Improving E.nu performance by assessing relationship quality

2

Author : L.N. Korevaar (Nijs)

Study : MSc Technology Management

Student number : 1340034

Email : L.N.korevaar@gmail.com

Faculty : Economics and Business

Supervisor : dr. ir. N.R. Faber

Co-assessor : drs. S.Sibum

3 The E.nu concept is a long-term collaborative relationship that is called partnering in construction supply chain literature. Partnering is seen as an innovative way to stimulate integration of the construction supply chain.

Relationship quality is a measure of how collaborative a relationship is. E.nu relationship quality has 6 dimensions: trust, objectives, teamwork, communication, continuous improvement and problem solving.

InstalNova provides support to the E.nu participants by helping them found the partnership and by providing them with access to their network. The general manager of InstalNova wishes to assess relationship quality within E.nus in order to improve E.nu performance. Successful partnerships have a high relationship quality and reported outcomes of such partnerships are: trust, culture change, increased collaboration, learning, increased quality, reduced costs, increased predictability, faster construction, increased turnover and profits, best value and fewer accidents.

The resulting main research question is:

How can relationship quality be assessed in an E.nu partnership?

In this thesis a measurement instrument is designed and validated. The design is based on the scale development procedure that is an appropriate research method for developing measurement instruments. An assessment procedure is proposed that enables the implementation of the measurement instrument in the E.nus. The assessment procedure consists of the following steps: initial survey, calculating scores, score representation, discussion, goal setting, improvement efforts and survey.

4

Preface

This thesis is the final chapter of the time I spent at the University of Groningen. After nine years I can finally say that I am ready to start contributing to the treasury of the Netherlands by starting working life. During this time I found out that it was hard to combine a career as a disk-jockey (with regular work until 08:00 in the morning) with exams, papers and workgroups. After playing in almost all large clubs in the Netherlands I came to the conclusion that I did not want to keep doing this till my retirement.

As a result I solicited for participation in an Amsterdam based think-tank that tried to find ways to create CO2 neutral neighborhoods in existing cities. During this time I came into contact with the sustainable construction sector and the E.nu partnerships that are the subject of this thesis. After a construction supply chains master class from prof. A. van Hal my interest in the construction sector was established.

I found it mind-blowing that a supply chain as old as the construction sector had not been able to benefit from the huge improvements that have taken over manufacturing. I would like to give an example: If you buy a new house in the Netherlands it is common that upon completion you walk through the house with the main contractor to inspect for faults. If you have less than 10 faults you can consider yourself a lucky man. Imagine that this would be the same at the cardealer: cracks in the body, one wheel squeaks and the oil would drip from under your car by the gallon. Would you consider this acceptable? This thesis is my first attempt to try to improve the construction supply chain and I imagine that this sector will be my professional area for the next couple of years.

I would like to thank dr. ir. N. Faber for all the advice and guidance he has given me, mister Adrie van Duijne (InstalNova) for the support of my research at the E.nus, drs. S. Sibum for being my second corrector on such a short notice and Martijn Harink and Theo Wever for pre-testing my survey. Enjoy reading my master thesis!

Nijs Korevaar

5

2. Literature framework ... 8

2.1 Supply chain ... 8

2.2 Construction supply chain ... 8

2.3 Construction supply chain performance... 8

2.4 Partnering ... 10

2.5 Partnering and business performance ... 11

3. Research Framework ... 13

3.1 Problem statement ... 13

3.2 Limitations ... 14

3.3 Research process design ... 15

3.4 Data collection method ... 16

4. Diagnose ... 18

5. Design of the measurement instrument ... 21

5.1 Conceptualization ... 21

5.2 Scale development ... 23

5.4 Data collection ... 25

5.5 Statistical analysis... 26

6. Implementation of the measurement instrument ... 32

6.1 Data representation ... 32 6.2 Assessment procedure ... 33

7. Evaluation ... 35

References ... 41

Appendix I: Figures and Tables ... 45

Appendix II: Construct items and their sources ... 49

Appendix III: Pilot study ... 51

Appendix IV: Questionaire ... 54

6

Part I – Diagnoses

Diagnoses

Design

Evaluation

Design of measurement instrument

Conceptualization Development Data collection Statistical analysis Conclusion

Implementation

7 The recent economic crisis has hit the construction industry hard and still there are no signs of a return to growth in this sector. Changing business circumstances provide companies or supply chains with the opportunity to innovate and come out of a crisis with a better value proposition to its customers and reap the benefits in the years of growth after the crisis. Partnering in construction, a collaborative supply chain management concept, has been seen as the way to progress from traditional adversarial relationships to cooperative relationships with suppliers and buyers similar to the manufacturing industry. E.nu is such a partnering concept that is aiming to provide sustainable construction works to construction clients.

E.nus are aimed at sustainable construction works and provide a premium solution to the customer at a premium price. The first reason for Uneto-VNI to initiate these partnerships is that in order to provide better value to the customer it is necessary that specialized sub-contractors (e.g. installers, glass fitters) are involved in the early stages of the design process. Secondly, Uneto-VNI envisioned a scenario where installers would be squeezed by main-contractors while they provide the most value to the customer. Additionally, margins in the construction industry are under pressure by low construction supply chain performance and competition solely on price. By improving cooperation between actors in the construction supply chain, failure costs can be reduced thereby increasing profitability. Finally, the fragmentation of the sustainable construction supply chain endangers the energy consumption reduction envisioned by the Dutch government.

One of the main causes is that property owners do not know where to start improving their building‟s energy performance. By integrating advice on- and implementation of sustainable construction works, E.nu offers government officials a way to accomplish their climate goals. The belief that the quality of sustainable solutions is dependent on collaboration of the implementing parties is the driving force behind the E.nu concept.

8

2. Literature framework

In this chapter the concepts supply chain, construction supply chain, partnering and relationship quality are explored. The chapter is concluded with a conceptual model that relates relationship quality to performance.

2.1 Supply chain

The supply chain is defined by Christopher (1992) as:

“The network of organizations that are involved, through upstream and downstream linkages, in the different processes and activities that produce value in the form of products and services in the hands of the ultimate customer”.

A typical supply chain will begin at some form of (natural) resource followed by production facilities and will end at the consumer after been through a logistics system. Such a generic manufacturing supply chain is depicted in Figure 1.

Figure 1: Generic manufacturing supply chain

2.2 Construction supply chain

Cox & Ireland (2002) identify five major sub-supply chains that characterize the construction industry: construction integration, professional services, materials, equipment and labor. These supply chains display significant overlap and construction organizations often participate in all or a majority of these supply chains. It should be noted that the number of subcontractors and suppliers could be hundreds or even thousands in larger and specialized construction projects. The construction industry's supply chains are depicted in appendix I.

2.3 Construction supply chain performance

In 1993 O‟Brien and Fisher found empirical evidence that there is potential to improve the construction supply chain performance. Errasti et al. (2006) state that main contractors and subcontractors need to improve their performance in terms of quality, service and cost to remain in business. There are four characteristics that are considered to be the causes of the underperformance of the construction supply chain.

9 Even though, future projects can be very similar and are often produced by reconfiguration of current project organizations. Learning from past and present projects as described by Kumaraswamy and Dulaimi (2001) is more difficult than in a “normal” manufacturing supply chain.

2.3.2 Fragmentation

The construction supply chain is characterized as being fragmented (e.g. Cox and Ireland, 2002; Briscoe et al., 2004; Tookey et al., 2001). Not only is the design and build of a construction project often separated, but sub- and sub-sub-contracting are a common phenomenon. The reasons behind this phenomenon are cost reductions and the mitigation of project risk. Sub-contractors can be specialized in labor, skills, materials or knowledge that enable them to complete a part of the project at lower cost than when the main-contractor would construct this project part himself. Sub-contractors are also responsible for their part of the project and bear the risks associated with failure or complications that occur on this project part. This fragmentation leads to communication, scheduling and litigation problems.

2.3.3 Adversarial relationships

The relationships between actors in the construction supply chain are generally highly adversarial and contested. According to Cox and Ireland (2002) this is because of the conflicting nature of supply and demand in the construction supply chain. The conflicting nature of supply and demand is caused by the focus of both the buyer and seller on costs, other factors are only accessory (e.g. construction speed, quality, safety of construction workers). This leads to a highly competitive market for clients, main-contractors and sub-contractors where switching costs are low and supply is plenty. In order to make more profit, actors down the supply chain are „squeezed‟. If a seller does not comply with the lowered price, the buyer simply turns to a competitor. These adversarial relationships prevent the construction supply chain from collaboration and make sub-contractors wary of supply chain initiatives from main-contractors (Dainty et al., 2001)

2.3.4 Traditional procurement

10

2.4 Partnering

Partnering is the most frequently used institutional form of a collaborative relationship in the construction industry (Wood et al., 2002). Partnering was introduced in the construction sector as an attempt to translate the collaborative relationships seen in the manufacturing sector to the construction supply chain. It was expected that these collaborative relationships would counter the causes of construction supply chain underperformance as stated in 2.3.

While the consensus in the academic world is that there is no unified understanding of the partnering concept (Li et al., 2000; Nyström, 2005), the Construction Industry Institute‟s (CII) definition of partnering is most commonly used (Bygballe et al., 2010). The CII defines partnering as:

„„A long-term commitment by two or more organizations for the purpose of achieving specific business objectives by maximizing the effectiveness of each participant‟s resources. This requires changing traditional relationships to a shared culture without regard to organization boundaries. The relationship is based upon trust, dedication to common goals, and an understanding of each other‟s individual expectations and values. Expected benefits include improved efficiency and cost-effectiveness, increased opportunity for innovation, and the continuous improvement of quality products and services.‟‟ (CII, 1991, p. iv)

The concept of partnering has become an umbrella for collaborative forms of relationships. There are generally 2 types: Project partnering and strategic partnering. Project partnering is a partnership that exists for the length a specified project, strategic partnering spans indefinitely over all or a particular range of projects that are carried out (Li et al. 2000).

2.4.1 Relationship quality

The construct relationship quality is introduced as a measure of “good” or “poor” relationships by Naude & Buttle (2000). This construct is further developed by Fynes et al. (2005) as a measure of how “good” or “close” the relationship between partnering organizations in a supply chain is. They state that relationship quality is defined as the degree to which parties in a relationship are engaged in an active long-term collaborative relationship. Therefore, relationship quality becomes a synonym for the level of collaboration between actors in a supply chain. Relationship quality can then be operationalized using the key relationship indicators of construction supply chain relationships.

2.4.2 Key relationship indicators

11 indicators. Meng (2010) argues that the indicators business attitude and objectives can be merged as win-win/win-loose business attitudes are the basis and outcome of shared or conflicting objectives. The resulting 8 top indicators are the indicators that determine the level of relationship quality between actors in a construction supply chain.

Kim et al. (2010) also conducted a literature study exploring critical success factors in supply chain partnerships but uses partnering studies across multiple industries. While Kim et al. (2010) use fewer articles and therefore found a shorter list of key relationship indicators, these indicators can also be found in- or converted to -the top 8 relationship indicators of Meng (2010).

2.4.3 Conceptual model of partnering

Beach et al. (2005) proposed a conceptual model of partnering based on the key relationship indicators they found in their literature research. Updating these indicators with the findings of Meng (2010) and dividing the outcomes of partnering in operational and relational outcomes as proposed by Zacheria et

al. (2009) provides the conceptual model of partnering that is used in this thesis. This model is

depicted in appendix I figure 2.

2.5 Partnering and business performance

Partnering was presented in the Egan (2002) report as the vehicle to improve the construction industry‟s underperformance by the integration of the construction supply and thereby countering the problems described in chapter 1.3. This idea is supported by Fynes et al. (2005), Zelbst et al. (2009) and Zacharia et al. (2009), who all found a positive relation between relationship quality or collaboration level and supply chain or business performance in other industries then construction.

2.5.1 Outcomes of partnering

Zacharia et al. (2009) argue that collaborative relationships will have two types of results: relational outcomes and operational outcomes. In order to create a comprehensive list of partnering outcomes, 5 literature studies into the benefits of partnering are analyzed in Appendix 1 (table 2). These studies include positive and critical reviews of the outcomes of partnering. In this analysis both relational and operational outcomes are presented. The relational outcomes of partnering are: trust, culture change, increased collaboration and learning. The operational outcomes of partnering are: increased quality, reduced costs, increased predictability, faster construction, increased turnover and profits, best value and fewer accidents.

12 between partners that in turn enable enhanced efficiency of activities within and between companies. Mutual orientation makes partners knowledgeable of each other, which improves decision making by taking into account benefits and costs of the other company or companies. The consensus in the academic world is that closer or higher quality construction supply chain relationships lead to an increase in construction supply chain performance.

2.5.2 Conceptual model of relationship quality and supply chain performance

There are currently no studies that directly link relationship indicators to supply chain performance outcomes. But as the key indicators of relationship quality are also critical success factors for partnering they can be linked as a whole to supply chain performance improvements reported in studies into partnering. The result is the following conceptual model depicted in figure 3 below.

Relationship quality · Trust · Objectives · Teamwork · Risk allocation · Communication · Continuous improvement · Problem solving · Procurement system

Supply chain performance

· Increased quality

· Reduced costs

· Increased predictability

· Faster construction

· Increased turnover & profits

· Best value

· Fewer accidents

13 The research framework consists of an analysis of the problem situation, limitations in which the study is conducted, the research methodology and the chosen data collection method.

3.1 Problem statement

Uneto-VNI (branch organization for installers), Syntens and TNO engineered a construction supply chain partnership concept called E.nu. InstalNova was established as an organization to oversee the creation and management of the E.nu partnerships. E.nu is a concept in which construction supply chain actors (I.E. main-contractors, isolation companies, glaziers, installers) are integrated in the field of sustainability to form an „one stop shop‟ for clients. The idea of an integrated construction supply chain has risen after several meetings with construction supply chain actors and clients who stated numerous problems with the current situation (e.g. lack of quality, low profit margins, schedule delays, suboptimalization of proposed solutions). An E.nu is formed as a supply chain partnership where all participants are responsible for the projects undertaken by the E.nu. After the decision to adopt the E.nu concept by all of the forthcoming participants, the new cooperation has to restructure their respective business processes to construct an integrated one-stop-shop for all sustainable construction works. Until now, 25 different E.nu partnerships have been initiated at different locations in the Netherlands over the last 2 years.

The general manager of InstalNova, Mr van Duijne, discerns that the performance in terms of profit, quality and predictability of time and costs of some of the E.nu partnerships are lagging and resemble the performance from before the adaption of the E.nu concept. This leads to the problem statement of my research.

How can InstalNova improve the average performance in terms of profit, quality and predictability of the E.nu partnerships?

14 InstalNova would like to create a tool for measuring supply chain relationships to:

1. Assess the current relationship quality in E.nu partnerships

2. Help specific E.nu partnerships to improve their supply chain relationship quality 3. Learn from current practices and enhance E.nu as a concept altogether

This leads to the objective of this research:

Developing a tool that assesses relationship quality in E.nu partnerships

This objective leads to the following main research question:

How can relationship quality be assessed in an E.nu partnership?

To answer the main research question, following sub questions need answering: 1. How can relationship quality be measured in an E.nu partnership?

a. What are the dimensions of relationship quality in an E.nu partnership?

b. How can the dimensions of relationship quality be measured in an E.nu partnership? b. Is the measurement instrument valid for measuring relationship quality in E.nus? 2. How can relationship quality be assessed in the E.nu partnerships?

a. How can E.nu relationship quality scores be presented comprehensively? b. How can E.nu relationship quality measurement be implemented in the E.nus? c. How can E.nu relationship quality be measured in a continuous way?

3.2 Limitations

The limitations form the boundaries in which this research project has to be performed. There are two types of limitations in practical research: limitations regarding the result of the research project and limitations regarding the research process itself (De Leeuw, 2001).

3.2.1 Research process limitations

The limitations concerning the research process are:

· The timeframe of this research will be 6 months, starting at 1-1-2011 and finishing at 30-6-2011

· There is no budget to hire external advisors or experts

· This report has to be reviewed by mr. van Duijne as outcomes of this study may contain sensitive information on the E.nus

15

· Only the variable relationship quality is used to improve E.nu performance. Other external factors as client commitment (Beach et al., 2005) and market conditions are not accounted for

· The organizational boundaries of the E.nu are also the boundaries of this research. Clients and suppliers are not considered in this research

· This study will have multiple customers, Uneto VNI, Syntens and TNO will be the primary clients but it has to be understandable for the E.nus as well

3.3 Research process design

The research in this report is based on the methodology of design-focused research as presented by van Aken et al. (2004). This methodology is suited for developing scientific knowledge that can be used to design interventions by practitioners in the field. Design-focused research aims to change the current situation by intervening in organization practice in order to develop a desired situation. In this study the desired situation is one with improved supply chain performance and this is achieved through measuring and improving supply chain relationship quality.

In this thesis the regulative circle (van Strien, 1986) is used as a meta-methodology instead of the empirical cycle. The empirical cycle is not suited to deal with interventions in practice, whereas the regulative circle is specially designed for intervening into practice by making a plan in which the focus is on solving a specific problem under specific circumstances. The regulative cycle consists of several stages: Diagnose phase, design phase, implementation phase and evaluation phase. The time constraint causes that only the diagnose and design phase will be fully performed in this study. However, there will be a detailed plan on how the measurement instrument can be implemented in the E.nus and an evaluation of the research performed in this study.

16 The goal of the design phase is to produce a solution to the problem stated in the problem statement. In this phase a relationship quality measurement instrument is designed. The design phase is presented in chapter 5. The design is based on the scale development procedure (Churchill, 1979) that is an appropriate research method for developing measurement instruments. This procedure consists of the following four interrelated steps:

· Conceptualization

· Scale development

· Data collection

· Statistical analysis

The implementation phase aims to intervene in the current situation and realize the desired situation using the design produced in the second step. The implementation phase is presented in chapter 6. In this phase a method will be presented that will enable measurement, presentation and diagnoses of relationship quality in the E.nu partnerships. Due to the time constraint it is not possible to implement this method in the E.nus as it first has to be evaluated by the management of InstalNova. Additionally, the E.nus have to support the assessment of relationship quality and this study will enable them to discover what the benefits of relationship quality assessment could bring them.

Finally, in the last phase of the regulative cycle, the conclusions of this study will be presented in chapter 8 together with the recommendations and a discussion.

In figure 4 on the next page the research process is depicted, including the chapter numbers mentioned in this section.

3.4 Data collection method

When considering the data collection method there are two aspects that have to be addressed: a) the source of the data and b) the method of observing or measuring the data (De Leeuw, 2001). Because this study is based on the methodology of design focuses research there will not only be data from desk research, but also from research in real business situations.

17

Diagnoses

Design

Evaluation

(5) Design of measurement instrument

Conceptualization Development Data collection Statistical analysis (7) Conclusion

Implementation

(6) Implementation of the measurement instrument

18

4. Diagnose

The E.nu concept is a long-term collaborative relationship that is called partnering in construction supply chain literature. Partnering is seen as an innovative way to stimulate integration of the construction supply chain, as most relationships are still considered adversarial.

In the literature framework the problem situation that faces the construction supply chain as a whole is presented. In this chapter the problem situation of the manager of InstalNova, mr. van Duijne, is multiformly analyzed using the organizational metaphors of Morgan (2006). Only metaphors that are relevant for the problem situation are analyzed.

Machine

Jackson (2000) states that organizations viewed from the machine metaphor strive for maximum efficiency. Efficiency is stimulated by a high level of control over the business processes. The manager of InstalNova and even the E.nu participants, have no way to measure and thereby control the relationship quality in E.nu partnership. A relationship quality measurement instrument will give InstalNova and the E.nus themselves a way to improve their control on the relationships between E.nu participants.

Culture

The adversarialism that has grown over the years of doing business in a sector where mostly costs were important is not easily reversed. Discussion on the relationships between E.nu participants should stimulate a more collaborative culture.

Organism

The organism metaphor stresses the interrelationship between the parts that form the complex system that is an organization (Jackson, 2000). An E.nu is based on the parenting companies of the participants. Managing the relations between these different actors and thereby organizations, is even more difficult than in a single organization.

19

Figure 4: Lifecycle of supply chain partnerships (based on Kim et al., 2010)

The management of the E.nus has been primarily focused on the founding of new E.nus and giving support to the existing E.nus. This support consists mainly out of coaching in the first months and access to the network of InstalNova and its founding partners Uneto-VNI, Syntens and TNO. In figure 6 below the founding process of an E.nu is depicted.

Figure 5: Founding process of an E.nu

The first three phases of the partnership life cycle by Kim et al. (2010) are present in the founding process of the E.nus. The last phase, reassessing and reshaping the partnership, is however missing within this model. In this phase the partnership is reassessed and can be maintained, improved or stopped. During the conduction of the surveys at the E.nus in this research, it became clear that the focus of InstalNova lies on the first three phases of the partnership lifecycle. The reassessing and reshaping phase receives far less attention and this is perceived by the E.nus as a lack of support. The measurement instrument and assessment procedure that is developed in this study is an effort to increase the support InstalNova gives to the E.nus in the last phase of the lifecycle of the partnerships.

20

Part II – Design

Diagnoses

Design

Evaluation

Design of measurement instrument

Conceptualization Development Data collection Statistical analysis Conclusion

Implementation

21 In this chapter the scale development procedure (Churchill, 1979) is used to produce a tool that can measure construction supply chain relationship quality. In the literature framework, a positive relation between partnering and performance was found. The measurement instrument includes the performance outcomes profit, quality and predictability to evaluate the predictive validity of the measuring instrument. The scale development procedure starts with the conceptualization of relationship quality and performance outcomes. The next step is to develop scales for relationship quality. Finally, data is collected at the E.nus and the validity of the measuring instrument is assessed using SPSS.

5.1 Conceptualization

Conceptualization is necessary to establish what is meant by relationship quality and performance outcomes in this research. In the next sections definitions for the constructs relationship quality and performance are given and their dimensions are specified.

5.1.1 Conceptualization of relationship quality

The first construct that has to be conceptualized is relationship quality. Relationship quality is conceptualized as the degree to which parties in a relationship are engaged in an active long-term collaborative relationship (Fynes et al., 2005). In the introduction eight key interrelated dimensions of relationship quality were found in the comprehensive literature study of Meng (2010). Together these dimensions form the construct relationship quality.

However, these key dimensions of relationship quality relate to a partnership between separate clients and main contractors (Meng, 2010), E.nus contain main- and subcontractors and no clients or suppliers. E.nus are founded as stand-alone businesses, which means that there is no procurement within the E.nu and risk allocation is specified when forming the E.nu. Therefore, the dimensions procurement and risk allocation as determined by Meng (2010) are superfluous and are not part of the dimensions of relationship quality in E.nus. The six dimensions of relationship quality that remain are the dimensions of relationship quality in E.nus and are conceptualized in the following paragraphs.

Trust refers to the conviction that every partner will equally contribute to the E.nu (Cullen et al.,

2000). Trust is also considered to be the most important aspect of relationship quality as it is both a prerequisite, as well as an outcome of high relationship quality. Successful cooperation needs trust to relieve tension and enhance adaptability, information exchange and joint problem solving (Yeung et

al, 2007). Successful cooperation in turn generates trust between parties that participated in the

22

Objectives refer to the tension between E.nu objectives and objectives formulated for the Parenting

organizations of the E.nu participants. Beach et al (2005) found that objective alignment is essential for a high relationship quality in the construction supply chain.

Teamwork refers to the attitude that partners in an E.nu display towards each other during

construction. These attitudes mostly arise during the planning phase of a project or when problems during construction arise (Chen and Chen, 2007).

Continuous improvement is conceptualized as joint efforts that are made to improve the building

process. Continuous improvement requires measurement of key performance indicators, stepwise improvement efforts and comparison between key performance indicators of the new and old processes to evaluate the improvement (Smythe, 2010).

Communication is defined as the openness of information within an E.nu. Partners have to learn about

each other‟s uncertainties and abilities in order to generate value (Austin, 2000). Zacharia et al. (2009) state that in order for partners to be more willing to collaborate intensely and openly, they need to have a deep understanding of products, organizational culture, skills, capabilities and business objectives of the organizations in the partnership.

Problem solving refers to the structure that is in place to solve problems that occur during

construction. These conflict resolutions are important for E.nus as the parenting companies will have different characteristics such as way of working and culture (Kim et al, 2010). These differences will eventually lead to conflicts that have to be dealt with in order to prevent the E.nu from falling apart.

5.1.2 Conceptualization of performance outcomes

In order to evaluate the predictive properties of the measuring instrument, the construct performance index is introduced. The performance index has three dimensions that are determined by the general manager of InstalNova. These dimensions are profit, quality and predictability and are all positively related to relationship quality as discovered in the literature framework. In the following paragraphs the dimensions of the performance index are conceptualized.

Profit is an accounting concept and is defined as revenue minus costs. Revenues and costs for partners

in an E.nu are accounted per project, as every project is unique. Profit can then be defined by the following formula:

∑ ( )

( )

Quality is defined as construction to optimal specifications, as E.nus perform the energy performance

advice and they are also responsible for developing the optimal specification for the customer.

23

5.2 Scale development

Content validity is the starting point for developing good measures. Content validity means that the items that measure a construct cover the major content of this construct (Churchill, 1979). The extensive literature of Meng (2010) ensures that the six dimensions cover the major content of the construct relationship quality. As the performance index is only used to evaluate the predictive validity of the measuring instrument, content validity is not an issue for this construct.

5.2.1 Itemization

The scales for the dimensions of relationship quality and performance index were generated using information from an interview with the general manager of the E.nus and by examining the existing literature on construction supply chain collaboration. In appendix II, table 1 an overview of the item statements and the corresponding sources is given.

Each scale is measured by a number of items that should converge. The different scales do not necessarily have to converge, as it is possible that E.nus do not engage in all aspects of relationship quality.

5.2.2 Scaling

In this research the seven point Likert rating scale is chosen as it provides interval data on attitudes (Cooper and Schindler, 2003). It is suited as it enables easy comparing of scores between E.nus. A seven-point scale also means that there are more possible answering choices, which enables more subtlety. While some researchers argue that respondents are not able to make a distinction between points on a seven point Likert scale, Dawes (2008) found that differences in mean, variation about the main, skewness or kurtosis between a five or seven point Likert scale were insignificant.

5.2.3 Pre-pilot testing of the instrument

24

5.2.4 Pilot study

The goal of the pilot study is to assess initial construct validity and reliability of the itemization of the domains of supply chain relationship quality and performance index. Construct validity assesses if the measures for a certain construct are really measuring this construct. Construct reliability is an estimate of the repeatability of the measurement. In this pilot study the Q sort method (Stephenson, 1953) is used which is useful to determine the opinion of subject on a topic and allows a pilot test with a small sample (2 judges).

Moore and Benbasat (1991) proposed the use of the Q sort method as a manual factor sorting technique to assess and improve levels of construct validity and reliability for scales of subjective constructs. Li et al. (2005) also use the Q-sort method and indicate that the degree of agreement between judges can be measured by two evaluation indices: Cohen‟s Kappa (Cohen, 1960) and Moore and Benbasat‟s (1991) Hit Ratio. While Cohen‟s Kappa is strictly a measure of agreement between judges, Moore and Benbasat‟s Hit Ratio is a derivative because it measures the agreement between judges by the notion that a high level implies that judges must have agreed over the placement of the items.

Two construction experts were asked to act as judges for the q-sort method. One is the owner of a large construction group, the other the is the owner of a small main contractor that specializes in cooperative construction. Both are academically educated and experienced in the field of sustainable construction.

The first judgment round resulted in fairly low judge agreement level (Kappa 68,3% and Hit ratio 70,7%). Moore and Benbasat (1991) indicate that there is a recommended level of placement within the constructs of 65%, but argue that the largest contribution of the Hit Ratio is that it provides guiding to which items should be reworked or removed. In order to improve the levels of Kappa and Hit Ratio, feedback was obtained from the judges on the off diagonal items as these items were placed outside the intended dimensions. One item was removed, three added, one shifted to another dimension and all were reworded. Finally, general feedback on the wording of the diagonal items was obtained and used to improve the item statements.

25 sorting round and eventually led a change of one item into the intended dimension by one judge. These levels indicate an excellent level of agreement between judges in the third round and consistency of Cohen‟s Kappa and Moore and Benbasat‟s Hit Ratio across two sorting rounds with the same items. This indicates a high level of construct validity and reliability of the scales that measure the domains of supply chain relationship quality and performance index. In table 1 to 3 of appendix II the result of the sorting rounds is depicted. In appendix III the resulting measurement instrument is presented.

5.4 Data collection

In order to validate the measurement instrument and to obtain measurements of relationship quality in the E.nus, data has to be collected from the E.nus. In the following section the population, data collection method and the response is presented.

5.4.1 Population

Of the twenty-five E.nus, only sixteen have been officially established as an independent corporation. This limits the population to sixteen E.nus, as only established corporations can perform building activities as an E.nu. The other E.nus are somewhere on the path (as shown in chapter 4) of becoming an established E.nu. Contact information on the established E.nu was requested and received from InstalNova. As the measurement instrument is developed to assess relationship quality across E.nus and not to evaluate different attitudes towards relationship quality within an E.nu, only the sixteen leaders of the E.nus were be asked to participate in the research.

5.4.2 Data collection method

26

5.4.3 Response

An email was sent to all sixteen E.nus explaining them the intention of the research and mentioned the involvement of InstalNova. To increase the legitimacy of the research email all mails were carbon copied to the managing director of InstalNova. Seven E.nus responded on this email and were directly called to make an appointment. The remaining nine E.nus were sent a reminder email a week after the first email. Two additional E.nus responded and were called to make an appointment. A week after the reminder email the remaining seven E.nus were called to make an appointment but only four were willing to participate in the research. The other E.nus refused on the basis that they had no time to participate or that the company‟s E.nu contact was on vacation. This resulted in a response rate of 81,25% after three weeks of visitations throughout the entire country. During the visitations it became clear that only six E.nus had actually performed construction works as an E.nu. The downfall of the Dutch construction market as a result of the economic crises was considered to be the most important reason for this by the E.nus. Other reasons included a lack of a track record and the long tendering procedure used by governmental organizations and housing corporations. All E.nus that performed construction works indicated that they only had pilot projects or demonstration projects that they sold at or under cost. For this reason the respondents all filled in very low profit scores. They indicated that these scores do not represent the revenues they expected when they would have their first pilot/demonstration projects completed. For this reason the profit scores are omitted from the rest of this study.

5.5 Statistical analysis

In this section, the validity of the constructs are assessed in order to determine whether the measurement instrument is valid for measuring relationship quality in the E.nus. Content validity assessment is based on the literature research and pre-test. Unidimensionality, reliability and predictive validity are assessed using the SPSS program and the survey data.

5.5.1 Content validity

27 not measure this dimension. Bagozzi and Fornell (1989) propose two tests that establish the unidimensionality of a measuring instrument: Factor analysis and reliability analysis.

5.5.2.1 Factor analysis

Factor analysis assesses if items load on the factors that they are intended to load on. As a rule of thumb the sample size has to be greater than 300 or more than 10 cases per variable. Both conditions are not satisfied as the population consists only of 16 entities and of this population 13 entities were able to respond. Only if one of the following conditions is satisfied the results of the factor analysis can be analyzed.

1. If at least four loadings on a factor are > 0,6 sample size does not matter for that factor 2. Sample size is not very important if Kaiser-Meyer-Olkin measure of sampling adequacy is

large enough (the general interpretation of large is above 0.8).

When all variables are selected for the analysis SPSS gives the warning that “this matrix is not positive definitive” when trying to construct the correlation matrix. According to Anderson and Gerbing (1984) this is due to sampling fluctuation that arises when sample size is small. The result is that the KMO test cannot be run and therefore the second condition is not satisfied. When the component and rotated component matrices are analyzed it can be seen that a only a maximum of 5 factors (instead of the intended 6) have a minimum of 4 factor loadings of at least 0,6 (Appendix V). Factor analysis for the measurement instrument as a whole is therefore not possible due to the small sample size.

Another possibility to assess unidimensionality is to perform a factor analysis on the items of each dimension separately. The goal is to discover if the items load on one factor (the intended construct), or that they load on more factors indicating that they are not only measuring the intended construct but also a construct that has not been conceptualized. The results are displayed in the table 1.

Table 1: Factor analysis results

Variable KMO Number of

-28 Only the variable trust satisfies the first condition by having a KMO score of 0.805. This variable only loads on one factor and therefore the factor analysis strongly indicates that the variable trust is unidimensional.

The variables quality and predictability have no KMO score. As the factor analysis on these variables can only be carried out with over a sample of 6 cases (only 6 E.nus have performed construction projects and were able to answer to these questions) this leads to a not definite positive matrix. The sample is simply too small to carry out the KMO test.

All variables except objectives have more than 4 factor loadings larger than 0.6 on the first factor and less than 4 for the other factors. This leads to an indication that these variables are unidimensional (it‟s not certain as there are other factors with an eigenvalue higher than 1).

As both conditions were not satisfied for the variable objectives it is not possible to carry out a factor analysis on this variable. There is no indication whether or not this variable is unidimensional.

5.5.2.2 Reliability analysis

Cronbach‟s alpha is used to evaluate the reliability of a set of items, as it is a measure of the intercorrelation between these items. Cronbach‟s alpha is an estimate of the squared correlation between the observed test score and an unobserved true score. Cronbach‟s alpha should be above 0.6 for items to be combined in a scale but higher scores are better. In table 3 the Cronbach‟s alphas of all variables, the item to be deleted (if it is possible to improve the reliability) and the new Cronbach‟s alpha are displayed.

Table 2: Reliability analysis

All variables are above 0.6 and can be combined into a scale although objectives just passed the threshold with a score of exact 0.6. It is important to realize that Cronbach‟s alpha is based on the consistency of respondent scores across the items to be included in the scale. The objective scale is constructed on objective alignment and on the distribution of the benefits that result from these objectives. While the benefits might be evenly distributed among the E.nu participants, there might not have been objective alignment as there are no objectives explicitly formulated. In short, the lower Cronbach‟s alpha can indicate that the alignment of goals and the evenly distribution of the benefits of these goals are not as naturally for the E.nus as is predicted by Meng (2010).

Variable Cronbach's alpha Item to be deleted Cronbach's alpha

Trust 0.907 - -Objectives 0.600 - -Teamwork 0.734 - -Communication 0.862 - -Continuous improvement 0.807 - -Problem solving 0.844 -

-Quality 0.535 Discussion on results 0.755

-29 the measuring instrument are in line with the results of other studies. As stated in chapter 2, there should be a positive relation between the dimensions of relationship quality and the outcomes quality and predictability.

As only six E.nus have performed construction works, only very large correlations are significant. This is the case for the relation between objectives - predictability, communications - predictability and problem solving - quality; these are marked green in table 3. The relations communication – predictability and problem solving – quality are quite logical, the relation objectives – predictability is less straightforward. Common objectives and fair sharing of the profits of these objectives increases the predictability of time and cost. One reason can be that common objectives lead to less conflict what in turns results in more open information exchange. This is also supported by a significant 0,824 correlation between these two variables.

All other correlations are not significant as their correlations are not large enough to overcome random chance that exists at six observations (0.707 at the two-tailed 0.05 level). Only three correlations are negative (marked red in table 3) but these three have the lowest significance (above 0.848), indicating that these are most likely to be caused by random chance. All other correlations (marked yellow table 7) are positive but not significant giving an indication that there might be a positive relation but that the sample size is too small to be certain. The overall positive correlations between the dimensions of relationship quality and the outcomes quality and predictability match the conclusions of Egan (2002), Beach et al. (2005), Larson (1995) and Wood and Ellis (2005) and thereby establishing the predictive validity of the constructs.

5.5.6 Statistical analysis conclusion

30

Table 3: Correlations between dimensions and outcomes

Quality Predictability Pearson Correlation -.102 -.013 Sig. (2-tailed) .848 .980 Pearson Correlation .529 .822* Sig. (2-tailed) .281 .045 Pearson Correlation .665 -.031 Sig. (2-tailed) .149 .954 Pearson Correlation .218 .853* Sig. (2-tailed) .679 .031 Pearson Correlation .517 .366 Sig. (2-tailed) .293 .476 Pearson Correlation .953** .700 Sig. (2-tailed) .003 .122 Pearson Correlation 1 .592 Sig. (2-tailed) .215 Pearson Correlation .592 1 Sig. (2-tailed) .215 Continuous Problem Quality Predictibility

*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).

Correlations

Trust

Objectives

Teamwork

31

Diagnoses

Design

Evaluation

Design of measurement instrument

Conceptualization Development Data collection Statistical analysis Conclusion

Implementation

32

6. Implementation of the measurement instrument

In this chapter a method will be presented that will enable measurement, presentation and assessment of relationship quality in the E.nu partnerships.

6.1 Data representation

The measurements used to validate the measuring instrument in chapter 5 provide the initial relationship quality scores for the E.nus. These scores have to be presented in a way that is easy to interpret and be put in perspective by also presenting the average E.nu score and best performing E.nu score.

The representation method has to comply with the following restrictions:

· It must give an overview of the current situation in one diagram

· It must show the different dimension scores

· It must visually demonstrate that higher scores are better

· It must be able to show individual E.nu scores and benchmarking scores in the same diagram A spider diagram is suited as it is able to show multiple dimensions in one diagram, higher scores will result in a larger surface area and benchmarks and E.nu score can be shown in one spider diagram. In figure 7 the average E.nu score, highest E.nu score and lowest E.nu score on the six dimensions of relationship quality are shown. Presenting a score for each of the dimensions allows for easy identification of problem areas. An overview of all E.nu relationship quality scores is only provided to InstalNova as this is sensitive business information.

Figure 6: E.nu scores

33 The scores and representations of these scores in a spider diagram are the starting point of the assessment procedure. E.nu leaders can engage in a discussion based on their relationship quality score with others members of their E.nu. They can discuss if the score represents their own experiences, whether or not they want to improve on all dimensions and if they feel that some dimensions are less urgent for their E.nu. They can then try to improve their relationship quality score on the dimensions they see fit. This procedure can then be repeated after some time (ranging from 6 to 12 months) and the previous scores can then be considered the reference score for evaluation of the relationship quality improvement efforts. In figure 8 the full assessment procedure is depicted.

Initial survey Calculating scores

Score representation Discussion Improvement efforts Survey Goal setting

Figure 7: Assessment procedure

34

Part IV – Evaluation

Diagnoses

Design

Evaluation

Design of measurement instrument

Conceptualization Development Data collection Statistical analysis Conclusion

Implementation

35 The last phase in the regulative cycle is to evaluate the preceding phases. This evaluation starts by a conclusion that answers the main and sub questions stated in the diagnoses phase. In the recommendations an advice on the use of this assessment procedure is given. Finally, in the discussion the strengths and weaknesses of this research are evaluated and recommendations for further research are given.

7.1 Conclusion

In this study the main research question is formulated as:

How can relationship quality be assessed in an E.nu partnership?

In this study a relationship quality measurement instrument was developed that consisted of the following dimensions: Trust, objectives, teamwork, communication, continuous improvement and problem solving..

Using literature and interviews the dimensions of relationship quality were itemized to form measuring scales. The validity of the measurement was assessed on content validity, unidimensionality, reliability and predictive validity. The sampling size inhibited to fully assess all dimensions of relationship quality. The correlations between the six dimensions of relationship quality and the outputs quality and predictability in terms of cost and time confirmed the positive relationship between objectives – predictability, communication – predictability and problem solving – quality that were found in the literature. The very small negative correlation between trust and the outcomes quality and predictability could be explained based on the literature. The designed measurement instrument is valid for measuring relationship quality in E.nu partnerships.

The proposed assessment procedure enables implementation of the measurement instrument in the E.nus. The assessment procedure consists of the following steps: initial survey, calculating scores, score representation, discussion, goal setting, improvement efforts and survey. These steps form a continuous improvement loop that can be run independently by the E.nus or with minor support from InstalNova.

36

7.2 Recommendations

In this section practical recommendations are given on the implementation of the assessment procedure and relationship quality improvement.

7.2.1 Relationship quality assessment implementation recommendations

In the following section recommendations to InstalNova are given for actions they have to undertake in the short- and long-term to implement the assessment procedure for relationship quality.

7.2.1.1 Short-term recommendations

Organizing a meeting with all E.nus will enable the researcher to give feedback to the E.nus on the relationship quality they scored during the assessment procedure. It is important to show why relationship quality is of importance in partnerships, how the measurement instrument is validated, how these scores are calculated and how they can improve their relationship quality scores (7.2.2). Only if the E.nus are convinced that improving relationship quality will lead to tangible benefits, they will expense the time that is needed for the assessment procedure. The goal of this meeting is to create commitment for relationship quality assessment.

The next step is to create a contact within InstalNova to support the assessment procedure. This person will be responsible for the surveys and will handle the processing and representation of the relationship quality scores. He or she will provide the feedback to the E.nus, moderate the discussions within the E.nus and facilitate the transfer of knowledge to improve relationship quality. Finally, this person has to record the goals that an E.nu has set and plan the next measuring round.

7.2.1.2 Long-term recommendations

Firstly, the item statements in the measurement instrument that are developed in this study are greatly based on construction supply chain literature. By receiving feedback from the E.nus it is possible to adapt the instrument to the changing environment where it is used for measurements. New problems will arise as E.nus age and become more mature and current problems might not be important in the future. The measurement instrument remains relevant by adapting it to the relationship quality needs of the future.

37 recommendations are ordered per relationship quality dimension.

7.2.2.1 Trust

Trust is considered to be the most important prerequisite for partnering in the construction supply chain. The high mean of trust in the results of the performed survey can be an indication that this is indeed the case. Beach et al. (2005) indicate that successful cooperation generates trust between parties that participated in the cooperation.

Sako (1992) identifies three forms of trust: contractual trust, competence trust and goodwill trust. Contractual trust means that parties believe that their partners behave as bespoke in an oral or written agreement. Competence trust is a higher level of trust and is grounded in the conviction that the other is capable in performing their tasks. Goodwill trust is the highest level of trust and means that parties will perform beneficial actions that are beyond expectation of the other party. Trust can also be expressed as the extent to which parties monitor partners or their confidence in the reliability of shared information or good behavior (Meng, 2010).

Monitoring of partners and the confidence in the reliability of shared information are lagging indicators and cannot be directly influenced by the E.nu participants. However, E.nu participants can influence the type of trust by completing their respective tasks and performing unexpected beneficial actions towards other E.nu participants.

7.2.2.2 Objectives

Beach et al. (2005) found that objective alignment is essential for a high relationship quality in the construction supply chain. As E.nu partners are also member of their parenting organization it is critical that they will pursue goals from both organizations. Mutual objectives that are beneficial for both the E.nu and the partnering organizations enable such a pursuit. The benefits that are created in pursuing the mutual objectives have to be divided between the partners in the E.nu in a fair way. Meng (2010) typifies high quality relationships by having a win/win business principle instead of leaching or squeezing profits from the E.nu toward the respective parenting companies of the participants. Win/win business principles can be enforced by openness of information and clear common goals.

Beach et al. (2005) proposed workshops to secure commitment to mutual objectives. Combined with openness of information these mutual objectives will ensure that parenting companies will try to upsell sustainable construction works towards the E.nu when possible.

7.2.2.3 Teamwork

38 lies on problem solving instead of finding out who is to blame, which is common in the construction industry (Meng, 2010). When there is a problem solving culture in an E.nu, parties will help each other if they run into problems during the construction process. There should be some conflict or else this may imply that mutual influence is compromised or non-existent and thereby reducing the benefits that arise from partnering (Brinkerhoff, 2002).

7.2.2.4 Communication

According to Tuten and Urban (2001), communication has several critical functions that have to be present for a partnership to be successful. These functions are: assisting in establishing performance requirements, adapt to changes in partner expectations, avoid political conflicts and to reduce the level of uncertainty. There are several ways to create an environment for open communication. Lau et al. (2002) propose the installment of a shared information system, Maheshwari et al. (2006) favor workshops to adjust cultural differences and Motwani et al. (1998) stress the importance of providing a feedback process.

7.2.2.5 Continuous improvement

Continuous improvement is a form of innovation that emphasizes many small incremental improvements devised by the workers instead of giant leaps thought of by R&D facilities or management. Most continuous improvement implementations are based on the Kaizen concept from Japan, and was described in the book “Kaizen: The Key to Japan‟s Competitive Succes” by Imai (1986). Imai (1986) states that the goal of continuous improvements is to identify, reduce and eliminate less than optimal processes. This is the same as the lean principle of reducing waste by eliminating non-value adding processes.

The principle of continuous improvement is reflection, and thus feedback, on processes. In order to be able to continuously improve the construction processes in the E.nus, there have to be performance measures in place for monitoring and providing feedback to all participants of the E.nu. Additionally, it is recommended that there is some form of incentive mechanism that encourages participants to try to improve the processes.

7.2.2.6 Problem solving

Traditionally, the construction supply chain has employed conflict resolution approaches such as domination and coercion (Maheshwari et al., 2006). Joint problem solving is seen as a better conflict resolution technique as it does not have the negative impacts, such as a lower level of communication and trust, like the more traditional approaches (Kim et al, 2010).

39 discussed and recommendations for further research are given.

7.3.1 Strengths

The first strength of this research is that it provides a way to measure collaboration in the E.nus to InstalNova. Hard data is often not available in SMEs and if it is present, these data are mostly lagging indicators in the construction industry (e.g. profit, building time). Using the dimensions of relationship quality, InstalNova can focus on leading indicators that will increase E.nu performance.

The E.nu concept has been devised and implemented on a gut feeling. This research has identified it as a supply chain partnership, which enables the application of research that has been carried out in this field.

This research has produced an easy to implement assessment procedure and provided guidance towards improving relationship quality. By providing measurements this research encourages E.nus to discuss the relationships with their partners and to do this in a continuous way.

7.3.2 Weaknesses

When a student writes a master thesis there is always tension between the more practical perspective of the client and the more scientific perspective of the University. In the beginning of the writing process I aimed at completing this thesis with both practical and scientific results. During the research it became clear that the small population would inhibit my intention of establishing clear and significant correlations between the dimensions of relationship quality and the outcomes in terms of costs, quality and predictability of the building process. In my opinion this is, and remains, a big gap in the current research into partnering in the construction supply chain.

I intended to validate the measurement instrument as thoroughly as possible. Due to the population and thereby the sample size, assessing unidimensionality was not possible by a regular factor analysis. Additionally, convergent and discriminant validity could not be assessed because the chi-square statistic is very sensitive for small sample sizes (Li et al. 2010).

The predictive validity of the measurement instrument was only assessed over 6 cases, as the other E.nus had not performed any construction works at all. This resulted in a correlation matrix that showed only 3 (positive) relations that were significant. The outcome profit could not be assessed at all as only pilot projects had been completed.

7.3.3 Recommendations for further research

40 guide construction supply chain organizations in its improvement efforts to create a supply chain that is ready for the future.