F16

F17

F18

F19F20

F21

F22

F23

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1

Better

Worse

quality

certificates

support

packaging

delivery

warranty

after-sales

brand

payment

Indifferent

Attractive One-dimensional

Must-be


provide to manage customer satisfaction as well as to avoid dissatisfaction. The only reliable

‘One-dimensional’ attribute is ‘flexibility in changing delivery time’ (F15). This attribute is

also significant for the ‘existing customers’. However, a combination ‘Attractive’-‘One-

dimensional’ is not significant for the ‘potential customers’. This can be explained by an on-

going movement of this attribute to the ‘One-dimensional’. Two other attributes are combina-

tions and can be contemplated as changing from an ‘Attractive’ to a ‘One-dimensional’. ‘De-

livery on a specific date’ (F16) is moving toward ‘Must-be’. Concerning the created value

related to the accompanying cost, the importance of the ‘delivery’ attributes may result in

high opportunity cost that could be generated by a delivery delay or inflexibility in the

order process.

4.4.3.2 Supporting Service

All three ‘supporting service’ attributes have a positive impact on the satisfaction of the po-

tential customers. Only the ‘technical support’ attribute (F9) is already moving into direction

‘Must-be’. With a stated importance of 8.28, this may be understood as this attribute should

be provided. The majority of the customers (66%) would like to have ‘possibility of manufac-

turing more than the mounted PCBs’ (F10) and almost all customers (96%) would like to see

the ‘technical support’ and the ‘functionality recommendations’ to be fulfilled.

4.4.3.3 Certificates

The second aspect that is quite centered in the middle of the diagram is ‘Certificates’. ‘Man-

agement certificates’ (F4) is shown as ‘One-dimensional’, ‘quality certificates’ (F5) as a com-

bination of ‘One-dimensional’ and ‘Indifferent’, ‘safety certificates’ (F6) as ‘Indifferent’, and

‘Corporate Social Responsibility’(F7) as a combination of ‘Attractive’ and ‘Indifferent’. Al-

though ‘safety certificates’ are significantly ‘Indifferent’ the TS-value of 48% and a stated

importance in the range of rather important attributes result in a relation that cannot be figured

out through our analysis. It could be explained by the fact that different products have differ-

ent safety requirements and a certificate may be important for a company but unimportant for

others. 60% of the customers would appreciate if the supplier focused on ‘Corporate Social

Responsibility’. This attribute moves from ‘Indifferent’ to ‘Attractive’ in spite of the fact that

the stated importance is still in the neutral area. The need of contributions in the Corporate

Social Responsibility was brought up throughout the last decade and its influences on the

EMS market may be seen in the next coming years.


4.4.3.4 After-sales Service

The ‘after-sales service’ is placed in the border areas of the quadrants ‘Indifferent’, ‘Attrac-

tive’ and ‘One-dimensional’. ‘Repair service’ (F19) is significantly classified as ‘Indifferent’

but displayed more as ‘Attractive’. The total strength of 51% explains this difference. Since

this study is about PCBs, repairing is not considered by for some customers. In case of a de-

fect, it could be cheaper to replace the PCBs than to repair it. The ‘response time lower than 5

working days’ (F18) inclines toward ‘Attractive’ and has a stated importance of 7.28. Nearly

90% of the customers will appreciate if the response time is lower than 5 working days. The

‘spare parts handling’ (F20) is presented as ‘Indifferent’. However, the analysis indicates a

change to ‘One-dimensional’ and that 60% of the customers would like to have the supplier

who can overtake the spare parts handling. An interview with customers of EDC shows that

‘spare part handling’ has been a responsibility of the B2B customers but is now more and

more moving toward the supplier.

4.4.3.5 Product Quality

The aspect ‘product quality’ is located in the middle of the diagram. The attribute, ‘percentage

of the defects lower than 0.1%’ (F1), is displayed as ‘Must-be’. However, this attribute is not

at a significant level due to the relatively small number of customer samples. A combination

of ‘Must-be’, ‘One-dimensional’ and ‘Indifferent’ indicates that the percentage of defects

must be kept low due to the generated cost in cases of repair necessity and product recall. The

influence of the ‘Indifferent’ category may be interpreted that defects are unavoidable. Fur-

thermore, an acceptable percentage of defects depends strongly on the manufactured product,

the components in use, and the complexity level. Hence, the attribute (F1) may be difficult to

classify. ‘Testing reports’ (F2) are placed as ‘Attractive’ even if they are classified as ‘Indiffe-

rent’-‘One-dimensional’. This may display the development of the attribute toward ‘One-

dimensional’. Making testing reports of the products accessible to the customers facilitates

cause study in case of defects or failures. As an ‘Indifferent’ attribute, ‘upgradability’ (F3) has

a relatively high stated importance with 7.09. Furthermore, the TS-value of 59% states that

more than half of the customers expected the supplier to provide this attribute. A significant

level of 10% is related to a sufficient CS-value for categorization. The position of F3 is de-

termined in the ‘Indifferent’ quadrant of the better-worse diagram but in the border with ‘At-

tractive’. This indicates a change in the attribute categorization or it may only be from specif-

ic customers who want to have a possibility of outsourcing rather than only manufacturing. It

could be understandable that customers with a well-known brand and an established supply


chain are not interested in this attribute. However, the analysis of different customer groups did

not show any hint of the relationship between the customer characteristic and the categorization of

this attribute.

4.4.3.6 Warranty

Providing an extended warranty (F17) is significant ‘Indifferent’ and this also shows the posi-

tion in the better-worse diagram in the lower left corner. The total strength is supporting this

classification with a very low value of 4.26. As already mentioned, ‘more than 12 months

warranty’ is not only not expected to be there but can also create dissatisfaction if this

attribute is provided in combination with a higher price. This is based on viewpoint of a part

of the large-scale companies that would classify this attribute as ‘Reverse’.

4.4.3.7 Packaging

Both ‘packaging’ attributes are displayed in the ‘Indifferent’ quadrant. With a TS-value of

6.38, less than 7% of the customers state that the attribute ‘shipped in pallets’ (F11) should be

provided. The ‘Indifferent’ classification seems understandable due to the fact that shipping in

pallets is not required for all products and depends on characteristics of orders. This means

that the attributes are defined in the certain contracts. The second ‘packaging’ attributes is

‘more than average fragile protection’ (F12) and not located close to the F11 but still dis-

played as ‘Indifferent’. The TS-value of 55.32 lowers the validity of the ‘Indifferent’ classifi-

cation an α-level of 10%, because more than half of the customers would like to get this

attribute. The vicinity to the ‘Attractive’ quadrant supports this and a classification in which

‘Indifferent’ and ‘Attractive’ are combined may be more appropriate. The need for an addi-

tional fragile protection is likely dependent on the product specification and the components

inside. Thus, the combination classification may be explained.

4.4.3.8 Brand

The position of the attribute ‘well-known brand’ (F21) associated with ‘Indifferent’ is in line

with the categorization. However, the TS-value indicates that 36% of the customers would

appreciate that the supplier has a well-known brand. In contrast, the customers may not focus

on suppliers with a strong branding to avoid any negative side-effects on the strength of their

own brand.


4.4.3.9 Payment Term

Regarding the ‘payment term’ in table 4-2, the attribute ‘discount if payment in advance’

(F22) has been classified as ‘Indifferent’ category while ‘discount for large quantity order’

(F23) is placed in the ‘One-dimensional’ category. The classification of ‘Indifferent’ in F22

indicates that the customers are in neutral perspective at a significant level of 0.05 whereas

the other at a not significant level. The high reliability of this attribute in accordance with the

stated importance of 5.17 can confirm the unimportance of partial payment in advance. Cash

flow in a manufacturing company is really essential because the company can use cash to buy

different types of material for manufacturing steps. Thus, it seems hard for B2B customers to

transfer money partially before delivery. Although the price is lower the B2B customers may

face troubles with their cash flow, which may interrupt manufacturing process. For payment

aspect, a multiple choice has been asked to aim at finding out a preferred payment time (see

table 4-4).

Table 4-4 Preferred payment time

"A shorter payment time leads to a lower price." Which payment time would you prefer?

Frequency Percent Valid Per-

cent

Cumulative

Percent

Valid

Payment within 30 days after 25 51.0 53.2 53.2 Payment within 60 days after 17 34.7 36.2 89.4 Payment within more than 60 5 10.2 10.6 100.0

Total 47 95.9 100.0 5 Missing System 2 4.1

6 7 Total 49 100.0 8 9

The sooner the customers pay after delivery, the lower the price is offered. 53.2% of custom-

ers chose the soonest payment time, within 30 days after delivery. Using correlations between

the turnover of the companies and the preferred payment time, a significant level of 0.01 indi-

cates the high reliability of the outcome. The correlation coefficient of 0.586 shows a mod-

erate and almost strong positive relationship. The more the value is close to 1, the higher the

positive correlation is.


Table 4-5 Correlation between turnover and preferred payment time

Correlations using Spearman’s rho

Turnover Preferred payment time

Turnover Correlation Coefficient 1.000 .586** Sig. (2-tailed) . .000 N 46 46 Preferred Correlation Coefficient .586** 1.000 Sig. (2-tailed) .000 . N 46 47 ** Correlation is significant at the 0.01 level (2-tailed)

The table 4-5 also indicates that the higher the turnover that the companies gain, the longer

payment time the companies tend to select. This means a higher flexibility for the large-scale

companies which they may need due to a usual higher variety in products and suppliers com-

pared to the small scale. Furthermore, paying later creates also a higher cash flow today.

Thus, compared to the companies with a lower turnover, these companies have a bigger cash

flow and more negotiation power against the supplier, both resulting out of a often higher

order quantity which means more profit for the supplier.

Conclusion 35

5 Conclusion

The last chapter summarizes main findings of the study. The recommendations for EDC are

given. The limitation and further research are also suggested.

5.1 Summary of the main findings

The findings of this study are clearly indicated in the Table 4-2. In a general overview, ‘prod-

uct quality’ is selected as the most important aspect when the customers were asked to rank

the importance of the nine aspects. ‘Delivery’ is in the second position, ‘supporting services

in the third position and ‘brand’ is the least important while considering the created value but

also the accompanying cost. However, an in-depth investigation of the attributes of these nine

aspects, the result reveals some small differences. ‘Delivery is then showed as the most in-

fluencing attribute, followed by ‘product quality’ and ‘supporting service’, while considering

the created value and the related cost.

In ‘product quality’ aspects, the B2B customers expect EDC to obtain the ‘percentage of de-

fective products less than 0.1%’ but they seem indifferent with ‘testing report’. ‘Delivery’ is

somewhat considered very important since four attributes in delivery aspect were mostly ca-

tegorized into ‘One-dimensional’, ‘Attractive’ or a combination of these categories. These are

also at an average stated importance of 8.15. The customers generally tend to focus on ‘short-

er lead time’, ‘delivery on a specific date’ and the ‘flexibility in changing the delivery time’.

A shorter lead time enables the B2B customers to deliver their products to the end-customers

in the shortest time. The more satisfied the end-customers feel, the more profit the B2B cus-

tomer may gain. Thus, a higher price with a shorter lead time may be acceptable.

Another important aspect in customers’ point of view is ‘supporting service’. ‘Technical sup-

port’ is preferred by both customers groups: exiting customers and potential customers. For

the B2B customers, a provided ‘technical support’ facilitates e.g. the integration of the prod-

ucts into other materials for manufacturing end-products. ‘Functionality recommendations’

and ‘possibility of manufacturing more than mounted PCBs’ are not of interest for the poten-

tial customers. Nevertheless, existing customers may accept to pay a higher price for acquir-

ing these attributes.

Besides the three mainly important aspects, further attributes are to highlight. Regarding the

‘payment term’, a notable point is a concern of ‘discount for large quantity order’, especially

for the potential customers. ‘Payment within 30 days after delivery’ is preferred by the ma-

Conclusion 36

jority of the customers. Concerning the ‘certificates’ aspect, the customers feel satisfied if the

supplier has ‘quality certificates’ such as ETL-approved production. Exploring ‘after-sales

service’, ‘claim handling lower than 5 working days’ is also recommended since the custom-

ers may feel convenient if problems are solved as soon as possible. Concerning the ‘packag-

ing’, large-scale companies, which have the turnover of more than 100MSEK, may feel satis-

fied if ‘shipping in pallets instead of boxes’ is offered. Conversely, small scale companies

have an ’indifferent’ attitude about this attribute. Regarding ‘warranty’, the policy of ‘12

months warranty’ seems not enough from the viewpoint of the big companies who have

strong negotiation and numerous selections of suppliers. They expect to be offered a longer

warranty time, i.e. more than one year, without paying any extra cost. ‘Brand’ is considered as

the least important factor from the viewpoint of the existing customers. However, from the

potential customers' perspective, this aspect is somewhat evaluated higher, i.e. in the middle

position among nine aspects.

For the attribute 'spare part handling', it is to state that 60% of the customers tend to think that

spare parts should be the responsibilities of the suppliers. The other remaining attributes are

seen as less important from the customers’ perspective.

5.2 Recommendations for EDC

The purpose of this part is to come up with a graphic that demonstrates which factors are less

or more important. It is also shown which aspects the company should focus on to create not

only value for the customers but also perform in an economic and efficient way. The new

model is presented in the following.

Figure 5-1 Customer value creation in EDC’s supply chain

Conclusion 37

Some concrete recommendations for EDC AB are found from this research work as follows.

The most important factor to focus on should be the attribute ‘percentage of defective prod-

ucts lower than 0.1%’. However, being aware of the fact that an acceptable percentage of de-

fects depends on the product specifications, the mentioned figure of 0.1% cannot therefore be

taken as a generally valid value. Continuous improvements in the EDC technical equipment

as well as skills of the experts and technicians are necessary. For example, training programs

can help the staff to be equipped with updated techniques. Furthermore, decreasing the per-

centage of defects is also a management task. Creating optimal conditions, controlling and

assuring the compliance with rules and standards are suggested.

‘Delivery’ is another relevant aspect. A smooth manufacturing process in combination with

sufficient supply of raw materials decreases the risk of delayed delivery. Delivery may affect

the dissatisfaction of the customers and may make them to look for new suppliers who can

bring better values for them. Additionally, strong efforts should be undertaken to be able to

deliver products in time as negotiated. Flexibility in delivery time and quantity order may be

included in the contract since this is preferable by the customers. The fourth aspect ‘delivery

on specific date’ is also considered as very important for the customers since this attribute is a

combination of ‘One dimensional’ and ‘Must-be’ attribute.

In terms of ‘supporting service’, EDC’s main concern should be to improve the functionality

of the products by providing recommendations to the customers. For example, finding substi-

tutes for components to decrease the cost and assuring that the products are designed to manu-

facture them in an efficient way are good recommendations. Furthermore, the ‘technical sup-

port’ department is expected to be available when problems occur. This makes the customers

feel more believable, comfortable and satisfied when they set up business with EDC. Once the

customers feel satisfied at a certain degree, they may accept to pay at a higher price for the

values they can receive.

Additionally, ‘discount for large quantity order’ is considered as preferable especially for the

potential customers. This could be used in the negotiations with the customers. However, the

classification as One-dimensional shows that this attribute is somewhat expected.

5.3 Limitations of the Study

The outcomes of the study show the factors influence the buying decision of B2B customers

in the electronic manufacturing market. Depending on the created values in relation with the

accompanying cost, the factors could be interlinked.

Conclusion 38

Despite contribution to business research and EDC company, this thesis includes several limi-

tations. Owning to the time constraints and the specific requirements for the respondents such

as being a purchaser of PBCs, the questionnaire could not be delivered to a large number of

customers. Thus, this is followed by a limited number of observations and a low response

rate. Therefore, it was not possible to classify all attributes to a significant level of 5%. The

small sample size influences also the validity of the t-test because some conditions have been

not fulfilled.

For a future research, the number of respondents should be increased so that the reliability of

analysis results can be improved. Additionally, further in-depth research focusing on main

concerns such as ‘delivery’ and ‘product quality’ can be conducted with an objective of gain-

ing more information about potential competitive advantages. A more quantitative approach

in the relationship between the different attributes could also be interesting to investigate.

References 39

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Appendix 42

Appendix Appendix A1

Attributes Explanation

Product Quality

percentage of defects lower than 1%

F1 Defective products refer to the ones which cannot be used due to faulty

testing report

F2 Reports are provided to the customer including the results of quality, func-tionality and compatibility tests after the products are manufactured.

Upgradability F3 The replacement of a product by a newer version of the same product en-sures that there is no incompatibility with the outdated components.

Certificates

management certificates F4 Certificates e.g. ISO 9000, ISO 14000 show that the products are manufac-tured in standardized processes (ISO, 2011)

quality certificates F5 Certificates e.g. Electric Testing Laboratory approved production (ETL),prove that the products meet the minimum requirements of product quality

safety certificates F6 Certificates e.g ATEX directive 94/9/EC, describe which equipment and which work are allowed in an environment with explosive atmosphere

Corporate social res-ponsibility

F7 Awards relate to environmental and social activities of the company con-tributing to the society

Supporting Service

functionality recom-mendation

F8 Suppliers’ recommendation: Recommendation e.g. functionality which is given by EDC, make the ordered products with more functionality while assembling with other components, and thus effective solutions for time and money saving

technical support F9 This is the responsibility of EDC to solve technical problems, e.g: how to integrate the PCBs into the products

possibility of manufac-turing more than the mounted PCBs

F10 This indicates that EDC covers more steps in a supply chain. EDC not only provide the purchased products but also offers other service such as logis-tics, assembling PCB into the end-products

Appendix 43

Packaging

shipped in pallets in-stead of boxes

F11 This involves the product protection. Pallet is a flat transport structure that supports goods in a stable fashion

more than average fra-gile protection

F12 More than average fragile protection: This also involves the product pro-tection. For example, using thicker carton can avoid damaging easy-broken products

Delivery

shorter lead time F13 A lead time is “the time between starting and completing a production

process” (Oxford 2007)

flexible time to change order quantity

F14 Flexible time to change the order quantity: Quantity of the ordered prod-ucts should increase or decrease flexibly after signing the contract

flexibility in changing delivery time

F15 Flexibility in changing the delivery time: Delivery time may be changed by negotiation

delivery on specific date F16 On-time delivery on a specific confirmed date: Products are delivered on the date given in the contracts, sooner or later may not be accepted

Warranty

more than 12 months warranty

F17 The supplier expects to bring more values and take more risks with a long-er time of warranty

After-sales Service

response time < 5 wor-king days

F18 Average response time to handle claims is lower than 5 working days

repair service F19 Repair service is provided if there are any arising problems with the prod-ucts

spare parts handling F20 Spare parts handling is the suppliers’ responsibility: Spare part is a new part to replace an old or broken part of a machine

Brand

well known brand F21 Order from a supplier with a well-known brand: This shows a high reputa-tion in the market

Payment

discount if payment partially in advance

F22 Discount if payment is done partially in advance: A lower price is offered if the total value of a contract is paid partially after being signed.

discount for large quan-tity order

F23 Discount for large quantity order: A lower price is offered with a higher amount of quantity

Appendix 44

Appendix A2-1

Classification According to Högström (2011)

According to Lee & New-comb (1997)

According to Berger et al.

(1993)

According to Kano et al.

(1984) M 6.72 6.72 6.71 6.71 O 6.45 6.45 6.46 6.99 A 5.86 5.84 5.86 6.10 I 5.09 5.09 5.06 5.19 R 1.20 1.20 1.20 1.20 Q 0.52 0.52 1.29 0.26

Appendix A2-2

Classification According to Högström

(2011)

According to Lee & New-comb (1997)

According to Berger et al.

(1993)

According to Kano et al.

(1984) M 1 1 1 1 O 7 7 7 1 A 3 3 3 5 I 11 11 11 14 R 0 0 0 0 Q 0 0 0 0

M, O 0 0 0 1 M, I 0 0 0 1 O, A 1 1 1 0 Total 23 23 23 23

Appendix 45

Appendix A3-1 Existing customer

Appendix 46

Appendix A3-2 Potential customers

Appendix 47

Appendix 4

Turnover up to 100 MSEK Turnover over 100 MSEK

t-value df Sign. classification t-value Df Sign. Classification

F1 0.00 20 n.s. M, I 0.63 23 n.s. M, O, A

F2 0.95 19 n.s. O, I 0.90 23 n.s. I, A

F3 0.33 19 n.s. I, O 0.90 23 n.s. I, A

F4 0.65 20 n.s. O, I 0.30 23 n.s. O, M

F5 0.32 20 n.s. I, O 1.23 23 n.s. O, A

F6 1.09 17 n.s. I, O, A 3.60 23 0.05 I

F7 0.63 20 n.s. I, A 0.59 23 n.s. I, A

F8 0.65 20 n.s. A, O, M 2.09 23 0.05 A

F9 0.00 19 n.s. M, O 0.59 23 n.s. O, M

F10 0.62 20 n.s. I, A 2.44 23 0.05 A

F11 3.88 20 0.05 I 3.46 23 0.05 A

F12 1.64 20 n.s. I, O 0.00 23 n.s. A, I

F13 0.61 20 n.s. A, O 0.57 23 n.s. O, A

F14 0.32 20 n.s. A, O 0.87 23 n.s. O, A

F15 1.91 20 0.05 O 2.41 23 0.05 O

F16 1.25 20 n.s. O, M 0.57 23 n.s. O, M

F17 3.83 20 0.05 I 0.86 23 n.s. I, R

F18 0.65 20 n.s. A, O 0.61 22 n.s. A, O

F19 1.59 20 n.s. I, A 1.49 23 n.s. I, O

F20 1.34 19 n.s. I, O 0.94 22 n.s. I, O, A

F21 2.98 20 0.05 I 2.07 23 0.05 I

F22 1.32 20 n.s. I, M, O 3.97 23 0.05 I

F23 1.25 20 n.s. O, M 0.00 23 n.s. M, O

Appendix 48

Appendix A5-1 Questionnaire page 1

Appendix 49


Appendix 50


Appendix 51


Appendix 52


Appendix 53


Appendix 54


Appendix 55


Appendix 56


Appendix 57


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