A RESEARCH SYNTHESIS OF KEY PARTNERING DRIVERS AND PERFORMANCE OUTCOMES IN ARCHITECTURE, ENGINEERING, AND CONSTRUCTION RESEARCH By Anthony Elijah Sparkling A THESIS Submitted to Michigan State University in partial fulfillment of the requirem ents for the degree of Construction Management - Master of Science 2014 ABSTRAC T A RESEARCH SYNTHESIS OF KEY PARTNERING DRIVERS AND PERFORMANCE OUTCOMES IN ARCHITECTURE, ENGINEERING, AND CONSTRUCTION RESEARCH By Anthony Elijah Sparkling There has been over two decades of research investigating partnering within the Architecture, Engineering, and Construction (AEC) industry. The concept was developed in the 1980s by the US Army Corp of Engineers to mitigate the rise in construction disputes and its dama ge to business relationships (Gransberg et al. , 1999). Much of this research has been centered on Black et al., 2000; Cheng et al., 2000 ) or report performance outcomes ( Ander son & Polkinghorn, 2011 ) for partnering often leaving researchers and practitioners in a state of confusion . Many of these studies l ack clear direction to propel the concept forward . As such, some have resorted to detailed literature reviews through qualitative approaches intended to summarize the status of partnering research . A meta - analytic approach is used for t his research to synthesize 173 studies from AE C partnering literature. Findings from this study achieves several goals established for this research being: 1) synthesize the body of knowledge in AEC partnering literature; 2) develop a proposed taxonomy of key partnering drivers (KPD) and performance o utcome s with preliminary quantitative evidence from the AEC partnering literature . The results will provide theoretical underpinnings of AEC partnering literature making a contribution to broader organizational knowledge and theory. In fact, t his research closes the gap in the literature illustrating a clear connection between key partnering drivers and performance outcomes using a systematically derived taxonomy. Copyright by ANTHONY ELIJAH SPARKLING 2014 iv ACKNOWLEDGEMENTS First and f oremost, I would like to thank God for giving me the strength, courage, and resolve to see the end result of two years of hard work and perseverance. The thesis would not have been possible without the kind support, encouragemen t, direction, and guidance of my academic advisor Dr. Sinem Mollaoglu - Korkmaz. From the day I arrived on campus you showed overwhelming trust and confidence in my ability to succeed. For this I owe my sincere gratitude. Next, to my committee members Dr. Ma tt Syal and Dr. Ahmet Kirca, I say thank you for lending your guidance and inspiration for this research . Dr. Syal over the course of two years I have had the pleasure of studying and learning from your vast experience for which I am truly grateful. To all of the other faculty and professors that I have enjoyed working with I say thank you. In particular, I want to thank Professor Timothy Mrozowski for the open door when I needed someone to offer a different perspective. To my research cohorts whom offered the much needed laughter, while also being there for encouragement and support I say thanks. I would also be remiss without mentioning the guidance and support of the Inte rnational Partnering Institute for this research. And finally, I chose to save the be st for last, my family to which I am forever indebted for graciously allowing me to endeavor on this new journey. To my loving wife, Pamela Sparkling, I say thank you for all the belief, kind words of encouragement, and trusting in me when the road ahead d id not always seem clear. I love you dearly. To my daughters, Brooklyn and Treasure, I only pray that someday you will know that all I do is for my family, despite all the sacrifices you have endured along this journey . My hope is v that I continue to lay a great foundation for the both of you. To my parents, I know you are proud me for all the doors I continue to break down and I love you for it . vi TABLE OF CONTENTS LIST OF TABLES ................................ ................................ ................................ .............................. viii LIST OF FIGURES ................................ ................................ ................................ .............................. ix CHAPTER 1 INTRODUCTION ................................ ................................ ................................ ............ 1 1.1. Overview ................................ ................................ ................................ .......................... 1 1.2. Background ................................ ................................ ................................ ....................... 4 1.3. Problem Statement ................................ ................................ ................................ .......... 5 1.4. Description of the Research ................................ ................................ ............................. 5 1.4.1. Research Scope ................................ ................................ ................................ ......... 5 1.4.2. Deliverables ................................ ................................ ................................ ............... 8 1.5. Readers Guide ................................ ................................ ................................ .................. 8 CHAPTER 2 LITERATURE REVIEW ................................ ................................ ................................ .... 9 2.1. History of Partnering ................................ ................................ ................................ ........ 9 2.1.1. Partnering A cross Industries ................................ ................................ ..................... 9 2.1.2. Partnering In the AEC Industry ................................ ................................ ............... 11 2.2. Partnering Types ................................ ................................ ................................ ............ 12 2.2.1. Characteristics of Partnering ................................ ................................ .................. 13 2.2.2. Partnering and Project Performance Outcomes ................................ .................... 16 2.2.3. Partnering Knowledge in the AEC Industry and Barriers to Its Implementation .... 1 7 2.3. Preliminary Review of Partnering Framework ................................ ............................... 22 2.3.1. Key Partnering Drivers ................................ ................................ ............................ 22 2.3.2. External Moderator ................................ ................................ ................................ 23 2.3.3. Project Performance Outcomes ................................ ................................ ............. 24 2.3.4. Organizational Performance Outcomes ................................ ................................ . 24 CHAPTER 3 RESEARCH METHODOLOGY ................................ ................................ ....................... 26 3.1. Research Strategy ................................ ................................ ................................ ........... 26 3.2. Meta - Analysis: A Scientific Method to Explore New Paradigms via Existing Research . 28 3.2.1. Benefits of Meta - Analysis ................................ ................................ ....................... 30 3.2.2. Use of Meta - Analysis and Directions from the Literature ................................ ...... 32 3.3. Data Collection and Screening ................................ ................................ ....................... 33 3.4. Data Coding Criteria ................................ ................................ ................................ ....... 37 3.4.1. Data Coding Form Development ................................ ................................ ............ 37 3.4.2. Data Quality and Validi ty ................................ ................................ ........................ 41 3.5. Hypothesis for Partnering Framework ................................ ................................ ........... 42 3.6. Interpreting Results and Discussion ................................ ................................ ............... 43 3.7. Summary ................................ ................................ ................................ ........................ 44 vii CHAPTER 4 FINDINGS ................................ ................................ ................................ .................... 45 4.1. Research Synthesis of Partnering Study Characteristics ................................ ................ 45 4.2. Research Synthesis of Partnering Drivers and Consequences ................................ ....... 53 4.2.1. Statistical Analysis of Key Partnering Drivers and Perform ance Outcomes ........... 58 4.3. Partnering Construct Development and Taxonomy ................................ ...................... 63 4.3.1. Key Partnering Driver Construct Development ................................ ...................... 64 4.3.2. Performance Outcome Construct Development ................................ .................... 70 4.4. Summary ................................ ................................ ................................ ........................ 73 CHAP TER 5 SUMMARY AND CONCLUSIONS ................................ ................................ ................. 74 5.1. Summary of the Results ................................ ................................ ................................ . 74 5.2. Partnering Framework ................................ ................................ ................................ ... 77 5.3. Theoretical Implication and Practical Application ................................ ......................... 80 5.4. Limitations and Recommendations for Future Research ................................ .............. 81 5.4.1. Limitations ................................ ................................ ................................ ............... 81 5.4.2. Recommendations for Future Research ................................ ................................ . 83 5.5. Conclusion ................................ ................................ ................................ ...................... 84 APPENDICES ................................ ................................ ................................ ................................ .. 86 APPENDIX A: PARTNERING STUDIES RESULTING FROM DATA COLLECTION AND SCREENING. ... 87 AP PENDIX B: PARTNERING RESEARCH CODING FORM. ................................ ............................. 100 APPENDIX C: PARTNERING CODING MANUAL ................................ ................................ ............ 102 APPENDIX D: KEY PARTNERING DRIVER CONSTRUC TS AND VARIABLES ................................ .... 107 APPENDIX E: EXTERNAL MODERATOR CONSTRUCT AND VARIABLES ................................ ........ 111 APPENDIX F: PERFORMANCE OUTCOME CONSTRUCTS AND VAR IABLES ................................ .. 112 REFERENCES ................................ ................................ ................................ ................................ 116 viii LIST OF TABLES Table 1: Snapshot of Final List of Partnering Studies as a Result of this Study (Full List of 173 Studies provided in Appendix A). ................................ ................................ ................................ .. 35 Table 2: Partnering Publication Sources Identified in AEC Literature and Number of Studies. ... 36 Table 3: Partnering Key Codes used during Study Coding (Detailed Description provided in Appendix C) ................................ ................................ ................................ ................................ ... 39 Table 4: Sample List of Key Partnering Driver Construct and Variables. (Full List provided in Appendix D) ................................ ................................ ................................ ................................ ... 41 Table 5: Partnering Constructs and Variables in AEC Literature. ................................ ................. 54 Table 6: Top Three Attributes for Each Partnering Construct in AEC Literature. ......................... 55 Table 7: Taxonomy of Partnering in AEC Literature. ................................ ................................ .... 57 Table 8: Key Partnering Driver Category Validation ................................ ................................ ..... 60 Table 9: Performance Outcomes Categorization Validation ................................ ........................ 61 Table 10: S napshot of Performance Outcome Constructs and Variables (Full List provided in Appendix F). ................................ ................................ ................................ ................................ .. 62 Table 11: Taxonomy of Partnering Constructs and Associated Definition. ................................ .. 64 Table 12: Ranking of Top Key Partnering Drivers in AEC Literature. ................................ ............ 76 Table 13: Top Performance Outcomes in AEC Partnering Literature. ................................ .......... 77 Table 14: Partnering Studies Resulting from Data Collection and Screening sorted by Source of Publication. ................................ ................................ ................................ ................................ ... 87 Table 15: Key Partnering Driver Cons tructs and Variables. ................................ ........................ 107 Table 16: External Moderator Construct and Variables. ................................ ............................ 111 Table 17: Performance Outcome Constructs and Variables. ................................ ..................... 112 ix LIST OF FIGURES Figure 1: Conceptual Model of Partnering Developed Based on Cheng (2000) and Crowley & Karim (1995). ................................ ................................ ................................ ................................ . 14 Figure 2: Research steps followed in this study. ................................ ................................ .......... 28 Figure 3: AEC Partnering Research Trends shown in Five Year Periods. ................................ ...... 46 Figure 4: Partnering Studies in AEC Literature shown by Five Year Periods. ............................... 47 Figure 5: Partnering Research in AEC Literature by Study Type and Number of Studies. ........... 49 Figure 6: Partnering Research in AEC Literature shown by Country. ................................ ........... 51 Figure 7: Partnering Studies by Country and Five Year Period. ................................ .................... 52 Figure 8: Stages of Construction Partnering and Associated Constructs. ................................ .... 69 Figure 9: Framework Developed to Understand AEC Part nering Literature. ............................... 79 Figure 10: Partnering Research Coding Form. ................................ ................................ ............ 100 Figure 11: Partnering Coding Manual. ................................ ................................ ........................ 102 1 CHAPTER 1 INTRODUCTION 1.1. Overview In the Architecture, Engineering, and Construction (AEC) industry individuals and organizations coalesce around a specific project aiming to satisfy project performance goals and objectives. Effective commun ication, trust, and knowledge sharing are imperative to meet these project performance expectations. In this endeavor, traditional project goals such as cost, schedule, and quality controls are important project performance measures ( Yeung , Chan, & Chan, 2 009 ; Cheng, Li, & Love , 2000 ). Yet, as projects become more complex and face greater uncertainties the need to achieve higher levels of performance is required of construc tion project teams (Solis, Sinfield, & Abraham , 2013). These teams, in the AEC indust ry, are commonly involved in projects such as heavy infrastructure, healthcare, transportation, or oilfield construction projects which requ ire greater performance efforts (Barlow, 2000; Losada, 1999; Katzenbach & Smith, 1993). In particular, they need to place team performance above their own individual performance objectives. Partnering in the AEC industry presents the opportunity to learn how loosely coupled interorganizational project teams (e.g., owner, designer, and contractors) not only enhance proj ect level performance outcomes, but, overall team collaboration and intraorganizational objectives. Research on partnering has existed for two decades or more reporting many benefits, barriers, and dilemmas, yet, consistently misses the implications across study findings. The research commonly examines different phases of AEC partnering being: project initiation and planning, design, delivery, and completion. These various stages of the construction 2 process provide access to a plethora of both objective and subjective data offering great insight into partnering characteristics . Many of these are perceived as critical to reach partnering project success. Additionally, information becomes available through partnering project performance metrics used to link pr oject performance, process performance, or organizational level performance outcomes to partnering implementation. The literature on partnering is saturated with studies identifying factors that are posited as critical drivers of success in partnered proje ct implementation and their impact on project performance outcomes. The factors include but are not limited to: quality specifications and engineering design, effective partnering workshops and facilitation, neutral third party facilitator, continuous part nering monitoring, commitment to partnering concept, respect among participants, and project visibility (Rogge, Griffith, & Hutchins , 2002). Further identified factors elicited through studies are: adequate resources, mutual trust, long - term commitment of the participants involved, coordination, effective support of senior management, clear lines of responsibility and roles, and creativity in problem solving spawned through enhanced collaborations present in partnering ( Fisher, 2004 ; Black, Akintoye, & Fitz gerald , 2000; Cheng et al., 2000 ). In many of these types of analyses researchers are able to report quantitative results through factor analysis techniques or other statistical inference methods. Though important, this research aims to synthesize a larger body of evidence and provide broader implications in organizational theory. A better understanding of partnering r esearch, through a meta - analytic approach , opens the possibility to explore links between critical drivers of partnering and its consequences on 3 project performance outcomes. Within the international business literature a similar case is presented by directing future researcher s in meta - analysis use as a valid research methodology. Other researchers have made use of meta - analyses in psychology to links personality traits to overall job satisfaction (Judge, Heller, & Mount, 2002) and in the AEC industry to explore issues surrounding construction industry injuries and interventions (Lehtola et al., 2008). In many of these analyses there are many b enefits offered; however, few meta - analytic studies exist in AEC research. As such, an opportunity is present to suggest the practically of meta - analysis as a research methodology to AEC industry researchers. Applications of meta - analytic research in other fields such as marketing provide d inspira tion and provide guidance to this study (Kirca & Yaprak, 2010). In particular, they help provid e for an improved review and synthesis of partnering studies in the AEC field. The purpose of this research is to satis fy the following objectives. First, this research will thoroughly examine the broad AEC partnering literature and use a meta - analytic approach to synthesize and strengthen the partnering body of knowledge. Second, the research synthesis will identify the b oundary conditions of AEC partnering literature and develop a proposed taxonomy of key partnering attributes. Next, this research aims to contribute to broader knowledge of team integration within interorganizational project teams by illuminating theoretic al underpinnings from 25 years of AEC partnering research in literature. Last, links are shown between key partnering drivers (KPD) and performance outcomes using evidence from the literature. 4 1.2. Background There has been over two decades of research invest igating partnering within AEC industry. Many of these studies provide insight into partnering, a construction methodology that lags behind other traditional methods involved in construction project delivery. Partnering has found its way into many construct ion industries throughout the world and reports numerous benefits in project performance (Hong, Chan, Chan, & Yeung, 2012) . Despite significant advantages offered through partnering implementation, it remains underutilized. The US Army Corp of Engineers d eveloped the partnering concept in the 1980s to mitigate the rise in construction disputes and its damage to business relationships (Gransberg, Dillon, Reynolds, & Boyd, 1999) . Studies investigating partnering report many benefits (Anderson & Polkinghorn, 2011; Bubshait, 2001 ; Black et al., 2000 ) and success variables (Chen & Chen, 2007; Chan, Chan, Chiang, Tang, Chan, & Ho, 2004; Chan, Chan, & Ho , 2003; Cheng et al. , 2000) addressing prescriptive problems found during partnering implementation. In some the se analyses researchers maintain cost growth and construction schedules are improved throu gh partnering (Gransberg, Dillon, Reynolds, & Boyd , 1999). Moreover, additional benefits are improved conflict resolution strategies, improved collaboration, stronger relationships and increased trust among project participants (Anderson & Polkinghorn, 2011) . Though not respondents as reported by an Engineering News Record (ENR) survey in 2011 (Tuchman, 2011). Partnering research, over the decades, has served to shed light to the limited application of its use in the AEC industry. 5 1.3. Problem Statement Research over the years group partnering studies according to key partnering drivers (KPD) to formulate study constructs (Beach, Webster, & Campbell, 2005) or present literature reviews through qualitative approaches ( Hong, Chan, Chan, & J. Yeung, 2012 ; Bygballe, Jahre, & Sward, 2010 ; Li , Cheng, & Love, 2000 ) , yet , few attempts are made to synthesize their findings using quantitative methods (Olds, Moskal, & Miller, 2005). A gap in the literature exists illustrating a clear connection between key partnering drivers (KPD) and perf ormance outcomes using a systematically derived taxonomy. 1.4. Description of t he Research This research primarily intends to fill this gap and will use a meta - analytic data collection approach to meet the following objectives 1) synthesize the body of knowled ge in AEC partnering literature; 2) develop a proposed taxonomy of key partnering drivers (KPD) and performance outcome s with preliminary quantitative evidence from the AEC partnering literature . The results will provide theoretical underpinnings of AEC pa rtnering literature making a contribution to broader organizational knowledge and theory. 1.4.1. Research Scope The literature guiding this research is mainly empirical research concerning both qualitative case studies and quantitative investigations. Yin (2003) maintains research methods such as cross - case syntheses are most appropriate to investigate single or multiple cases studies. In cross - case syntheses, the aim is to aggregate findings across studies through word data tables used to develop patterns and mak e conclusions through argumentative interpretation (Yin, 6 2003). Another research method, content analysis, is conducive to both qualitative and quantitative research. Similar to cross - case synthesis, content analysis is used primarily to produce objective, systematic, though quantitative descriptions stemming from communications (Krippendorff, 2012; Kassarjian, 1977). Despite their potential, larger data sets are better suited to other research synthesis methods such as meta - analysis which allow for numeric interpretations in final analyses and conclusions (Cooper et al., 2009; Yin, 2003; Lipsey & Wilson, 2001). Additionally, this research does not aim to examine communication occurrences within cases or research studies, but to analyze and aggregate their f indings. The primary intent for this research is to extensively review AEC partnering literature, combine salient attributes informing partnering project success, and show links between performance outcomes. To do this, a meta - analy tic research synthesis i s conducted examining approximately 25 years of partnering research in the United States (US) and other countries such as the United Kingdom (UK), Australia (AU), and Hong Kong (HK). A meta - analysis allows researchers to summarize, integrate, and interpret findings into one informative study (Lipsey & Wilson, 2000). The purpose is to aggregate as many high quality studies reporting both qualitative and quantitative results stemming from empirical research. The focal points of this research are project part nering studies conducted across multiple countries brought together through a comprehensive literature review. The primary motivation for this is to capture studies published in top construction management journals and other scholarly sources over the past 25 years of partnering research (Hong et al., 2012; Chau Kwong, 1997). A concern within this research is partnering attributes and performance outcomes are 7 frequently reported qualitatively, which is not conducive to a thorough meta - analysis. Despite this , the analysis will report both qualitative findings resulting from the initial search of AEC partnering literature and quantitative results using a meta - analytic approach. As a result of the meta - analysis, outcomes of this study will part from tradition al partnering research efforts and establish a sound justification connecting key partnering drivers and implications on performance outcomes as reported throughout the literature. Although useful, practitioners perplexed (Chan et al., 2004; Cheng et al., 2002; Black et al., 2000; Cheng et al., 2000). In that, clear direction on partnering antecedents and performance impacts remains elusive for those seeking to con centrate efforts in partnering practice and research. Conclusions derived through exhaustive investigations required in meta - analysis, are not without limitations. It is therefore acknowledged that results are not meant to cover the entire field of partne ring literature diverging across industries. Despite this limitation, prominent sources in AEC literature are scoured to produce results which are validated and developed through a sound methodology consistent with meta - analysis literature. The intention t o limit studies to top construction management journals and other key sources entailing robust studies is to help eliminate erroneous results which may surface when broader methodological criteria are established when selecting studies. Although this may l imit the generalizability of this study, unreliable studies are also avoided providing even greater validity in study results ( Cooper, Hedges, & Valentine, 2009 ; Lipsey, M & Wilson, D., 2001 ). 8 1.4.2. Deliverables Deliverables resulting from this study are: 1. Evid ence based guidance to AEC partnering researchers and practitioners as to links between key partnering drivers and performance outcomes through both qualitative and quantitative findings . 2. A theoretical contribution to knowledge within interorganizational project teams. 3. Future guidance to researchers regarding th e applicability of meta - analytic approaches in AEC research. 1.5. Readers Guide A literature review on partnering in AEC industry is conducted and resides in Chapter 2. This is followed by Chapter 3 whi ch describes the research methodology, including strategy and development of the meta - analytic research approach ascribed to meet research objectives and goals as presented. The partnering taxonomy development and coding str ategy are presented in Chapter 4 , along with findings as a result of research synthesis condu cted for this study. The final chapter, Chapter 5, provides a summary of the results . It also offers final conclusions, contributions to the AEC field and body of knowledge, along with limitation s and recommendations for future research, respectively. 9 CHAPTER 2 LITERATURE REVIEW 2.1. History o f Partnering The concept of Total Quality Management (TQM) as a sound business management practice in the AEC industry planted the seeds necessary for the emer gence of partnering (U.S. Army Corps of Engineers, 2010). Although this concept appeared in the 1980s AEC industry, it is not a unique practice. Partnering has existed in many formats and across multiple industries such as automotive, telecommunications, e ducation, and business management in general. To understand the history of partnering it is, therefore, important to explore other instances where partnering has shown its applicability and presented challenges. 2.1.1. Partnering Across Industries As businesse s attempt to gain competitive advantages while controlling costs and quality, many resort to partnering ( Mentzer, Min, & Zacharia, 2000 ; Hagedoorn, 1996; Lambe rt, Emmelhainz, & Gardner, 1996 ) . To understand the significance and history of partnering it is useful to briefly review its use w ithin other industries outside of the AEC industry. Industries such as technology, automotive, and public - private partnerships, to name a few, have successfully engaged in the partnering concept and are discussed next. In the technology industry this strategy is undertaken for several reasons, namely to share in research and development (R&D) activities with other companies and to gain greater access to new market opportunities (Hagedoorn, 1996). Within the business sector this inter - company strategic partnering arrangement is often maintained through joint ventures or established in R&D contracts. Often times these agreements are formulated among large companies which 10 dominate their respective industries. For example, Micr osoft entered a joint venture with a smaller Japanese company Mitsui in 1987 to develop microprocessors (Hagedoorn, 1996). This and other joint ventures are found across the landscape and all seek to effectively leverage their internal abilities with that of identified partners to benefit both parties. The rich history of partnering is further evinced in business supply chain management. The automotive and telecommunication industries are among the best examples of supply chain partnering use. In particula r, companies such as Toyota and G eneral M otors (GM) use supplier partnering to improve cost, process, and deliver better quality and performance to their customers (Brennan, 1997) . Other perceived advantages of supply chain management are joint - problem so lving and information sharing, which are synonymous with AEC partnering goals. Though this type of partnering is beneficial, it is not without pitfalls. Brennan (1997) identified some common hurdles as: large financial investments in the company alignment process (e.g. facilities and equipment), over reliance on partner for continual business, and business stagnation or complacency resulting in missed opportunities for new markets. Supply chain partnering juxtaposed with AEC partnering show many parallels which are examined later. Nevertheless, it is critical to identify several partnering antecedents and implementation factors present within the retailing industry suggested by (Mentzer, et al., 2000) . For example, Mentzer et al., (2000) posit interdepende nce, conflict resolution, trust, commitment, organizational compatibility, and top management vision as antecedents required to effectively implement partnering. They further contend, that proper implementation is maintained through information sharing, te chnology use, establishing strategic interface teams, 11 addressing organizational barriers, maintaining joint programs, understanding asset specificity, and establishing joint performance measures. While examining these factors it becomes evident that multip le industries suffer from similar concerns when deciding to partner and with effective partnering implementation. A final area where partnering has existed is within public - private partnerships. This area concerning partnering tends to reside in public po licy initiatives where parties attempt to join for - profit sectors with public organizations or institution. In many of these partnering arrangements the aim is to increase efficiencies and budgetary constraints by leveraging private sector resources (Mazou z, Facal, & Viola, 2008) . This type of partnering even persists in education, for example, charter schools commonly partner with local non - for profit or private entities to supplement resource needs (Smith & Wohlstetter, 2006) . Smith and Wohlstetter (2006) maintain public - private partnerships in this format can exist either through formal or informal agreements depending on the level trust among the parties. Moreover, the public - private partnerships offer mutuality in resources such as financial, human, phy sical, or to ensure organizational needs of either party are met. With these various industry perspectives in mind, it is important to understand the evolution of partnering in the AEC industry. In addition, a noticeable theme is present in the commonalit ies within each industry especially how partnering is developed and implemented. 2.1.2. Partnering In t he AEC Industry 12 Partnering has taken on many meaning across industries. Therefore, the CII Partnering Task Force defines partnering - term commitment between two or more organizations economic conditions ushering in new business improvement strategies (CII, 1989). As a consequence, partnering in the AEC industry is suggested to have developed during this period as a strategy to help businesses address these economic challenges working jointly toward common goals and objectives, while spreading risks equally among participants. As partnering implementation blossomed defining characteristics and variations in its use began to develop. 2.2. Partnering Types Partnering is typically provided in several variations (i.e., project partnering and strategic partnering ) and can be followed under any project delivery method or can stand alone contractually (Lahdenperä, 2012; Loraine, 1993) . The goals for many project stakeholders (i.e., owners, archite cts, engineers, and contractors) are to deliver high quality projects on time and under budget (Anderson & Polkinghorn, 2011) . With this motivation in mind, project stakeholders often rely on the contract to provide direction to the team. In addition, incr easing team collaboration and communication is attributed to project performance outcomes. Partnering is frequently posited as beneficial to achieve these goals. Though not the most common partnering type, strategic partnering offers clients and other key stakeholders the best chance to overcome high risk and uncertainty in external environments 13 (Bennett & Peace, 2006; Barlow et al. 2000). This is partly due to the longer durations involved in the project delivery process. A contractual partnership is also established in this format between organizations and can be followed across multiple projects or on a single project. Therefore, strategic partnering provides a cooperative environment to deal with concerns in s, and perceptions all stemming from trust. 2.2.1. Characteristic s of Partnering As organizations works to foster collaborative environments through use of partnering , several prominent characteristics are present. These characteristics are found within the part nering structure that develops during partnering initiation and implementation. Several attributes of partnering such as mutual trust, shared vision, long - term commitment, dedication to common goals, equal expectations and values are commonly reported as t he foundation of partnering ( Crowley & Karim, 1995 ; CII, 1989 ). Though the aforementioned attributes are not an exhaustive, many researchers begin with these partnering characteristics which are further displayed through a conceptual model. A conceptual m odel is beneficial to understand how partnering organizations operate within shared boundaries to meet the project specific objectives. The model in Figure 2 - 1 depicts three partnering project organizations. The organizations in this case are represented a s owner/client, designer, and contractor. The partnering boundary develops among the project participants. From this, Crowley and Karim (1995) posit that a semi - permeable boundary exists 14 within the partnering structure. This semi - permeable boundary allows partnering stakeholders Figure 1 : Conceptual Model of Partnering Developed Based on Cheng (2000) and Crowley & Karim (1995). to share knowledge, resources, and exchange p roject specific information. The letters D, E, F, G, H, a nd I situated along the partnering boundary represent individuals either working at the interorganizational level (G, H, I) or the intraorganizational level (D, E, F). In this format, partnering participants are also able to provide innovative problem solv ing ideas to address issues quickly and effectively when they share contiguous organizational boundaries. The arrangement also affords organizations the ability to mitigate confidential or sensitive information from leaking between organizations. Partner ing boundaries, in particular the semi - permeable boundary represents a project network and takes on similar characteri stics of h igh p erformance t eams (HPT) . In the analysis of Chinowsky et al. (2010) several project network characteristics are identified a s necessary for HPTs and are categorized as mechanics (i.e., information and knowledge exchanges between 15 actors) and dynamics (i.e., motivation for individuals or actors to achieve high performance). The mechanics in partnering occurs at both the interorga nizational project level and intraorganizational level. Contention among several authors suggests these factors as critical to determine whether an organization can achieve high levels of knowledge sharing at the intraorganizational level analysis (Chinows ky et al., 2010), across geographical boundaries existing within intra - organizations (Javernick - Will, 2011), and at the interorganizational project level ( Zhang & Ng, 2013 ; Solis et al., 2013; Chinowsky et al., 2011; Chinowsky et al., 2008). Key interactio n components confounding communication and knowledge exchanges stem from the underlying network structure in that ease of knowledge transfers is dependent on the tie strength between individuals and the type of knowledge exchanged ( Reagans & McEvily, 2003 ; Hansen, 1999 ). In this assessment, strong ties (i.e., closely connected and frequent interactions) in knowledge exchanges are not always correlated with effective performance, rather weak ties (i.e., distant and infrequent interaction) can also afford acc ess to tacit knowledge so long as it is easily codified ( Reagans & McEvily, 2003 ; Hansen, 1999; Granovetter, 1973). While this is true, explicit knowledge is reported as best transmitted through non - redundant weak ties (Bresnen et al., 2003; Hansen, 1999). Tacit knowledge may involve information learned from working with the client on previous projects. Moreover, if the tacit knowledge or information is complex, such as a new construction method or a constructability problem encountered, the weak tie is les s beneficial. Reagan and McEvily (2003) and Bresnen et al. (2003) further argue knowledge 16 transfers are best when project team members share knowledge in common or mental models as a result of their individual attributes (i.e., same discipline, same cohor t, etc.). 2.2.2. Partnering a nd Project Performance Outcomes The success of partnering is illuminated across many studies in AEC literature. At the project level researchers have investigated partnering implications on transportation and bridge projects (Ander son & Polkinghorn, 2011; Gransberg et al., 1999). Other research, again, directs attention on perceptions of those with extensive partnering experience ( Chan et al., 2004; Chan et al., 2003 ; Black et al., 2000 ) . The multitude of studies conducted report ma ny findings informing how goals and objectives are met through partnering. Some report measurable outcomes in partnered vs. non - partnered projects, in that partnered (Chan et al., 2004 ; Black et al., 2000; Grajek et al., 2000; Gransberg et a l., 1999): Lower project related cost growth Projects completed at or under budgeted cost Reduced project related cost growth per change order Shorter construction schedules than planned Zero costs associated with disputes and claims Fewer disputes and cl aims Increased quality satisfaction Increased satisfaction in working relationships 17 Notwithstanding these positive attributes, others maintain partnering success hinges on less salient variables that are difficult to quantify. Successful implementation of partnering and subjective outcomes can be found throughout the literature, as well. A study conducted by Chan et al., (2003) is helpful in identifying relational variables found in partnering which are conducive during all phases of construction being: es tablishing and clearly communicating conflict resolution strategies; willingness and openness to resource sharing among project participants; clear direction as to lines of responsibilities for team members; working with win - win attitudes; and feedback thr ough regular monitoring of partnering process. Construction project stakeholders working to effectuate successful partnering stand to benefit from analyses such as Chan et al. (2003), in that, all of these variables appropriately attuned can lead to better team collaboration and success in project performance goals. These are primary motivations behind many project stakeholders and are presented through partnering. Notwithstanding, research investigating key partnering drivers (KPD) are among the most promi nent in partnering literature. 2.2.3. Partnering Knowledge in t he AEC Industry and Barriers t o Its Implementation The Architecture, Engineering, and Construction (AEC) industry is an environment where many relational transactions exist. These transactions occur d uring project planning, design, and construction phases involving construction projects. The motivations behind many of these transactions are constrained by the type of project delivery method or contractual arrangement employed. There are traditional pro ject delivery methods such as Design - Bid - Build (DBB), Construction Management (CM), and Construction Management - At Risk (CMR). Along with, 18 other emerging project delivery methods or arrangements such as Design - Build (DB), Integrated Project Delivery (IPD ), and partnering . Because partnering can be followed contractually or philosophically, it can enhance most project delivery methods helping to promote team integration (Lahdenpera, 2012; Yeung et al., 2012; Saunders & Mosey, 2005). Mollaoglu - Korkmaz et al . (2013) further maintain the level of team integration achieved is directly associated with the project delivery method followed on the project. This, in turn, results in optimized project performance outcomes. Despite the potential benefits for the AEC i ndustry, some argue partnering will continuously find resistance to its implementation. This is identified in developing partnering literature which suggests partnering is more of a fluid process which relies on many social aspects that are deeply rooted i (Hartmann & Bresnen, 2011) . As such, many claim the AEC industry is, and will remain, an adversarial industry fueled by profit motivations (Drexler Jr. & Larson, 2000) . For example, Bresnen (2007) con tends present get constrained due to several factors. Among these are difficulties in maintaining the collaborative goals and objectives, encouraging conformity, o pportunism, and setting superficial benchmarks or targets. In particular they contend partnering exerts normative pressures on individuals stifling innovative thinking within the team. This may also lead to opportunistic behavior where major partnering mem bers take advantage of smaller tier contractors or suppliers, thereby, impacting trust. 19 In the meanwhile, partnering attempts to encourage trust over a single construction project, while dealing with the aforementioned concerns. In this, the notion is lac k of commitment and unwillingness to compromise are challenged over a short time span (Ng, Rose, Mak, & Chen, 2002) . Dietrich et al. (2010) assert discontinuity in projects inhibits collaboration which, in a project based industry, performance is contingen t upon. Although this is true, successful collaborative efforts can serve as a catalyst reinforcing partnering motivations with the potential for future work. More importantly, Drexler and Larson (2000) maintain trust is developed over the course of partne ring projects creating reinforcing causal loops. In that, more time spent working through challenging problems and dealing with the frustrations of the greater trust in project team members. Still, others argue partnering is not a one size fits all solution for construction projects (Eriksson, 2010) . Therefore, we should also address the best applications for partnering to help understand its applicability. According to Lahdenpera (2012) and Eriksson (2010), partnering is most suitable for complex projects involving high - risk and uncertainties such as infrastructure projects. Within this application, project performance benefits are typically shared between owner and other project stakeholders. Meaning multiple parties stand to reap rewards from partnering. There are two variations of partnering, one of which is best suited for these types of projects encouraging trust and long term commitment among all parties. The tw o partnering types are project partnering and strategic partnering . Project partnering refers to relationship established for a single project, while strategic partnering implies a long - term commitment over several 20 projects (Li, Cheng, & Love, 2000). Both exhibit key strengths and weakness in partnering implementation yet are still beneficial to enhance performance outcomes. Recent research on partnering investigates AEC industry perceptions on barriers to partnering , suggesting areas where attention is ne eded in practice ( Korkmaz , Sparkling, & Thomas, 2014; Thomas, 2013). In particular the studies identify four prominent categories from which barriers are found being: cultural (i.e., traditional construction silos with distinct individual organizational bo undaries and objectives), organizational/program level (i.e., perceived unequal risks sharing and time committed to the process), project team (i.e., misaligned goals and objectives, lack of workshops and training earlier in process), and legislative/gover nance (i.e., laws and regulations encouraging competitive bidding rather than technical competence partnering philosophy as a significant barrier followed by lack of trust among pr oject participants. Furthermore, lack of partnering training programs and workshops early on in the project planning and design phase are likely culprits impeding partnering implementation possibly leading to confusion among the project teams or feelings o f unfair sharing of the risks associated with the project ( Korkmaz et al., 2014; Thomas, 2013). Despite concerns purported by some researchers, the key to overcoming implementation barriers are found in the relational aspects of partnering such as trust. In fact, Kumaraswamy et al. (2005) point out that mistrust is often reported within traditional contract delivery methods (i.e., DBB, CM, and CMR) where team integration and collaboration are not the focus. Rather, relational contracting approaches such as strategic partnering, and even project partnering, 21 offer the best deterrents to combat distrust and alleviate traditional adversarial mentalities found in construction. Even more, the construction industry relies upon established relationships and maintai ning trusting relationships helps everyone meet company and project specific objectives. Another perspective offered through literature maintains partnering is a dynamic relationship between interorganizational project team members. In this stream of lite rature it is argued that partnering challenges individuals and organizations to deviate from deeply rooted behaviors and routines developed over time (Gottlieb & Haugbolle, 2013; Hartmann & Bresnen, 2011). This perspective focuses on the conceptualization aspects of partnering , rather than procedural processes, helping researchers understand the theoretical connections. For example, Zhang and Ng (2013) attend individuals in construction teams behold extensive amounts of core knowledge in their respective di sciplines. They contend, effectively leveraging this pool of expertise can aid collaboration, joint problem solving, and improve efficiencies in project delivery efforts. More importantly, they argue volitional knowledge sharing originates from ude towards knowledge sharing and perceived behavioral controls. That is, motivation for sharing information is perceived as beneficial by the individual and appropriate opportunities, resources, or tools are present for these knowledge exchanges to succes sfully occur. In this, it is implied enhancing knowledge sharing in organizations is beneficial to achieving team integration, improving the efficacy in works processes, and transferring knowledge across multiple projects (Zhang & Ng, 2013 ; Dietrich, Eske rod, Dalcher, & Sandhawalia, 2010 ; Bresnen, Edelman, Newell, Scarbrough, & Swan, 2003). 22 mix of framed experience, values, contextual information, and expertise in sight that provides a partnering this knowledge and information sharing is imperative for project success and increased team collaborations (CII, 1991), but remains a challeng e due to the temporary nature of construction project teams (Bresnen et al., 2003). 2.3. Preliminary Review of Partnering Framework Partnering also exhibits other characteristics identified by key drivers or anticipated performance outcomes. For example, Beach et al., (2005) suggests partnering success is predicated upon factors such as top management commitment, partnering workshops, early implementation and involvement of key participants. F actors such as this are classified as key partnering drivers (KPD) an d are used to develop a conceptual partnering framework . The KPD are divided into three distinct subordinate categories being: planning and procurement oriented, relationship oriented, and process oriented. In t his taxonomy of key partnering drivers a posi tive link to partnering success is present ; moreover, performance outcomes are often seen as consequences resulting from the process. Chapter 4 will expound on the basis for these categories , though a brief synopsis is given next. 2.3.1. Key Partnering Drivers Planning/Procurement Oriented : R efers to those variables identified early on in the decision making process when potential project participants are deciding to pursue partnering. 23 Relationship Oriented : R efers to key variables found during the partnering li fe - cycle to improve relationships and enhance relationship management within interorganizational project teams. Process Oriented : R efers to identified variables occurring during partnering implementation process necessary to ensure the efficacy of partneri ng process. 2.3.2. External Moderator Public Sector Constraints : Important public sector concerns (e.g., b ureaucratic public client organizations , or s tringent public rules, regulations and laws which may discourage partnering implementation such as competitive b idding ) attenuating the success of partnering . Performance Outcomes The performance outcome categories are bifurcated into two exclusive constructs: project performance and organizational performance . These constructs are posited to distinctly classify pe rformance characteristics attributed to partnering reported in AEC partnering literature. The first category, project performance , is further divided into four subordinate categories. These categories are cost performance , schedule performance , quality an d safety performance , and dispute and litigation performance . Meanwhile, the organizational performance construct is separated into process performance and intraorganizational performance . A definition is given next for each of constructs mentioned above. 24 2.3.3. Project Performance Outcomes Cost Performance : R elated to those cost improvement outcomes attributed to partnering identified during partnering implementation and evaluated at project completion. Schedule Performance : R elated to outcomes associated wit h improved project durations which are ascribed to partnering process evaluated at project completion. Quality/Safety Performance : R elated to outcomes involving project safety improvements and design quality shown to reduce waste and inefficiencies during partnering process evaluated at project completion. Dispute/Litigation Performance : O utcomes refer ring to the reduction of disputes and litigation attributed to partnering process resulting in better claims and issue resolutions. 2.3.4. Organizational Performance Outcomes Process Performance : Process related improvements in interorganizational team collaboration learned through partnering process and available for feedback into all stages of the process. Intraorganizational Performance : Intraorganizational relat ed outcomes beneficial to long term organizational success evaluated after project completion. The aforementioned partnering categories to which attributes are classified are developed through extensive an AEC literature review. From this it is evident th at many dependent and independent variables describing key partnering drivers and performance outcomes are 25 present, therefore, a meta - analy tic approach was followed in this research. The following sections provide a brief overview of meta - analyses as a met hodology to explore wide bodies of existing research and its benefits in synthesizing the literature. 26 CHAPTER 3 RESEARCH METHODOLOGY 3.1. R esearch Strategy The primary goal of this research is to gain a deeper understanding of 25 years of partnering researc h in AEC literature through a research synthesis . In doing so, the following objectives are established for the research: 1. S ynthesize the body of knowledge in AEC partnering literature. 2. D evelop a proposed taxonomy of key partnering drivers (KPD) and perfo rmance outcome s with preliminary quantitative evidence from the AEC partnering literature . The results will provide theoretical underpinnings of AEC partnering literature making a contribution to broader organizational knowledge and theory. To study the r elationship among variables many researchers implore the use of a quantitative research design to investigate and test hypotheses (Creswell, 2009). The objective for this study is to learn the relationships between key partnering drivers and performance ou tcomes . To do so, a preliminary quantitative research design is used following a similar strategy as that with non - experimental research. A quantitative research design was chosen for this study because the methodology is conducive for interpreting links b etween dependent and independent variables using a survey instrument to convert them into numeric descriptions which are then available for statistical analysis (Creswell, 2009). T he research strategy followed for this study is shown on Figure 2. The over all research strategy is complemented by a five step meta - analysis approach namely : 1) Identify key partnering 27 drivers and performance outcomes reported in the AEC literature published in top tier construction management research journals, and other key pu blication sources , which are used to formulate study constructs and establish coding criteria; 2) Collect homogeneous studies reporting correlations between key partnering drivers and performance outcomes derived through empirical research; 3) Categoriz e s tudies according to research design (e.g., quantitative, qualitative, mixed - methods, or anecdotal) and other criteria established by coding sheet; 4) Data evaluation resulting from coding , and; 5) Interpret and discuss findings as a result of meta - analysis ( Kirca & Yaprak, 2010; Cooper et al., 2009; Lipsey & Wilson, 2001). The p roblem identification , need for the research, and literature review were discussed in Chapter 1. Therefore, the next sections will focus on the subsequent steps followed in this re search and provides a brief introduction to meta - analysis as a research method . 28 Figure 2 : Research steps followed in this study. 3.2. Meta - Analysis: A Scientific Method to Explore New Paradigms v ia Existing Research According to Coo per et al. (2009), the current era of meta - analysis was spawned from psychotherapy research by Glass (1976) and Rosenthal and Rubin (1978). From this nascent stream of meta - analysis work, the early 1980s experienced significant growth in meta - analyses focu sed on methodology and statistical inferences resulting from this research method. 29 According to Lipsey and Wilson (2001), meta - analyses rapidly moved to research conducted in social and health sciences, along with education and psychology. A m eta - analysis is similar to survey research, in that, research reports are surveyed rather than people. Meta - analysis is an ideal way to summarize, integrate, and interpret scholarly studies and combine findings into a grand mean effect for key variables. First and for emost, the studies must meet several criteria for consideration in meta - analysis being: empirical studies reporting quantitative findings using descriptive or inferential statistics for data analysis, entail comparable constructs and variables, and work w ith similar statistical formats (Cooper et al., 2009; Lipsey & Wilson, 2001). A limitation in this resides in the determination of relevant studies, which is subjective to the researcher conducting the MA. The findings from each study are interpreted throu gh effect sizes. This effect size is defined according to Lipsey & Wilson From this, key benefits are afforded to investigators and are shown by the various uses shown in literature. A recent meta - analysis conducted in the AEC literature utilized the approach to understand burgeoning project management research involving knowledge brokering (Holzmann, 2013). The research explores 10 years of pr oject management research to elicit areas for future research through a content analysis shedding light on current research trends. To do so, a content analysis approach is offered examining industry sector, project type, country, and the characteristics o f knowledge transfer. Findings from this research provide a great roadmap to future investigators as to emerging trends in knowledge brokering research. Although the 30 objective of the research is achieved and is presented using descriptive and qualitative i nformation, it lacks a final summary of effect size resulting from statistical analysis as required in typical meta - analyses (Cooper et al., 2009; Lipsey, & Wilson, 2001). In engineering educational research, meta - analysis is cited as a promising techniqu e to explore students, faculty, and engineering communities (Olds et al., 2005). Despite this, they attest it remains under reported or utilized in engineering research. Olds et al. (2005) , also explain how research in the engineering educational community stands to benefit if they effectively leverage emerging descriptive designs such as conversational analysis, observations, ethnographic studies, and more importantly meta - analyses. Similarly, AEC literature is lacking in its use of this promising methodol ogy which, for example, afforded engineering education researchers to assess the impacts of technology use on student learning across 760 articles (Olds et al., 2005). Specific benefits resulting from meta - analyses are discussed next. 3.2.1. Benefits o f Meta - Ana lysis A thoroughly conducted meta - analysis has many benefits to researchers and practitioners. In meta - analytic research the results may not only synthesize previous research, but, offer researchers valuable information on potential relationships that have not been explored in the data. For example, a model based or model driven meta - analysis examining the intercorrelations among constructs or variables may posit connections that independent studies fail to examine (Cooper et al., 2009). Additionally, b y ex amining longitudinal data in meta - analyses , the synthesist may be able expound theories as a result of unknown 31 connections such as mediating or confounding variable relationships that are otherwise not accounted for in bivariate analysis (Cooper et al., 20 09). A practitioner reading a meta - analysis or research synthesis also stands to benefit from information gleaned from the research. Many practical implications are put forward through meta - analyses , however, they predicated on the particular contextual q uestion explored and the reporting methods. For example, Cooper et al. (2009) maintains research synthesist should make efforts to include all studies in some format as to help readers understand the broader literature stream even though some may not be co nducive to typical meta - analytic reporting on effect sizes. Therefore, synthesist should try to present findings such that practitioners and researchers can make sense of whether descriptive statistics, qualitative, quantitative or a combination of all the various reporting methods. Research findings common to many studies according to Cooper et al., 2009 and Lipsey and Wilson (2001) are: Central Tendency Description: Characteristics of single sample respondents reported using mean, median, mode, or propo rtions. These are compatible for computing effect sizes; although it is critical variables are the same for all studies. Pre - Post Contrasts: These studies are single sample central tendency comparisons, however, variable are measure as change over time. R esulting descriptive statistics are typically reported showing relationships between two values as gains or differences 32 among respondents. Effect size is calculated as standardized differences between means. Group Contrasts: These types of studies involve two or more groups of respondents drawing comparisons across groups. In addition, one or more variables are measured within the studies and are reported using descriptive statistics, again, central tendency values such as means or proportions. Association between Variables: This type of research typically represents responses using covariation over respondents of two variables looking for correlations between them. Results are commonly reported as a correlation coefficient or derived through variable cross tabulation efforts. For example, odd - ratio, lambda, chi - square coefficient, or other similar statistical measurements to understand correlations between variables. These categories are prominently identified within findings resulting from many studies. Me ta - analyst should carefully identify consistencies among studies through this categorization process. This, again, initiates the process to which the meta - analysis can begin to set other criteria necessary to begin searching and collecting appropriate stud ies. In this study the association between variables is followed. 3.2.2. Use of Meta - Analysis and Directions from the Literature Meta - analysis research is ubiquitous and broadly extends across many disciplines in scholarly literature. In business literature rese archers have utilized a meta - analysis to assess market orientation antecedents and the implications on performance (Kirca, Jayachandran, & Bearden, 2005). In their analysis, the research approach was useful to consolidate findings from previous 33 market orie ntation and performance relationship literature, while also helping to eliminate inconsistencies and guide practitioners to problem areas management can place greater emphasis to enhance company performance objectives. 3.3. Data Collection a nd Screening Data c ollection commences after a cautiously developed study criteria is created. The research criteria set forth during design, aims to define the best population for eligible studies without placing stringent limitations to maintain the study samples as repres entative. An effective search strategy attempts to gather research from various sources include but are not limited to: review articles, study references, computerized bibliographic databases, bibliographic reference volumes, journals, authors in the area or topic, government agencies, and conference proceedings (Cooper et al., 2009; Lipsey & Wilson, 2001). An effective search strategy attempts to gather research from various sources include but are not limited to: review articles, study references, comput erized bibliographic databases, bibliographic reference volumes, journals, authors in the area or topic, government agencies, and conference proceedings. Many strategies also exist to identify studies using various search programs and search methods such a s Boolean logic to find key words or phrases. The search strategy used in this research is similar to that of Hong et al. (2012), as far as key word search partnering project partnering strategic partnering abstract . In addition, the search is limited by year, subject area, language, and document type. 34 Through a meta - analytic approach , this research aims to uncover correlations between key partnering drivers (KPD) and performance outcomes in AEC literature. In doing so, the following criteria acted as bookends for the research: 1. Partnering research in AEC literature from 1984 - present (Hong et al., 2012; Li et al., 2000; CII, 1989). 2. Leading construction management journals (Hong et al., 2012; Chou Kwong, 1997). Th ree prominent search engines ProQuest, Science Direct, and Scopus where used to collect relevant studies. In addition, manual searches of leading construction mana gement journals were completed. The initial search produced 622 studies from which the abstra cts were scanned to determine if the article should be further c onsidered for greater analysis. An additional manual search strategy is used to scan key journals for any additional studies investigating AEC partnering. Many studies where removed through da ta evaluation and screening for double counting , relevancy (e.g., word partnering used in the abstract or title although no connection to AEC partnering exists) , and/or inclusion error such as partnering within a different context (e.g., partnering concern ing public/private partnerships) . A snapshot of the final list of 1 73 partnering related studies as a result of the second stage analysis is shown on Table 1 , and includes articles collected from references or other search strategies including industry col laboration . The list was reviewed by an expert panel to improve the reliability of the final list of partnering related studies; most importantly, this is undertaken to ensure all relevant studies are included in the analysis. 35 Table 1 : Snapshot of Final List of Partnering Studies as a Result of t his Study ( Full List of 173 Studies provided in Appendix A). Author(s) Title Source of Publication Year Cheung, S., Suen, H., and Cheung, K. An automated partnering monitoring system - Partne ring Temperature Index Automation in Construction 2003 Yeomans, S., Bouchlaghem, N., and El - Hamalawi, A. An evaluation of current collaborative prototyping practices within the AEC industry Automation in Construction 2006 Yeung, J., Chan, A., Chan, D., and Li, L. Development of a partnering performance index (PPI) for construction projects in Hong Kong: a Delphi Study Automation in Construction 2007 Yeung, J., Chan, A., and Chan, D. A computerized model of measuring and benchmarking the partnering perfo rmance of construction projects Automation in Construction 2009 Carr, F., Hurtado, K., Lancaster, C., Markert, C., and Tucker, P. Partnering in Construction: A Practical Guide to Project Success Book 1999 Bennett, J., and Peace, S. Partnering in the Co nstruction Industry - A Code of Practice for Strategic Collaborative Working Book 2006 Table 2 displays the number of AEC partnering studies resulting from data collection and screening, along with the publication source. From this data collection and sc reening evaluation it is evident that the bulk of partnering research has been in the Journal of Management in Engineering (JME - 3 3 ), International Journal of Project Management (IJPM - 26 ), Construction Management and Economics (CME - 20 ), Journal of Construct ion Management and Engineering (JCME - 14), Engineering, Construction and Architectural Management ( ECAM - 12 ) , and Proceedings of the Institute of Civil Engineers: Municipal Engineer (PICE ME - 11) . This notion is clearly shown on Table 2 . Chou Kwong (1997) an d Hong et al. (2012) both confirm how disparate findings gleaned from this table are best understood . As anticipated , top tier construction management journals hold the predominance of AEC partnering studies ; w hereas other sources only have limited partner ing publications , many with only three or fewer . 36 Table 2 : Partnering Publication Sources Identified in AEC Literature and Number of Studies . Source of Publication # of Studies Source of Publication # of Studies Journal of Manageme nt in Engineering 33 Facilities 1 International Journal of Project Management 2 6 Habitat International 1 Construction Management and Economics 20 IEEE Transactions on Engineering Management 1 Journal of Construction Engineering and Management 14 Journa l of American Water Works Association 1 Engineering, Construction and Architectural Management 12 Journal of Architectural Engineering 1 Proceedings of the Institute of Civil Engineers: Municipal Engineer 11 Journal of Civil Engineering and Management 1 Industry Report 9 Journal of Infrastructure Systems 1 Project Management Institute 9 Journal of Legal Affairs and Dispute Resolution in Engineering and Construction 1 Automation in Construction 4 Journal of Marine Science and Technology 1 Book 3 Jour nal of Professional Issues in Engineering Education and Practice 1 Building and Environment 3 Korean Society of Civil Engineering Journal of Civil Engineering 1 Journal of Purchasing & Supply Management 3 Lean Construction Journal 1 Proceedings of the Institute of Civil Engineers: Civil Engineer 3 Pipeline & Gas Journal 1 Business Ethics: A European Review 1 Procedia - Social and Behavioral Sciences 1 Construction Innovation 1 Research Policy 1 Cost Engineering 1 Road and Transport Research 1 Engin eering Project Organization Journal 1 Supply Chain Management: An International Journal 1 European Journal of Purchasing & Supply Management 1 Thesis 1 Total 173 37 3.4. Data Coding Criteria This section gives a general description of the evaluation criteria established for this study. This data evaluation strategy initiated the meta - analytic approach followed in the resear ch methodology. 3.4.1. Data Coding Form Development According to Cooper et al. (2009) this criteria should be restrictive enough so as to allow homogeneous studies examining similar constructs using consistent methodological and procedural features. More importantly, the studies should be investigating the same topics and within similar contexts. For example, a study evaluating public / private pa rtnerships is not the same as AEC partnering where construction project teams work collaborative ly to deliver construction projects. In this format, either project specific partnering or intra organizational partnering is being considered. The researcher followed common meta - analysis techniques to evaluate AEC partnering literature by: 1) Evaluating the data collected from search strategy identified in Chapter 3 and ensuring the study satisfies the litmus test for further inclusion in the data sample as a AEC partnering study; 2) The studies are sorted as empirical, anecdotal, book, dissertations, etc.; 3) Studies are coded according to the coding manual to analyze study characteristics; and 4) Empirical studies are coded according to identify their substantive characteristics for analysis. To begin study selection, criteria are established to determine the eligibility of each study for meta - analysis . This criterion should be explicit in the research study population unde r 38 consideration for both analyzing and summarizing of their findings. General categories or items to consider when developing the data coding form are to determine if key distinguishing features are identified within each study namely: research respondent characteristics, key variables are represented, research methods and methodology, cultural and linguistic range, time frame, and publication type (Cooper et al., 2009; Lipsey & Wilson, 2001). In study selection methodology it is important to ensure a posi tive relationship exists between restrictive eligibility criteria and an extensive coding regimen including broader methodological and procedural features to improve validity of results. Additionally, methodological issues present within selected studies s hould be thoroughly explored to strengthen study design. For this research a coding form is developed , shown in appendix B , using the constructs found in literature review. The coding form serves as the survey instrument in meta - analysis research and it i s therefore imperative that care been taken in its design. As with surveys, the coding sheet must clearly elicit what is being measured and go through iterations to ensure it accurately accomplish es defined objectives and goals for the research (Cooper et al ., 2009). The cod ing form entailed 15 key codes that allowed the researcher to assign a code to characteristics and research design for each study identified during stage two of the meta - analysis. The 15 key codes are shown on Table 3 along with their d escriptions . 39 Table 3 : Partnering Key Codes used during Study Coding (Detailed Description provided in Appendix C) Descriptions Key Code Descriptions Key Code Study ID ID Performance Outcome Constructs PEROUTC Type of Publicati on TYPPUB Project Performance Outcomes PPERFOUT Year of Publication PUBYR Organizational Performance OPERFOUT Key Publication Source in AEC Literature KEYPUB Survey Design SURVD Study Type STUTYP Number of Respondents NRESP Unit of Analysis UNITA Data Collection Method DATACM Partnering Type PARTYP Construction Industry Sector CONSEC Key Partnering Driver Constructs KPDC Country of Study COUN The items coded within each study are based on recommendations found meta - analysis literature and preliminar y literature survey on AEC partnering ( Cooper et al., 2009; Lipsey & Wilson, 2001 ). C oded items in this study provide information on the characteristics of the publication and study methodological characteristic. A coding manual is developed explaining the categories used on the coding form. The coding manual is given in appendi x C . The key codes and coding manual are used to reduce error through orderly extraction of information from each rep ort examined in this research. The items collected from the codi ng forms were used in this study to delve into key study characteristics and substantive issues. The researcher entered coded data directly into an excel spreadsheet according to the established criteria on the coding form. From this, data evaluation 40 and a nalysis where conducted to construct a meta - analytic taxonomy on key partnering drivers and performance outcomes in AEC literature. To enrich the information collected via the coding form, the taxonomy on key partnering drivers and performance outcomes ar e investigated using an analysis to link them to each construct . First, the constructs are obtained via AEC literature on partnering from the coding forms. Next, the items identified in the research are sorted in respective constructs based on AEC literatu re and agreements made through researcher collaborations with industry professionals and practitioners. Example placements for the following items are : Clear contracting language and form of contracts are used. (Planning / Procurement Oriented) Mutual g oals and objectives are communicated to partnering participants. (Relationship Oriented) Continuous improvement workshops are used. (Process Oriented ) A full listing of this data sorting and analysis is provided in Appendices D, E, and F. The key partneri ng driver items are further investigated to understand their influence on the success of partnering . These are purported as having a positive or negative influence to successful partnering . Contrastingly, performance outcomes are inherently positive and ar e analyzed as such. A sample of this data analysis strategy for key partnering drivers is given on Table 4. 41 Table 4 : Sample List of Key P artnering Driver Construct a nd Variables . (Full List provided in Appendix D) PLANNING / PROCURE MENT VARIABLE RELATIONSHIP # OF TIMES IDENTIFIED Contract language and form of contract PLAN 0 6 + 12 Incentives / Fees / risk - reward/ gainshare - painshare PLAN14 + 12 Financial security/stability PLAN10 + 9 Poor understanding of the concept PLAN29 - 9 Availability of resources PLAN 0 1 + 8 Partnering experience PLAN27 + 8 Shared Equity PLAN34 + 7 Contract size or appropriate project size PLAN 0 7 + 6 Good cultural fit PLAN11 + 6 High cost to adopt partnering PLAN12 - 6 Partnering agreement PLA N26 + 6 Previous work experience with other members PLAN30 + 6 Technical expertise PLAN37 + 6 Clear and Compatible goals PLAN 0 3 + 4 Time required to develop PLAN38 + 4 3.4.2. Data Quality and Validity A common threat to the integrity and internal validity o f a research synthesis is coder reliability (Cooper et al., 2009; Lipsey & Wilson, 2001). To control for intrarater reliability the researcher worked extensively with an experienced research synthesist to develop appropriate data collection methods. This helped to ensure that studies are systematically collected and coded for further analysis. A second approach to internal validity was to consult industry professionals and faculty with knowledge concerning AEC partnering to pilot test the coding criteria a nd identify key constructs. By doing so, confidence is afforded to the classification of studies and substantive study characteristics collected by the researcher; moreover, the coding form is refined as a result . And finally , a two month time frame was all otted for the data collection, screening, coding stages of the research synthesis to help avoid coder drift. In addition, a 42 random sample of studies are recoded or double coded by the researcher to check for agreement rates between the coding results. The Agreement Rate (AR) equation, a widely used index of interrater or intrarater (IRR) according to Cooper et al. (2009), is give as: In this study, the value of AR is computed as 0.945 when recoding is completed by the researcher for 10 percent of the studies c oded during data evaluation and coding process. Ex ternal validity, as with any research method, is another important factor t o account for within a research study. Threats to external validity can surface from publication bias or lack of random sampling within studies (Cooper et al., 2009). In this study external validity is largely unaddressed, due to the study characteristics in AEC literature and conceptualization in the research design s offered. Even still, key study characteristics such as source of publication is coded and discussed to help readers understand the generalizability of findings from this research synthesis . 3.5. H ypothesis for Partnering Framework The research will analyze a hypothesis based on the data under consideration in this study . A Chi - Square test ( X 2 ) is conducted to understand the proposed partnering taxonomy where the observed values are the number of t imes the variables are counted within each of the study findings under investigation and tested against the expected values. In lieu of a qualitative 43 analysis utilized to summarize findings resulting from all research investigated in this stream of literat ure, a preliminary quantitative analysis is used to explore the following null hypothesis: H 0 = There no is difference between observed and expected values of both key partnering drivers and performance outcomes found in AEC literature. 3.6. Interpreting Resul ts a nd Discussion The final stage of this research is dedicated to the presentation of findings and to then discuss the results. This study reports the findings using descriptive statistics on study characteristics such as type of publication, year of publ ication, etc. The results are collected through two overlapping data sets being 173 studies to capture the broad base of AEC partnering literature study characteristics. Key study characteristics are accessed through this data offering direction and insigh t as to the depth and breadth of partnering research in AEC literature. The second data set consists of 74 studies or 43% of all AEC partnering literature. These key studies focus in on substantive issues integral to this study. Th ese are , then, explored by statistical analyses on substantive study characteristics , for example , partnering type, key partnering driver construct, and performance outcome construct as a result of data evaluation and analysis. Implications of research findings are discussed in C hapter 6, along with limitations and direction for future research. 44 3.7. Summary In summary, Chapter 3 emphasizes the goals and objectives of this research and introduces the research methodology that is followed . A meta - analytic approach is used for resear ch design being: construct identification, data collection and screening, coding form development , and data evaluation stemming from AEC literature investigating partnering . The next Chapter directs attention to the taxonomy on this stream of literature. F rom this, data analysis techniques which are found in meta - analytic research are used in Chapter 5 to ensure quality and to present findings on key partnering drivers and performance outcomes . 45 CHAPTER 4 FINDINGS This chapter presents a research synthesi s evaluating AEC partnering study characteristics and other substantive study features are presented using both a qualitative and quantitative approach. Then, details of the partnering taxonomy developed from partnering constructs are given . Lastly , a part nering framework developed as a result of this study 4.1. Research Synthesis of Partnering Study Characteristics This study examined key partnering drivers and prominent links between performance outcomes from 25 years of research purported in AEC partnering literature. A meta - analytic approach was conducted and suggests several key findings. The researcher utilized the information obtained from data analysis and evaluation on the key characteristics within the broader spectrum of AEC partnering literature. M eaning, 173 studies are used to report the background on this stream of literature. The following sections will focus attention on study characteristics found within the literature. As a result of this research synthesis, this study presents several key f eatures related to AEC partnering literature. First, the initiation of partnering purportedly commences with the Construction Industry Institute (CII) Partnering Task Force research aiming to establish consistency as it relates to partnering in constructio n, along with guidelines on process implementation and anticipated benefits (CII, 1989). Based on the trends shown on Figure 5, partnering research experienced rapid growth for a 10 year period reaching its crescendo around the year 1999 with empirical stu dies. 46 For interpretation of the references to color in this and all other figures, the reader is referred to the electronic version of this thesis. Figure 3 : AEC Partnering Research Tr ends shown in Five Year Periods. Contrasting ly, anecdotal research continued its ascension for approximately another five years thereafter. Surprisingly, the preponderance of AEC partnering research appears to be stalling based upon the evidence. This, perhaps, illuminates another approach is warran ted to continue investigating the practically of partnering and implications on performance outcomes through more industry based research with more sophisticated metrics to interpret findings. Based on findings from this research synthesis, Figure 6 is gi ven showing the aggregation of partnering studies over the past 25 years of research. Over the first two periods partnering research nearly tripled. The researcher further posits this growth may be attributable to the Latham Report (1994) put forward in th e UK, presenting a direction for researchers in this region regarding ways to improve ethics and trust performance in the UK construction industry (Wood, McDermott, & Swan, 2002; Khalfan, McDermott, & Swan, 1996). They credit the 0 5 10 15 20 25 30 1989 - 1993 1994 - 1998 1999 - 2003 2004 - 2008 2009 - 2013 # of Studies AEC Partnering Research Trends # of Anecdotal Studies # of Qualitative Studies # of Quantitative Studies # of Mixed Studies 47 Latham Report with guidanc e on their investigations to shed light on trust issues. Khalfan et al. (1996) further suggest these issues originate from the complexities of the construction industry and its associated fragmentation across organizations and projects. Subsequently, rese arch only doubles from 1998 to 2003 and remains relatively consistent from the period of 2003 to 2008. Then, as previously mentioned, research trends begin declining. Partnering research appears to have reached a saturation point, to which is confirmed by this downward trend. Figure 4 : Partnering Studies in AEC Literature shown by Five Year Periods. The second feature resulting from this synthesis was the type of publications in which AEC literature on partnering resides (i.e., j ournal, thesis or dissertation, industry report, conference proceedings, or unpublished manuscripts). Study findings show AEC partnering literature is most prominent within journal publications (160) and industry reports (9). Seventy four percent 9 25 49 51 39 1989 - 1993 1994 - 1998 1999 - 2003 2004 - 2008 2009 - 2013 # of Studies Years Partnering Studies in AEC Literature 1989 - 1993 1994 - 1998 1999 - 2003 2004 - 2008 2009 - 2013 48 (74%) of the studies are found within key publication sources (i.e., Journal of Management in Engineering , International Journal of Project Management , Construction Management and Economics , Journal of Construction Management and Engineering , Engineering , Construct ion and Architectural Management , and Proceedings of the Institute of Civil Engineers: Municipal Engineer ). Results did not produce any studies or literature resulting from conference proceedings or unpublished manuscript, however, a thesis on partnering a nd three book sources were accounted for. This is an interesting finding, as many research projects in academic literature stem from thesis or dissertations. As such, it was anticipated that many more AEC partnering studies would exists in this category. Study type (i.e., quantitative, qualitative, mixed, or anecdotal) was another finding related to AEC partnering research characteristics in which this study determined. As shown on Figure 7, partnering studies are predominantly empirical and quantitative i n study methodology and results. Of 173 partnering studies found within the literature results show: 70 - anecdotal, 64 - quantitative, 31 - qualitative and 8 - mixed methods. The findings from Figure 7, also purports a large number of anecdotal studies exists in AEC partnering literature. This category includes studies that are not empirically derived or are found in books and other publications that lack scholarly research rigors required for most of the other studies. Despite this concern, the researcher utiliz es this group of studies to help provide direction and guide future partnering research. 49 Figure 5 : Partnering Research in AEC Literature by Study Type and Number of Studies . When focusing on the empirical research findings invo lving AEC partnering the portion of quantitative studies becomes more evident. From this, it is clear that many researchers are taking advantage of quantitative methods to understand partnering ; thus, when anecdotal studies are not accounted almost two - thi rds of empirical partnering research is quantitative in methodology and findings. As such, a potential gap is presented for additional studies focused on underlying sociological constructs developed during partnering. These originate from organizational th eory and are often alluded to by other researchers which are more conducive to qualitative or mixed method approaches (Bresnen, 2009; Bresnen, 2007; Bresnen, Goussevskaia, & Swan, 2005). 70 64 31 8 0% 10% 20% 30% 40% 50% Percentage of Total Mixed 5% Qualitative 18% Quantitative 37% Anecdotal 40% Partnering Research in AEC Literature 50 The unit of analysis utilized by researchers investigating partner ing was forty two percent (42%) at individual partnered project level, while the majority examined interorganizational partnering or fifty eight percent (58%) of the studies. This finding exclaims that researcher realize the need to understand the organiz ational dynamics found within partnering more than the project level investigation. Although, research remains rather stagnate as to the advantages offered to project level performance which is difficult to infer benefits which are directly attributed to p artnering. The types of partnering investigated ranged from single project partnering, long - term organizational partnering, or general partnering when the type is not identifiable. Forty six percent (46%) of the studies found in AEC partnering literature looked at single project partnering, long - term organizational partnering was found in fifteen percent (15%) of the studies, and twenty eight percent (28%) of the studies did not directly mention the type of partnering . Meanwhile, one study examined partner ing from both perspectives. Results related to construction industry sector where not consistently reported or where difficult to determine the appropriate sector; however, it is worth noting that forty five percent (45%) of the studies did not attempt t o specify the construction industry sector. Therefore, future researchers may rethink the reporting related to this information in efforts to provide greater direction to both academics and practitioners. Another interesting findings resulting from this research synthesis within study characteristics is illuminated by the country in which the studies originated. This is shown on Figure 8, which 51 groups several countries where few studies were reported. According to the findings, the United States (US) prod uced the bulk of partnering studies (51); meanwhile, the United Kingdom (UK) follows with (49). The countries of origin are determined in one of two methods being: 1) country is clearly elicited within the study and is identified as such, or 2) when countr y is not clearly communicated in the study, the country is assigned by the researcher as first * Others: Singapore (3), Finland (1), India (1), Japan (1), Taiwan (2), Norway (1), Chile (1), Poland (1), Netherlands (2), Vietnam (1), Mal aysia (1), Korea (2), Puerto Rico (1), Spain (1), New Zealand (1). Figure 6 : Partnering Research in AEC Literature shown by Country. From Figure 8, it is also clear that several other countries are lagging behind with partnering re search. Although this is true, many of these countries are now beginning to conduct more research in this area as evinced in Figure 9. This figure, also, shows initial AEC partnering 0 10 20 30 40 50 60 US UK Hong Kong * Others Sweden Australia China US UK Hong Kong * Others Sweden Australia China # of Studies 53 46 28 20 12 8 6 Partnering Research in AEC Literature 52 research starting in the United States (US) from 1989 - 1993, with a dras tic increase the following period. During this same time period from 1994 - 1998 the United Kingdom (UK) and Hong Kong both experience their initial starts in AEC partnering research. Interestingly, a transition occurs in research trends by country from 19 99 - 2003 where both the US and UK begin to show declines in number of partnering studies; whereas, other countries continue to see growth until 2009. Figure 7 : Partnering Studies by Country and Five Year Period. Next a brief s ummary of three other study characteristics is given. The studies included in this portion of the analysis are reduced to 71. This is particularly important because these studies directly investigate similar constructs which are aggregated in this synthesi s to derive the 0 5 10 15 20 25 1989 - 1993 1994 - 1998 1999 - 2003 2004 - 2008 2009 - 2013 # of Studies Years US UK Hong Kong Sweden China Others Australia 53 taxonomy of AEC partnering literature. The next section directs attention to these substantive study characteristics extracted through the coding criteria and results thereof. 4.2. Research Synthesis o f Partnering Dri vers a nd Consequences Thi s section presents findings associated with key partnering drivers and performance outcomes as a result of this research synthesis. A quantitative approach is used to explore links between the constructs included in the taxonomy of AEC partnering literatur e. To illuminate findings descriptive statistics are reported. The three primary partnering categories and nine subsequent constructs are shown in Table 5 . This table illuminates the pervasive variables identified within AEC literature investigating part nering . These are the results of 71 studies investigating similar substantive issues. The mean number of items provided by each study was 13 items, while the median was 12. Process oriented variables are most frequently purported in AEC literature (i.e., 2 74 variables identified by 55 studies), while planning and procurement related variables occurred second most frequently in AEC literature (i.e., 160 variables identified by 55 studies). Meanwhile, 23 variables classified as external moderators attenuatin g the effect of key partnering drivers on partnering project success. In sum, 939 variables are purported within partnering literature of which 566 are categorized as key partnering drivers and 350 variables are performance consequences or outcomes. 54 Tabl e 5 : Partnering Constructs and Variables in AEC Literature. Constructs # of Times Variables Identified # of Studies Key Partnering Drivers Process Oriented 274 55 Planning / Procurement Oriented 160 55 Relationship Oriented 13 2 48 External Moderator Public Sector Sentiment 23 8 Project Performance Outcomes Cost Performance 71 29 Schedule Performance 40 29 Quality / Safety Performance 59 27 Dispute / Litigation Performance 32 21 Organizational Performance Outcomes Intra organizational Performance 78 27 Process Related Performance 70 27 This research synthesis produced the following ranking of key items found within the taxonomy on AEC partnering literature. The top three items most frequently identified by the lit eratu re are presented on Table 6 . 55 Table 6 : Top Three Attributes for Each Partnering Construct in AEC Literature. Constructs Key Attributes # of Times Identified Key Partnering Drivers Planning / Procurement Oriented * Clear contracti ng language and form of contract used ; Incentives, feeds, risk - reward, or gainshare - painshare arrangements used. 12 Organizations have financial security and stability to support process . 9 * Po or understanding of the concept; Availability of resource s 8 Relationship Oriented Mutual trust is established for interorganizational project team. 21 Mutual goals and objectives are communicated to partnering participants. 14 Strong team commitment. 12 Process Oriented Top management commitment and s upport. 20 Effective and open communication or dialogue within the interorganizational project team. 16 Continuous improvement workshops are used. 14 External Moderator Public Sec t or Sentiment Bureaucratic public client organizations inhibit partn ering implementation. 6 Stringent public rules, regulations and laws discourage partnering implementation such as competitive bidding. 4 Conservative industry culture inhibits partnering approach where status quo is strongly supported. 3 * Key att ributes equally identified within AEC partnering studies. 56 Table 6 (C ) : Top Three Attributes for Each Partnering Construct in AEC Literature. Constructs Key Attributes # of Times Identified Project Performance Outcomes Cost Performance Meeting bu dgeted costs targets for the project. 10 Cost savings are achieved on the project. 7 Reduces additional project expenses resulting from changes. 6 Schedule Performance Meeting schedule targets for the project. 12 Reduces time in delivery the pr oject. 6 Better productivity for project teams. 5 Quality / Safety Performance Improves the overall quality of the project. 14 * Environmental issue complaints ; * Reduces the amount of wasted work or rework ; * Increases client satisfaction . 5 Impro ve designs for the project. 4 Dispute / Litigation Performance Reduces number of disputes associated with the project. 10 * Reduces litigation associated with the project ; Effective clai ms and issue resolution process; 7 *Improved conflict resolut ion strategies; Reduced exposure to risks. 3 Organizational Performance Outcomes Process Related Performance Improved relationship for interorganizational project team. 16 Long - term trust established for interorganizational project team. 10 Impr oved communication for interorganizational project team. 9 Intraorganizational Performance Improved profit margins. 8 * ; Improved corporate culture . 7 Opportunity to continuously access new project s based on healthy relationships and experience. 6 * Key attributes equally identified within AEC partnering studies. The number of items varied by construct, for example, external moderators had the fewest number of items (10). Contrastingly, the pr ocess oriented category held the greatest proportion of partnering variables assigned to any category (72). The proposed taxonomies are shown on 57 Table 8, including; (1) number of items or variables assigned to each construct; (2) number of times the variables a re identified within all studies combined; and (3), number of studies investigating the constructs. A complete list of the items identified in literature can be found in the appendices. The number of items listed in each of the constructs and number of tim es variable s identified reported on Table 7 , are then used in data analysis to calculate expected values for the Chi - Square test in the next section. Table 7 : Taxonomy of Partnering in AEC Literature . Constructs # of Items # of Tim es Variables Identified # of Studies Key Partnering Drivers Process Oriented 72 274 55 Relationship Oriented 33 132 48 Planning / Procurement Oriented 38 160 55 External Moderator Public Sector Sentiment 10 10 23 Project Performance Outco mes Cost Performance 23 71 29 Quality / Safety Performance 20 59 27 Schedule Performance 11 40 29 Dispute / Litigation Performance 7 32 21 Organizational Performance Outcomes Intraorganizational Performance 26 78 27 Process Related Performance 20 70 27 The results from both Table 6 and Table 7 also give several key findings that are worth noting. First, key partnering drivers received the highest number of studies (55) reporting on the associated constructs. In addition, it is c learly evident that process oriented attributes of partnering are most important to perpetuate successful partnering according to AEC literature. This means procedural aspects such as continuing to gain support of top management, ensuring 58 effective lines o f communication exists among interorganizational project team members, and continuous improvement workshops may help reinforce the partnering process. A second key finding relates to cost performance at the project level. The evidence shows that cost impli cations are improved through partnering based on the number of times the variables are identified in literature. Within the cost performance construct meeting project budgets and costs savings are offered through partnering , as Table 8 also indicated. Othe r costs are also reduced, in particular those associated with changes on the project. At the organizational level of analysis the results were closely split between process related and intraorganizational performance . For example, 27 studies captured varia bles found in organizational performance outcomes with 70 and 78, respectively situated in each construct. Key findings for process related performance are associated with interorganizational team performance such as improving relationships, building long - term trust, and communication. Meanwhile, partnering is reputation in the industry. Statistical analysis for this study is given next to further elucidate findin gs as a result of hypothesis testing. 4.2.1. Statistical Analysis of Key Partnering Drivers and Performance Outcomes To learn the associations of variables a Chi - Square test ( X 2 ) is conducted where the observed values are the number of times the variables are co unted within each of the study findings under investigation and tested against the expected values. This test is completed to learn the significance level of the relationships between key partnering drivers and project partnering 59 success. In addition, the test helped to validate the proposed taxonomy on partnering and its associated constructs and the categorization of items or variables based on AEC literature. The following null hypothesis and alternative hypothesis are used to examine the taxonomy of pa rtnering: H 0 = There is no difference between observed and expected values of both key partnering drivers and performance outcomes found in AEC literature. H 1 = There is a significant difference between observed and expected values of both key partnering drivers and performance outcomes found in AEC literature. A Chi - Square test ( X 2 ) is used in final analysis to examine key partnering drivers and performance outcomes. Expected values for key partnering drivers are calculated as: Results from this analysis relating to key part nering driver s are given on Table 8. An example calculation for expected value of the relationship (Yes) cell is calculated as: The information in the observed section of the table displays the number of times variables are posited as having a positive relationship on partnering success within studies. These counts are reported in the (Yes) row. If variables within each study are negatively associated with successful partnering it was reported in the (No) row. A table showing this fu ll coding for each 60 variable is shown in the appendices. A brief snapshot is given on Table 10, along with an explanation on the strategy followed during analysis. Based on the results shown on Table 8 , the taxonomy of key partnering drivers is a valid cat egorization of the variables found in AEC literature (i.e., ). Meaning, there is a significant difference between the observed and expected values produced from the research synthesis and subsequent categorization. From this it is suggested th at the exploratory taxonomy of key partnering drivers is not as a result of chance or randomization. In addition, a level of dependency exists between those who feel partnering success hinges on the respective key partnering driver categories. Table 8 : Key Partnering Driver Category Validation Observed Key Partnering Drivers Expected Key Partnering Drivers Planning/ Procurement Relationship Process Total Planning/ Procurement Relationship Process Yes 128 113 250 491 13 8.799 114.509 237.693 No 32 19 24 75 21.201 17.491 36.307 Total 160 132 274 566 To reach aforementioned results on key partnering drivers the researcher assigned values to each variable within studies. The values are classifi ed using a strategy to determine if the variable has a positive (+) or negative ( - ) association with partnering success. For instance, 61 purported incompatible project type (e.g., public sector, private sector) to implore the benefits of partnering on a proj ect runs counter to its overall success. In a similar manner, including incentives or risk - reward arrangements for the project participants is seen as beneficial to partnering success. Table 9 displays similar results regarding observed performance outco mes situated in project performance and organizational performance . Expected values are arrived at using a slight variation in computation, in part, because performance outcomes are commonly reported with a neutral or positive connotation. Based on the re sults, again, it shows that the taxonomy related to performance outcomes found in AEC partnering literature is appropriately categorized. The Chi - square test provides that observed values obtained from the literature are significant ly different when compar ed to expected values, and therefore, are far from chance in the classification of partnering performance outcomes (i.e., - 40 ). Table 9 : Performance Outcomes Categorization Validation Observed and Expected Performance Outcomes Project Performance Organizational Performance Observed 202 148 Expected 115.159 63.626 - 40 The observed and expected values presented on Table 9 are arrived at through results provided on Table 1 0 . This table, which is found in the appendices, previews the results of coding for 62 performance outcome variables. Results from Table 10 are then used to compute expected values. A sample calculation is given next. Table 10 : Snapshot of Performance Outcome Con structs and Variables ( Full List provided in Appendix F). To compute the expected value for project performance variables, first, the researcher combined all the observed variables found in the literature being 202 (i.e., 71 cost performance, 40 schedule performance, 59 quality and safety perfor mance, and 32 dispute and litigation performance). Second, the following formula is used: The numbers of available project performance variables for each construct are: 23 cost performance, 11 schedule performance, 20 quality and safety performance, and 7 dispute and litigation performance. Additionally, the numbers of available organizational performance variables are: 20 process performance and 26 intraorganizational performance. The overall total number of available performance outcome variables equa ls 107. An example calculation SCHEDULE PERFORMANCE VARIABLE TOTAL Meeting schedule targets SCHP6 12 Reduce time in delivering the project SCHP9 6 Better productivity SCHP1 5 Project schedule growth SCHP8 4 Time varianc e SCHP11 3 Improved construction time SCHP2 2 Integrated solutions to improve efficiency SCHP4 2 Liquidated damage percent of total contract days SCHP5 2 Percent of additional days granted SCHP7 2 Improved productivity SCHP3 1 Time SCHP10 1 TOTAL 40 63 to determine the expected value for the project performance outcome category is entered as such: The full listing of available variables used for the project performance analy sis is shown in the appendices. 4.3. Partnering Construct Development a nd Taxonomy From the initial analysis conducted at stage one , being construct identificat ion, the following constructs were formulated the guide to the research. There were three major categories from which these were found being : key partnering drivers, project performance outcomes , and organizational performance . The following Table 11 shows the initial taxonomy of partnering constructs. The table also gives definitions for each construct to which establishes the criteria for inclusion of specific variables identified within each study. The table identifies the construct categories as: key pa rtnering drivers , project performance outcomes , and organizational performance . The major categories are further segmented into nine different constructs that are used to build the partnering taxonomy. 64 Table 11 : Taxonomy of Part nering C onstruct s and Associated D efinition . Constructs Definitions Key Partnering Drivers Planning / Procurement Oriented Important attributes identified early on in the decision making process when potential project participants decide to pursue partne ring. Relationship Oriented Important attributes found during relationship management occurring within interorganizational project teams. Process Oriented Important attributes occurring during the partnering process necessary to ensure the efficacy of partnering process. External Moderator Public Sector Sentiment Important public sector concerns attenuating the success of partnering process. Project Performance Outcomes Cost Performance Those cost improvement outcomes attributed to partnering pr ocess evaluated after project completion. Schedule Performance Those project schedule improvement outcomes attributed to partnering process evaluated after project completion. Quality / Safety Performance Those project quality and safety related outcomes attributed to partnering process evaluated after project completion. Dispute / Litigation Performance Those project dispute and litigation improvements attributed to partnering process evaluated after project completion. Organizational Perfo rmance Outcomes Process Related Performance Process related improvements in interorganizational team collaboration learned through partnering process and available for feedback into process. Intraorganizational Performance Intraorganizational related outcomes beneficial to long term organizational success evaluated after project completion. 4.3.1. Key Partnering Driver Construct Development As organizations set out to pursue partnering they will typically employ a strategy to determine its applicability for the project. Several variables nested within key partnering drivers are 65 frequently posited to ensure effective planning and procurement and are therefore categorized as such . CII (1989) and Black et al., (2000) suggest establishing and maintaining shared performance goals and objectives, ensuring partner organizations are properly aligned, and having the necessary technical expertise and resources to implement partnering are key planning and procurement attributes . Other subordinate variables under KPD are relationship oriented and are considered prior to and during the partnering implementation stages . Some of these relationship oriented aspects are identified as mutual trust, top management commitment, and win - win team philosophy which are explored from the perspective of partnering participants . Additionally, it is important that procedural or process oriented drivers are appropriately accounted for to learn key implementation variables , the last subordinate category to KPD. These three distinct catego ries are discussed next. Planning and procurement oriented refers to those variables identified early on in the decision making process when potential project participants are deciding to pursue partnering. Partnering planning and procurement oriented at tributes present in AEC literature are categorized as key drivers of partnering in this research. Many organizations and potential partnering participants approach partnering planning and procurement systematically. This means, prior to organizations setti ng out to establish a partnered project they evaluate the merit for partnering based on several criteria. Some of these key attributes or questions identified in the literature are (Bresnen, 2010; Bresnen, 2009; Yeung et al., 2009; Eriksson & Pesamaa, 2007 ; Chan et al., 2006; Wong et al., 2005; Gladola & Sheedy, 2002; Ng et al., 2002; Rogge et al., 2002; Black et al, 2000; Grajek et al., 2000) : 66 Is the project the right size for partnering (i.e., > $5 million)? Does the contracting language clearly include partnering? What form of contract or project delivery method will be used? What is the anticipated project duration? Will there be a joint project charter established for the project (i.e., formal document signed by partnering parties outlining joint coll aboration principles established during the initial workshop)? Should the project partnering participants use a partnering agreement? Do the partnering participants have the necessary technical expertise to develop partnering? Should the partnering project include incentives, risk - reward, or gainshare - painshare arrangements? Do participants have any previous partnering experience? How well do participants understand the partnering concept? Many of these questions owners, contractors, and designers will con sider and must answer prior to forming a partnership to help ensure the project aligns with intraorganizational goals and objectives . Relationship oriented refers to key variables found during the partnering life - cycle to improve relationships and enhance relationship management within interorganizational project teams. One frequently posited variable is mutual trust within the project team members throughout the entire partnering process. Thus, relationships are predicated on trust which formulates the 67 in itial building blocks for the rest of the dealing in terms of communication and information exchanges. Several other KPD extracted from AEC literature shows mutual goals and objectives that are clearly communicated to the project team and garnering team me to the entire partnering process are essential during all stages of partnering . In addition to clear goals and objectives, project team members should feel equally empowered to offer innovative ideas or solutions when problems are encount ered during project execution (Hughes, Williams, & Ren, 2012; Yeung et al., 2009; Tang, Shen, & Cheng, 2006; Chan et al., 2004; Chan et al., 2003; Ng et al., 2002; Akintoye et al., 2000). Process oriented refers to identified variables occurring during pa rtnering implementation process necessary to ensure the efficacy of partnering process. After organizations decide to pursue partnering , a professional facilitator leads a workshop which establishes the partnering relationship for the participants. During the workshop decision - making processes and performance improvement metrics are discussed by the project team. Other KPD included in the partnering process oriented phase are: top management commitment and support during implementation, open and effective c ommunication among project participants, and early involvement of designer, contractor, and subcontractors in partnering process, developing a dispute resolution process, and joint project office with shared information technology tools are utilized ( Lahde npera, 2012 ; Manley et al. 2012; Eriksson, 2010; Chan et al. 2006; Nystrom, 2005 ). Other effective KPD purported are continuous training and frequent partnering meetings where feedback is provided to the team for continuous improvement efforts ( Cheung et a l., 68 2003 ; Rogge et al., 2002 ; Cheng et al., 2000 ). While working through partnering implementation process it is, also, imperative that relationships are appropriately managed and strengthened. Although the categories are mutually exclusive, the attribute s are realized across various stages of the construction process. For example, during project initiation and conceptual design partnering participants have decided to pursue partnering and start outlining the joint partnering charter, while also working wi th other project team members representing the owner, client, designers, and main contractors to select subcontractors and vendors. At this junction they are also establishing mutual trust and setting the goals and objectives for the projects, which are re l ationship attributes. Figure 4 displays the six stages of a construction project s and depicts how key performance attributes and performance outcomes are related. The schematic design and design development stages are where relationship and process orient ed attributes are starting to become more focused, especially as the project ap proaches the construction phase. From here, project characteristics and performance outcomes start to take shape allowing project partnering stakeholders to learn from the over all construction process how partnering impacts performance outcomes . The performance outcomes are classified as project, process, or organizational performance and are discussed next. 69 Figure 8 : Stages of Construction Partnerin g and Associated Construct s. 70 4.3.2. Performance Outcome Construct Development AEC literature maintains successful partnering projects are beneficial to improve performance at several dimensions. To examine performance implications literature points to certain use ful metrics found in the three distinct dimensions. These dimensions are project performance , process performance , and intraorganizational performance . Performances at the project level are separated as : cost performance, schedule performance, quality/saf ety performance, and finally dispute/litigation performance. These areas are common reported in AEC literature as critical measure and outcomes that should be evaluated to ascertain whether a project is successful. Cost performance is related to those cos t improvement outcomes attributed to partnering identified during partnering implementation and evaluated at project completion. To learn and analyze cost benefits attributable to partnering , researchers utilize objective metrics such as cost growth (i.e., change in contract amount in respect to original contract amount), average cost per change orders (i.e., change in contract amount in respect to number of change orders), and schedule growth among others (Gransberg et al., 1999). The aforementioned object ives metrics, though not exhaustive, are used to report project performance goals and objectives. From this, some researchers and partnering participants utilize this project level performance information to compare partnered versus non - partnered project o utcomes (Grajek et al., 2000; Gransberg et al., 1999; Weston et al., 1993). 71 Schedule performance is related to outcomes associated with improved project durations which are ascribed to partnering process evaluated at project completion. For example, partn ering is believed to reduce the overall project delivery time, while also helping the project team members meet predetermined schedule milestones or target dates (Anderson & Polkinghorn, 2011; Doloi, 2009; Larson, 1995). In the meanwhile partnering is also credited with reducing the number of liquidated damages per total contract days, controlling project schedule growth, and improving both productivity and efficiency within the project (Ling, Ong, Ke, Wang, & Zou, 2014; Lu & Yan, 2007; Gransberg et al., 19 99; Gransberg et al., 1998). Quality and safety performance is related to outcomes involving project safety improvements and design quality shown to reduce waste and inefficiencies during partnering process evaluated at project completion. The quality of construction documents and designs are improved through greater collaboration from all parties early on in the conceptual and design development stages of a project. During the early phases of the construction process bringing in contractors can assist in value engineering and constructability concerns which are shown to have a positive impact on both cost and schedule performance (CII, 1991). Therefore, project delivery arrangements such as partnering can assist efforts to boost quality. Often times the qu ality of the project is based upon client or end - noticeable improvements resulting from quality design are fewer environmental complaints, reduced wasted work, or having to do rework; More importantly partnering p rojects are thought to provide a safer environment for workers because there is a higher performance expectation for the project, which fosters better safety awareness among all project team 72 members. This goes hand in hand with goals and objectives for bot h the project team and organizations involved. Dispute and litigation performance outcomes refer to the reduction of disputes and litigation attributed to partnering process resulting in better claims and issue resolutions. The bedrock of partnering from its inception has been to minimize disputes and litigation within the construction industry due to the competitive nature of business fueled by high financial risks (CII, 1991). Partnering , as such attempts to assuage those concerns by creating systems to deal with claims and issues intent on minimizing disputes which lead to litigation ( Bayliss et al., 2004; Chan et al., 2003; Gransberg et al., 1999). Certain performance aspects are typically defined as soft measures and are frequently purported using su al., 2003). The two types of organizational performance outcomes are process performance and intraorganizational performance , although organizational performance may also be unders tood through both subjective and objective data. Process performance is related to improvements in interorganizational team collaboration learned through partnering process available for feedback into all stages of process. For example Black et al. (2000) and Chan et al. (2003) exclaim less adversarial relationships, improved administration processes, better communications among participants, and long - term relationships solidified by trust are offered as some of the anticipated process performance advantag es. These are categorized, again, as process performance attributes because they can 73 be recycled back into partnering implementation as feedback to further refine partnering implementation and are related to procedural performance aspects. The final perfo rmance dimension, being organizational performance, offers partnering organizations additional paybacks. Intraorganizational performance is related to outcomes beneficial to long - term organizational success identified during partnering and analyzed after project completion. Some of these reported paybacks or outcomes are increased profit, closer relationships with client and other partnering parties, improved organizational competencies and corporate cultures, and the ability to seize new market opportunit ies (Cheng et al., 2000; Lazar et al., 1997). Again, many of these attributes are positioned to provide feedback during the partnering initiation and implementation stages. 4.4. Summary This Chapter presented the findings as a result of the analysis undertaken to explore AEC partnering literature. More importantly, a sound taxonomy on this literature is asserted to guide industry practitioners and researchers as to the current state of AEC partnering . One of the most prominent deliverables was covered through a qualitative synthesis on partnering study characteristics, and then a preliminary quantitative analysis was used to explore relationships among substantive study feature s. The next chapter summarizes the results, presents limitations , and conclusions . 74 C HAPTER 5 SUMMARY AND CONCLUSIONS The final chapter provides a summary of the results. In addition, it also offers theoretical and practical implications, l imitations, recommendations for future research , and final conclusions , respectively. 5.1. Summary of t he Results This study attempted to understand vast body of AEC partnering literature that has been developed over the past 25 years. To do so, a meta - analytic approach was followed aiming to provide a sound taxonomy on partnering attributes found in the li terature. Based on this, the study offers a useful framework of partnering and its associated variables which are critical to successful project partnering. Results from this study provide both researchers and practitioners with information to understand t he depth and breadth of AEC partnering literature. For example, it is clearly evident from the qualitative results that a new research direction on partnering is needed to propel this concept forward in its understanding and implementation. With all of the research that has been conducted, it still lacks decisive evidence on its impact on performance outcomes. In fact, the decline in research may suggest that this concept, which is deeply rooted in organizational theory, is more difficult to understand than original expectations. Initial findings from this research synthesis shows that partnering research in AEC literature has predominately received the most attention in the US and UK. In addition, the number of studies appears to be on a downward trend, e specially in these two regions. Although other smaller countries seem to be growing in their partnering research investigations. 75 Other findings related to study characteristics, clearly point out that many researchers are taking advantage of quantitative methods to understand partnering ; however, anecdotal studies accounted almost half (40%) of partnering research. As such, a potential gap is presented for additional empirically derived studies focused on deeply rooted sociological constructs developed du ring partnering via case studies . In part, because partnering is a dynamic process that continues to evolve as do projects which should b e studied longitudinally . S ociological constructs such as knowledge exchanges and its implication on team integration a re best understood through critical investigation of individuals and their associated behaviors. As such, the future of partnering research may best fit organizational theory investigated at the project team level. This is often alluded to by other researc hers and is more conducive to qualitative or mixed method approaches (Bresnen, 2009; Bresnen, 2007; Bresnen, Goussevskaia, & Swan, 2005) . Perhaps this type of research can help with concerns about the temporary impacts of partnering that does not appear t o translate across multiple projects. R esults of this study and the partnering taxonomy show the following constructs are critical to success project partnering: 1) planning and procurement oriented items such as providing the appropriate contracting lang uage and contractual forms identifying the partnering arrangement; 2) relationship oriented items such as ensuing that the interorganizational project teams are able to develop mutual trust, along with, communicating mutually beneficial goals and objective s for all partnering participants; and, 3) process oriented items which are those action items occurring during partnering such as keeping the support from top management from the respective home organizations and maintaining effective lines of communicati on 76 between interorganizational team members. The following Table 12 and Table 13 both display the top ranked KPDs and performance outcomes found in AEC partnering literature with a minimum reporting of 10 or more times identified in the literature. Table 12 : Ranking of Top Key Partnering Drivers in AEC Literature . Constructs Key Attributes # of Times Identified Ranking Relationship Oriented Mutual trust is established for interorganizational project team. 21 1 Process Oriented Top management commitment and support. 20 2 Process Oriented Effective and open communication or dialogue within the interorganizational project team. 16 3 Process Oriented Continuous improvement workshops are used. 14 4 Relationship Oriented Mutual goal s and objectives are communicated to partnering participants. 14 4 Process Oriented Early involvement of designer / contractor / subcontractors. 13 5 Planning / Procurement Oriented *Clear contracting language and form of contract used; Incentives, feed s, risk - reward, or gainshare - painshare arrangements used. 12 6 Process Oriented Regular monitoring of partnering process (Benchmarking) 12 6 Relationship Oriented Strong team commitment. 12 6 Process Oriented Team building sessions are used . 11 7 Proc ess Oriented Free flow of information among partnering participants . 10 8 * Key attributes equally identified within AEC partnering studies. 77 Table 13 : Top Performance Outcomes in AEC Partnering Literature. Constructs Key Attribut es # of Times Identified Ranking Process Performance Improved relationship for partnering participants. 16 1 Quality / Safety Performance Improve the quality of the project. 14 2 Schedule Performance Meeting schedule targets. 12 3 Cost Performance Mee ting budgeted costs targets. 10 4 Dispute / Litigation Performance Reduces disputes for the project. 10 4 Process Performance Long - term trust established for project participants. 10 4 Other findings from this research show that performance outcomes ar e related to partnering and key partnering drivers. This is suggested from the partnering framework put forward in this research. The aim was to show links via AEC partnering literature which identifies the key performance variables attributed to partnerin g. As such, the variables are aggregated into the taxonomy of partnering . 5.2. Partnering Framework A partnering framework is given in Figure 9 based on the evidence from AEC partnering literature. The framework displays a link between key partnering drivers a nd successful partnering projects (1 - 2), meaning when variables included within each construct category are appropriately attuned positive outcomes are anticipated for the project. Similarly, links (1 - 3) and (2 - 3) both maintain a positive association exist s between both key partnering drivers and 78 project partnering with the performance outcomes. A moderated relationship (1 - 2(4)) is also identified in this partnering framework which includes variables that may attenuate the effects of key partnering drivers and the overall success of the partnered project. The moderated variables are categorized as public sector constraints (e.g., stringent public rules, regulations, and laws that discourage partnering). 79 Figure 9 : Framework Develo ped to Understand AEC Partnering Literature. 80 5.3. Theoretical Implication and Practical Application This section will illuminate the findings from this study as they relate to previous partnering research in AEC literature. This research establishes guidance t o the state of partnering research along with a valuable taxonomy available for further investigation. In addition, this study provided key drivers of partnering linking them to both project performance and overall partnering succes s. Joining with prior re search, this study shows that keys to partnering reside within the process of partnering implementation. Many studies point to variables such as gaining the support and commitment of top management, along with effective and open communications as prerequis ites to maintain a successful partnering arrangement. For example, Black et al. (2000) ranks process oriented factors such as these among the highest to mitigate conflicts during the project and to ensure senior management is committed to the partnering ap proach. Continuing with this notion, this research directs attention to the process oriented attributes providing the bulk of the variables identified in the AEC partnering literature. As such, industry practitioners involved in partnering would be wise t o keep clear and open dialogues among interorganizational project teams. This collaborative environment, among project teams, allows for enhanced knowledge sharing and trusting relationships to develop which are proven beneficial to performance outcomes (Z hang & Ng, 2013 ; Solis et al., 2013; Chinowsky et al., 2011; Chinowsky et al., 2008). A similar sentiment is shared by Bemelmans, Voordijk, and Vos (2012) in their investigation specific to supplier - contractor collaborations in AEC industry. Based on their findings these two factors are most influential to successful partnering . 81 Over the decades clear project specific performance implications remains elusive, yet studies as this continue to report cost improvements are available through partnering . Early s tudies investigating partnering performance outcomes provide quantitative evidence alluding to (Anderson & Polkinghorn, 2012; Gransberg et al., 1999). This study aggregated over 23 performance related variables associated with cost. In particular, variable s such as achieving budgeted costs and schedule goals are purported in AEC literature as key benefit s of partnering. The problem with these measured performance outcome s stems from lack of longitudinal data and the singular nature of construction projects. Meaning it is difficult to draw conclusions based purely on the implementation of partnering especially with the uniqueness of construction projects. 5.4. Limitations and Recommendations for Future Research In an effort to synthesize the literature on AEC pa rtnering key limitations and areas for future research are identified. The following sections expound on these giving direction and guidance for other researchers. 5.4.1. Limitations The main objective of this study was to synthesize the AEC literature on partn ering using a meta - analytic approach. The goals and objectives for this study are achieved, despite several limitations. One such limitation is a direct result of this literature st ream which does not provide statistical results reporting clear effect size s on variables under consideration in partnering. Given this, a meta - analytic approach was followed in lieu of a traditional meta - analysis to provide guidance on AEC partnering literature. Despite this limitation, the results 82 from this study allows for a c lear interpretation of key partnering drivers and performance outcomes attributable to partnering . Based on the results and limitations the meta - analytic approach used in this study is suggested as a sound methodology in the AEC literature to aggregate fi ndings from multiple studies. Although this study was not able fully deploy the meta - analysis techniques, others may find this approach beneficial to understand links between variables found in AEC research. More importantly, a meta - analytic approach gives great insight as to the dearth of literature available on topics under investigation and can help identify gaps in the knowledge for future research. Based on the taxonomy of partnering , future researchers can begin to focus on key areas integral to succ essful partnering . Key findings from this research synthesis are available for testing and validation via case studies. Also, the synthesis sheds light on the need to collect additional data as it relates to measured performance outcomes. With this type of data, practitioners would gain greater confidence and insights to true partnering implications at both the project and organizational performance levels. For example, only a limited number of studies offer project level data although possibly stemming fro m the confidentiality associated with this information ( Grajek et al., 2000; Gransberg et al., 1999 ) . Despite this, a concerted effort is needed to gain access to project data to report tangible benefits all partnering practitioners can fully interpret. 83 5.4.2. Recommendations for Future Research Two key areas are illuminated from this research synthesis which are available for other to explore . First, much research on AEC partnering stems from quantitative exploration of interorganizational project teams. For example, studies illuminating key success factors are dominate in the literature, yet the findings show that more qualitative studies on these same project teams are ripe with additional information ( Chen & Chen, 2007; Cheng & Li, 2002; Black et al., 2000 ) . Hartman and Bresnen (2011), for instance, argue that collaborative arrangements (i.e., partnering ) are more suited to a more participatory research approach. This means the dynamic nature of construction lends best to a qualitative case study approach i nvestigating the changing and evolutionary interactions among project teams. Utilizing the taxonomy resulting from this research, others are able to hone in on critical variables and test these via case study approaches. Following this case study approach , this research offers a framework on partnering . The framework, with further explorations, may identify genuine or eliminate spurious relationships when tested through qualitative case study experiments. This line of inquiry, furthers the assertion that c warranting longitudinal investigation (Hartman and Bresnen, 2011). Given this, studies imploring socio - psychological theories are more beneficial to understand partnering contextually, while also filling the gap in qualitative research into interorganizational partnering literature. 84 The second future direction from this research is the need for more quantitative results which are more malleable . Meaning, presenting findings which are re laxed for extrapolation of project performance or statistical inference data to make comparisons across studies. Since the initiation of this research stream only a limited number of studies attempt to offer guidance as to the project level benefits of par tnering. Although difficult, future researchers may ease this comparison by providing several additional markers. First, by clearly pointing out the construction sector under investigation other researchers would, then, be able to ascertain the types of pr ojects from which similar attributes are available. This would help relax the concern on making comparisons across project performance outcomes that result from the uniqueness of construction. Second, stronger metrics are needed to gain access to project p erformance indicators. Perhaps, other researchers can follow original project performance metrics first attend to by Grajek et al., ( 2000 ) and Gransberg et al., ( 1999 ) clearly suggesting cost and schedule performance variables. Again, a qualitative or even a mixed methods approach might spawn lif e into this line of AEC partnering literature through case study. 5.5. Conclusion Partnering in the AEC industry has existed since the early 1980s and remains an elusive concept in its true implications on project succe ss and performance outcomes. Many studies examining successful partnering are completed, yet are dispersed on specific benefits that are expected from partnering. Therefore, this st udy aimed not only to identify the various attributes on partnering, but to develop a sound taxonomy aggregat ing key variables into groups. To achieve this, a meta - analytic approac h was followed to synthesize 173 partnering studies published 85 over the last 25 years. From this data, the research er was able to aggregate , analyze, a nd present findings pertaining to the AEC partnering literature. Although a statistical analysis was afforded for only a few variables, the qualitative evidence from this study is very detailed in its depiction on our current state of partnering research in AEC literature. 86 A PPENDICES 87 APPENDIX A: PARTNERING STUDIES RESULTING FROM DATA COLLECTION AND SCREENING. Table 14 : Partnering Studies Resulting from Data Collection a nd Screening s orted by Source of Publication . Au thor(s) Title Source of Publication Year Cheung, S., Suen, H., and Cheung, K. An automated partnering monitoring system - Partnering Temperature Index Automation in Construction 2003 Yeomans, S., Bouchlaghem, N., and El - Hamalawi, A. An evaluation of curren t collaborative prototyping practices within the AEC industry Automation in Construction 2006 Yeung, J., Chan, A., Chan, D., and Li, L. Development of a partnering performance index (PPI) for construction projects in Hong Kong: a Delphi Study Automation in Construction 2007 Yeung, J., Chan, A., and Chan, D. A computerized model of measuring and benchmarking the partnering performance of construction projects Automation in Construction 2009 Carr, F., Hurtado, K., Lancaster, C., Markert, C., and Tucker, P . Partnering in Construction: A Practical Guide to Project Success Book 1999 Bennett, J., and Peace, S. Partnering in the Construction Industry - A Code of Practice for Strategic Collaborative Working Book 2006 Mosey, D. Early Contractor Involvement in Building Procurement Book 2009 Cheng, E., Li, H., Love, P., and Irani, Z. Strategic alliances: a model for establishing long - term commitment to inter - organizational relations in construction Building and Environment 2004 Chan, A, Chan, D., Fan, L., L am, P., and Yeung, J. Partnering for construction excellence - A reality or myth? Building and Environment 2006 Cheng, E., and Li, H. Application of ANP in process models: An example of strategic partnering Building and Environment 2007 Wood , G., McDerm ott, P., and Swan, W. The ethical benefits of trust - based partnering: the example of the construction industry Business Ethics: A European Review 2002 Hughes, D., Williams, T., and Ren, Z. Differing perspectives on collaboration in construction Construct ion Innovation 2012 Bresnen, M., and Marshall, N. Partnering in construction - a critical review of issues, problems and dilemmas Construction Management and Economics 2000 Bresnen, M., and Marshall, N. Building partnerships: case studies of client - contr actor collaboration in the UK construction industry Construction Management and Economics 2000 Bresnen, M., and Marshall, N. Motivation, commitment and the use of incentives in partnerships and alliances Construction Management and Economics 2000 Kwan, A ., and Ofori, G. Chinese culture and successful implementation of partnering in Singapore's construction industry Construction Management and Economics 2001 88 Table 1 4 ) : Partnering Studies Resulting from Data Collection a nd Screening sorted by Sour ce of Publication . Author(s) Title Source of Publication Year Chan, A., Chan, D., and Ho, K. An empirical study on the benefits of construction partnering in Hong Kong Construction Management and Economics 2003 Wood, G., and Ellis, R. Main contractor exp eriences of partnering relationships on UK construction projects Construction Management and Economics 2005 Phua, F. When is construction partnering likely to happen? An empirical examination of the role of institutional norms Construction Management and Economics 2006 Eriksson, P.E., Pesamaa, O. Modelling procurement effects on cooperation Construction Management and Economics 2007 Mason, J. The views and experiences of specialist contractors on partnering in the UK Construction Management and Economics 2007 Kaluarachchi, Y., and Jones, K. Monitoring of a strategic partnering process: the Amphion experience Construction Management and Economics 2007 Yeung, J., Chan, A., and Chan, D. Establishing quantitative indicators for measuring the partnering perf ormance of construction projects in Hong Kong Construction Management and Economics 2008 Doloi, H. Relational partnerships: the importance of communication, trust and confidence and joint risk management in achieving project success Construction Managemen t and Economics 2009 Lau, E., and Rowlinson, S. Interpersonal trust and inter - firm trust in construction projects Construction Management and Economics 2009 Bresnen, M. Living the dream? Understanding partnering as emergent practice Construction Manageme nt and Economics 2009 Lai, I., and Lam, F. Perceptions of various performance criteria by stakeholders in the construction sector in Hong Kong Construction Management and Economics 2010 Bandefelt, U. I trust you, I trust you not: a longitudinal study of control mechanisms in incentive contracts Construction Management and Economics 2010 Eriksson, P.E. Partnering: what it is, when should it be used, and how should it be implemented Construction Management and Economics 2010 Bresnen, M. Keeping it real? Constituting partnering through boundary objects Construction Management and Economics 2010 89 Table ) : Partnering Studies Resulting from Data Collection a nd Screening sorted by Source of Publication . Author(s) Title Source of Publication Year T abish, S., and Jha, K. Identification and evaluation of success factors for public construction projects Construction Management and Economics 2011 Lahdenpera, P. Making sense of the multi - party contractual arrangements of project partnering, project alli ancing and integrated project delivery Construction Management and Economics 2012 Bubshait, A. Partnering: An innovative and effective project organization concept Cost Engineering 2001 Hartmann, A., and Bresnen, M. The emergence of partnering in constr uction practice: an activity theory perspective Engineering Project Organization Journal 2013 Loraine, R. Project specific partnering Engineering, Construction and Architectural Management 1993 Li, H., Cheng, E., and Love, P. Partnering research in cons truction Engineering, Construction and Architectural Management 2000 Fortune, C., and Setiawan, S. Partnering practice and the delivery of construction projects for Housing Associations in the Uk Engineering, Construction and Architectural Management 2 006 Ingirige, B., and Sexton, M. Alliances in construction: Investigating initiatives and barriers for long - term collaboration Engineering, Construction and Architectural Management 2006 Eriksson, P.E., and Laan, A. Procurement effects on trust and cont rol in client - contractor relationships Engineering, Construction and Architectural Management 2007 Jones, K., and Kaluarachchi, Y. Operational factors affecting strategic partnering in UK social housing Engineering, Construction and Architectural Manage ment 2007 Swan, W., and Khalfan, M. Mutual objective setting for partnering in the public sector Engineering, Construction and Architectural Management 2007 Eriksson, P.E., Nilsson, T., and Atkin, B. Client perceptions of barriers to partnering Engine ering, Construction and Architectural Management 2008 90 Table ) : Partnering Studies Resulting from Data Collection a nd Screening sorted by Source of Publication . Author(s) Title Source of Publication Year Phillips, S., Martin, J., Dainty, A., a nd Price, A. Analysis of the quality attributes used in establishing best value tenders in the UK social housing sector Engineering, Construction and Architectural Management 2008 Eriksson, P.E., Atkin, B., and Nilsson, T. Overcoming barriers to partneri ng through cooperative procurement procedures Engineering, Construction and Architectural Management 2009 Davis, P., and Love, P. Alliance contracting: Added value through relationship development Engineering, Construction and Architectural Management 2 011 Hughes, D., Williams, T., and Ren, Z. Is incentivisation significant in ensuring successful partnered projects? Engineering, Construction and Architectural Management 2012 Akintoye, A., McIntosh, G., and Fitzgerald, E. A survey of supply chain colla boration and management in the UK construction industry European Journal of Purchasing & Supply Management 2000 Zuo, J., Chan, A., Zhao, Z., Zillante, G., and Xia, B. Supporting and impeding factors for partnering in construction: a China study Facilitie s 2013 Ning, Y., and Ling, Y. Comparative study of drivers of and barriers to relational transactions faced by public clients, private contractors and consultants in public projects Habitat International 2013 Larson, E. Partnering on Construction Project s: A Study of the Relationship Between Partnering Activities and Project Success IEEE Transactions on Engineering Management 1997 Construction Industry Institute (CII) Meeting the Challenges of the Future Industry Report 1989 Construction Industry Instit ute (CII) In Search of Partnering Excellence Industry Report 1991 Associated General Contractors (AGC) Partnering - A Concept for Success Industry Report 1991 Construction Industry Institute (CII) Partnering II - A Model for Excellence Industry Report 19 96 Gransberg, D., Reynolds, H., Boyd, J., and Gokdogan, G. Evaluation of TxDOT Partnering Plus Program Industry Report 1998 Rogge, D., Griffith, P., and Hutchins, W. Improving the Effectiveness of Partnering Industry Report 2002 91 Table ) : Part nering Studies Resulting from Data Collection a nd Screening sorted by Source of Publication . Author(s) Title Source of Publication Year Polkinghorn, B., La Chance, R., and La Chance, H. "An analysis of the Maryland Department of Transportation State Highw partnering program and process" Industry Report 2006 U.S. Army Corps of Engineers Partnering: A Tool for USACE, Engineering, Construction, and Operations Industry Report 2010 Caltrans Caltrans Subcommittee Meeting Report Industry Repo rt 2011 Wong, A. Partnering in construction industry: Hong Kong context International Journal of Project Management 1997 Bower, D, Crabtree, E., and Koegh, W. Rhetorics and realities in new product development in the subsea oil industry International Jo urnal of Project Management 1997 Black, C., Akintoye, A., and Fitzgerald, E. An analysis of success factors and benefits of partnering in construction International Journal of Project Management 2000 Boddy, D., and MacBeth, D. Prescriptions for managi ng change: A survey of their effects in projects to implement collaborative working between organisations International Journal of Project Management 2000 Li, H., Cheng, E., Love, P., Irani, Z. Co - operative benchmarking: a tool for partnering excellence in construction International Journal of Project Management 2001 Ng, S., Rose, T., Mak, M., and Chen, S. Problematic issues associated with project partnering - the contractor perspective International Journal of Project Management 2002 Bresnen, M., and Marshall, N. The engineering or evolution of co - operation? A tale of two partnering projects International Journal of Project Management 2002 Naoum, S. An overview into the concept of partnering International Journal of Project Management 2003 Che ung, S., Ng, T., Wong, S., and Suen, H. Behavioral aspects in construction partnering International Journal of Project Management 2003 Packham, G., Thomas, B., and Miller, C. Partnering in the house building sector: a view International Journal of Project Management 2003 Kadefors, A. Trust in project relationships inside the black box International Journal of Project Management 2004 Bayliss, R., Cheung, S., Suen, H., and Wong, S. Effective partnering tools in construction: a case stud y on MTRC TKE contract 604 in Hong Kong International Journal of Project Management 2004 92 Table ) : Partnering Studies Resulting from Data Collection a nd Screening sorted by Source of Publication . Author(s) Title Source of Publication Year Shek - Pui Wong, P., and Cheung, S. Trust in construction partnering; views from parties of the partnering dance International Journal of Project Management 2004 Beach, R., Webster, M., and Campbell, K. An evaluation of partnership development in the construc tion industry International Journal of Project Management 2005 Bresnen, M. Deconstructing partnering in project - based organisation: Seven pillars, seven paradoxes and seven deadly sins International Journal of Project Management 2007 Lu, S., and Yan, H . A model for evaluating the applicability of partnering in construction International Journal of Project Management 2007 Lu, S., and Yan, H. An empirical study on incentives of strategic partnering in China: Views from construction companies Internatio nal Journal of Project Management 2007 Chen, W., and Chen, T. Critical success factors for construction partnering in Taiwan International Journal of Project Management 2007 Alderman, N. and Ivory, C. Partnering in major contacts: Paradox and metaphor International Journal of Project Management 2007 Kadefors, A., Bjorlingson, E., and Karlsson, A. Procuring service innovations: Contractor selection for partnering projects International Journal of Project Management 2007 Errasti, A., Beach, R., Oyarbi de, A., and Santos, J. A process for developing partnerships with subcontractors in the construction industry: An empirical study International Journal of Project Management 2007 Pesamaa, O, Eriksson, P.E., and Hair, J. Validating a model of cooperative procurement in the construction industry International Journal of Project Management 2009 Tang, L., Shen, Q., and Cheng, E. A review of studies on Public - Private Partnership projects in the construction industry International Journal of Project Managem ent 2010 Yeung, J., Chan, A., and Chan, D. Defining relational contracting from the Wittgensteing family - resemblance philosophy International Journal of Project Management 2012 Meng, X. The effect of relationship management on project performance in co nstruction International Journal of Project Management 2012 Ling, F., Ong, S., Ke, Y., Wang, S., and Zou, P. Drivers and barrier to adopting relational contracting practices in public projects: Comparative study of Beijing and Sydney International Journa l of Project Management 2014 93 Table ) : Partnering Studies Resulting from Data Collection a nd Screening sorted by Source of Publication . Author(s) Title Source of Publication Year Smith, A., and Culp, G. Continuous Partnering Helps Ensure Proj ect Success Journal of American Water Works Association 2000 Voyton, V., and Siddiqi, K. Partnering: Tool for Construction Claims Reduction Journal of Architectural Engineering 2004 Raziszewska - Zielina, E. Fuzzy Control of Partnering Relations of a Const ruction Enterprise Journal of Civil Engineering and Management 2011 Pocock, J., Hyun, C., Liu, L., and Kim, M. Relationship between project interaction and performance indicators Journal of Construction Engineering and Management 1996 Puddicombe, M. Desi gners and contractors: Impediments to integration Journal of Construction Engineering and Management 1997 Conley, M., and Gregory, R. Partnering on Small Construction Projects Journal of Construction Engineering and Management 1999 Gransberg, D., Dillo n, W., Reynolds, H., and Boyd, J. Quantitative Analysis of Partnered Project Performance Journal of Construction Engineering and Management 1999 Drexler, J., and Larson, E. Partnering: Why Project Owner - Contractor Relationships Change Journal of Construc tion Engineering and Management 2000 Gladola, C. and Sheedy, W. Partnering on Defense Contracts Journal of Construction Engineering and Management 2002 Cheng, E., and Li, H. Development of a Practical Model of Partnering for Construction Projects Journa l of Construction Engineering and Management 2004 Chan, A., Chan, D., Chiang, Y., Tang, B., Chan, E., and Ho, K. Exploring Critical Success Factors for Partnering in Construction Projects Journal of Construction Engineering and Management 2004 94 Table 14 ) : Partnering Studies Resulting from Data Collection a nd Screening sorted by Source of Publication . Author(s) Title Source of Publication Year Wong, P., Cheung, S., and Ho, P. Contractor as Trust Initiator in Construction Partnering - Prisoner's Dil emma Perspective Journal of Construction Engineering and Management 2005 Tang, W., Duffield, C., and Young, D. Partnering Mechanisms in Construction: An Empirical Study on the Chinese Construction Industry Journal of Construction Engineering and Managemen t 2006 Anvuur, A., and Kumaraswamy, M. Conceptual model of partnering and alliancing Journal of Construction Engineering and Management 2007 Eriksson, P.E. Procurement Effects on Coopetition in Client - Contractor Relationships Journal of Construction Engi neering and Management 2008 Eom, C., Yun, S., and Paek, J. Subcontractor evaluation and management framework for strategic partnering Journal of Construction Engineering and Management 2008 Johnson, T., Feng, P., Sitzabee, W., and Jernigan, M. Federal Ac quisition Regulation Applied to Alliancing Contract Practices Journal of Construction Engineering and Management 2013 Grajek, K, Gibson, G, Tucker, R., Partnered Project Performance in Texas Department of Transportation Journal of Infrastructure Systems 2 000 Anderson, L. and Polkinghorn, B. Efficacy of Partnering on the Woodrow Wilson Bridge Project: Empirical Evidence of Collaborative Problem - Solving Benefits Journal of Legal Affairs and Dispute Resolution in Engineering and Construction 2011 Cook, E. and Hancher, D. Partnering: Contracting for the Future Journal of Management in Engineering 1990 Weston, D. and Gibson Jr., E. Partnering - Project Performance in US Army Corps of Engineers Journal of Management in Engineering 1993 Harback, H., Basham, D ., and Buhts, R. Partnering paradigm Journal of Management in Engineering 1994 Abudayyeh, O. Partnering: a team building approach to quality construction management Journal of Management in Engineering 1994 95 Table ) : Partnering Studies Result ing from Data Collection a nd Screening sorted by Source of Publication . Author(s) Title Source of Publication Year Crowley, L., and Karim, A. Conceptual Model of Partnering Journal of Management in Engineering 1995 Ellison, S., and Miller, D. Beyond AD R: working toward synergistic strategic partnership Journal of Management in Engineering 1995 Larson, E. Project Partnering: Results of Study of 280 Construction Projects Journal of Management in Engineering 1995 Bates, G. I don't believe in change ju st for the sake of change Journal of Management in Engineering 1996 Miles, R. Twenty - first century partnering and the role of ADR Journal of Management in Engineering 1996 Nielsen, D. Partnering for performance Journal of Management in Engineering 199 6 Bates, G. Garden of Managerial Delights Journal of Management in Engineering 1996 Crane, T., Felder, J., Thompson, P., Thompson, M., and Sanders, S. Partnering Process Model Journal of Management in Engineering 1997 Love, S. Subcontractor partnering : I'll believe it when I see it Journal of Management in Engineering 1997 Lazar, F. Partnering - New benefits from peering inside the black box Journal of Management in Engineering 1997 Brooke, K., and Litwin, G. Mobilizing the partnering process Journal of Management in Engineering 1997 Gardiner, P., and Simmons, E. Conflict in Small - and Medium - Sized Projects: Case of Partnering To The Rescue Journal of Management in Engineering 1998 Crane, T., Felder, J., Thompson, P., Thompson, M., and Sanders, S. Partnering Measures Journal of Management in Engineering 1999 Thompson, P., and Sanders, S. Partnering Continuum Journal of Management in Engineering 1999 96 Table ) : Partnering Studies Resulting from Data Collection a nd Screening sorted by Sou rce of Publication . Author(s) Title Source of Publication Year Cheng, E., Li, H., and Love, P.E.D. Establishment of critical success factors for construction partnering Journal of Management in Engineering 2000 DeVilbiss, C., and Leonard, P. Partnering is the foundation of a Learning Organization Journal of Management in Engineering 2000 Lazar, F. Project Partnering: Improving the Likelihood of Win/Win Outcomes Journal of Management in Engineering 2000 Kumaraswamy, M., and Matthews, J. Improved subco ntractor selection employing partnering principles Journal of Management in Engineering 2000 Cheng, E., Li, H., Drew, D., and Yeung, N. Infrastructure of partnering for construction projects Journal of Management in Engineering 2001 Pena - Mora, F., and Harpoth, N. Effective partnering in innovative procured multicultural project Journal of Management in Engineering 2001 Cheng, E., and Li, H. Construction Partnering Process and Associated Critical Success Factors: Quantitative Investigation Journal of M anagement in Engineering 2002 Chan, A., Chan, D., and Ho, K. Partnering in Construction: Critical Study of Problems for Implementation Journal of Management in Engineering 2003 Wong, P., and Cheung, S. Structural Equation Model of Trust and Partnering Success Journal of Management in Engineering 2005 Maturana, S., Alarcon, L., Gazmuri, P., and Vrsalovic, M. On - site subcontractor evaluation method based on lean principles and partnering practices Journal of Management in Engineering 2007 Chan, A, Ch an, D., Fan, L., Lam, P., and Yeung, J. Achieving Partnering Success through an Incentive Agreement: Lessons Learned from an Underground Railway Extension Project in Hong Kong Journal of Management in Engineering 2008 Eriksson, P.E., and Nilsson, T. Part nering the Construction of a Swedish Pharmaceutical Plant: Case Study Journal of Management in Engineering 2008 Cho, K., Hyun, C., Koo, K., and Hong, T. Partnering process model for public - sector fast - track design - build projects in Korea Journal of Manag ement in Engineering 2010 Hong, Y., Chan, D., Chan, A., and Yeung, J. Critical Analysis of Partnering Research Trend in Construction Journals Journal of Management in Engineering 2012 97 Table ) : Partnering Studies Resulting from Data Collectio n a nd Screening sorted by Source of Publication . Author(s) Title Source of Publication Year Doloi, H. Empirical Analysis of Traditional Contracting and Relationships Agreements for Procuring Partners in Construction Projects Journal of Management in Engin eering 2013 Chen, T., and Kao, C. A Study of Identifying Success Variables for Construction Partnering via S EM Framework Journal of Marine Science and Technology 2010 Tang, W., Qiang, M., Duffield, C., Young, D., and Lu, Y. Enhancing Total Quality Manag ement by Partnering in Construction Journal of Professional Issues in Engineering Education and Practice 2009 Bygballe, L., Jahre, M., and Sward, A. Partnering relationships in construction: A literature review Journal of Purchasing & Supply Management 2010 Gadde, L., and Dubois, A. Partnering in the construction industry - Problems and opportunities Journal of Purchasing & Supply Management 2010 Laan, A., Noorderhaven, N., Voordijk, H., and Dewulf, G. Building trust in construction partnering projects: An exploratory case - study Journal of Purchasing & Supply Management 2011 Le - Hoai, L., Lee, Y., and Son, J. Partnering in Construction: Investigation of Problematic Issues for Implementation in Vietnam Korean Society of Civil Engineering Journal of Civil E ngineering 2010 Saunders, K., and Mosey, D. PPC 2000: Association of consultant architects standard form of project partnering contract Lean Construction Journal 2005 Keil, J. How Partnering Benefits the Construction Process Pipeline & Gas Journal 2007 Adnan, H., Shamsuddin, S., Supardi, A., and Ahmad, N. Conflict Prevention in Partnering Projects Procedia - Social and Behavioral Sciences 2012 Barnes, M. Civil engineering management in the Industrial Revolution Proceedings of the Institute of Civil Eng ineers: Civil Engineer 2000 Gellatly, G., Burtwistle, P., and Baldwin, A. Groupware the key to successful partnering: a case study Proceedings of the Institute of Civil Engineers: Civil Engineer 2000 Cathcart, A. Channel Tunnel Rail Link: a contract part nership Proceedings of the Institute of Civil Engineers: Civil Engineer 2003 98 Table ) : Partnering Studies Resulting from Data Collection a nd Screening sorted by Source of Publication . Author(s) Title Source of Publication Year Hartshorne, D., a nd Cadman, P. Storm Flood Relief Tank - Westbourne Avenue, Rhyl. Proceedings of the Institute of Civil Engineers: Municipal Engineer 1999 Edmonds, M., and Hogan, M. Millennium coastal park: Llanelli land bridges Proceedings of the Institute of Civil Engin eers: Municipal Engineer 2000 Crane, A. Local authorities achieve best value through partnering and demonstration Proceedings of the Institute of Civil Engineers: Municipal Engineer 2001 Stephens, M., and Thomas, D. Partnership: a marriage made in Kent Proceedings of the Institute of Civil Engineers: Municipal Engineer 2001 Cunningham, L., and Pomfret, M. Partnering contracts in practice at Blackpool, UK Proceedings of the Institute of Civil Engineers: Municipal Engineer 2007 Gullick, D., Cairns, R., a nd Pearson - Kirk, D. Application of partnering principles to a framework contract Proceedings of the Institute of Civil Engineers: Municipal Engineer 2007 Harwood, K., and Follett, B. Warwickshire - Arup partnership: The first five years Proceedings of the Institute of Civil Engineers: Municipal Engineer 2007 Rankin, J., Jameson, P., Yarwood, N. NEC X12 at the heart of Worcestershire Highways Proceedings of the Institute of Civil Engineers: Municipal Engineer 2007 Turner, J. Pearce, S., Fenton, M., and Sim s, B. Effective partnering remediating the former Avenue coking works Proceedings of the Institute of Civil Engineers: Municipal Engineer 2007 Aggus, S. and Hiscocks, E. Coventry framework partnership Proceedings of the Institute of Civil Engineers: Muni cipal Engineer 2007 Orr, J. The ruby bay bypass - the project that pushed the boundaries Proceedings of the Institute of Civil Engineers: Municipal Engineer 2012 99 Table ) : Partnering Studies Resulting from Data Collection a nd Screening sorted by Source of Publication . Author(s) Title Source of Publication Year Cowan, Charles, Clifford Gray, and Erik Larson. Project partnering Project Management Institute 1992 Moore, Carl, Donald Mosley, and Michelle Slagle. Partnering guidelines for win - win project management Project Management Institute 1992 Romancik, D. Partnership toward improvement Project Management Institute 1995 Schmader, K. and Gibson, G. Partnered project performance in US naval facilities engineering command Project Management In stitute 1995 Back, W. and Sanders, S. Partnering in a unit price environment Project Management Institute 1996 Larson, E., and Drexler, J. Barriers to project partnering: report for the firing line Project Management Institute 1997 Thomas, S., Tucker, R ., and Kelly, W. Compass: An Assessment Tool for Improving Project Team Communications Project Management Institute 1999 Jiang, J., Klein, G., and Chen, H. The Relative Influence of IS Project Implementation Policies and Project Leadership on Eventual Out comes Project Management Institute 2001 Jiang, J., Klein, G., and Discenza, R. Pre - project partnering impact on an information system project, project team and project management Project Management Institute 2002 Barlow, J. Innovation and learning in com plex offshore construction projects Research Policy 2000 Manley, K. Partnering and Alliancing on Road Projects in Australia and Internationally Road and Transport Research 2002 Humphreys, P., Matthews, J., and Kumaraswamy, M. Pre - construction project par tnering: from adversarial to collaborative relationships Supply Chain Management: An International Journal 2003 Weston, D. An Analysis of Project Performance for Partnering Projects in the U.S. Army Corps of Engineers Thesis 1992 100 APPENDIX B: PARTNERING RESEARCH CODING FORM . Figure 10 : Partnering Research Coding Form . 101 Figure : Partnering Research Coding Form . 102 APPENDIX C: PARTNERING CODING MANUAL Figure 11 : Partnering Coding Manual . 103 104 Fig 105 Figure 11 (C ) : Partnering Coding Manual . 106 Figure 11 (C ) : Partnering Coding Manual . 107 APPEN DIX D : KEY PARTNERING DRIVER CONSTRUCTS AND VARIABLES Table 15 : Key P artnering Driver Constructs a nd Variables . PLANNING / PROCUREMENT VARIABLE RELATIONSHIP # OF TIMES IDENTIFIED Contract language and form of contract PLAN 0 6 + 12 Incentives / Fees / risk - reward/ gainshare - painshare PLAN14 + 12 Financial security/stability PLAN10 + 9 Poor understanding of the concept PLAN29 - 9 Availability of resources PLAN 0 1 + 8 Partnering experience PLAN27 + 8 Shared Equity PLAN34 + 7 Contract size or appropriate project size PLAN 0 7 + 6 Good cultural fit PLAN11 + 6 High cost to adopt par tnering PLAN12 - 6 Partnering agreement PLAN26 + 6 Previous work experience with other members PLAN30 + 6 Technical expertise PLAN37 + 6 Clear and Compatible goals PLAN 0 3 + 4 Time required to develop PLAN38 + 4 Competent PLAN 0 4 + 3 Incompatible or ganizational cultures PLAN15 - 3 Incompatible project type PLAN16 - 3 Joint contractor selection PLAN17 + 3 Joint project charter PLAN18 + 3 Owner capacity and organization PLAN25 + 3 Past negative experience PLAN28 - 3 Prequalification PLAN31 + 3 Reputation PLAN33 + 3 Broad partnering team PLAN 0 2 + 2 Equality among partnering participants PLAN 0 8 + 2 Fair profit assumptions PLAN 0 9 + 2 High ethical standards PLAN13 + 2 Joint specifications PLAN19 + 2 Lack of client initiatives in RC practice PL AN20 - 2 Lack of knowledge of relational approach PLAN22 - 2 Limited bid invitations PLAN23 - 2 Project duration PLAN32 + 2 Strategic benefits unclear PLAN35 + 2 Cooperative skills PLAN 0 5 + 1 Lack of common goals PLAN21 - 1 Low - bid mentality PLAN24 - 1 Supervision and management characteristics PLAN36 + 1 TOTAL 160 108 Table 15 (C ) : Key P artnering Driver Constructs a nd Variables . RELATIONSHIP ORIENTED VARIABLE RELATIONSHIP TOTAL Mutual trust REL24 + 21 Mutual goals and objectives co mmunicated REL23 + 14 Team commitment REL28 + 12 Commitment REL 0 3 + 7 Equal power/empowerment REL11 + 6 Positive Attitude REL25 + 6 Integrated team REL14 + 5 Mutual interest REL22 + 5 Acting consistent with objectives REL 0 1 + 4 Honesty REL13 + 4 L ack of trust REL20 - 4 Unity REL32 + 4 Win / win motivation REL33 + 4 Common vision REL 0 5 + 3 Company wide acceptance REL 0 6 + 3 Concerns about opportunistic behavior REL 0 7 - 3 Dedicated team REL 0 9 + 3 Lack of acceptance as long - term business strat egy REL18 - 3 Align relationships with objectives REL 0 2 + 2 Integrity REL15 + 2 Inter - personal/cultural clash REL16 - 2 Teamwork REL29 + 2 Timely responsiveness REL30 + 2 Unenthusiastic participation REL31 - 2 Commitment to win/win attitude REL 0 4 + 1 Cooperation REL 0 8 + 1 Ego/personality indifference REL10 - 1 Fear of unknown REL12 - 1 Promise - keeping REL17 + 1 Lack of experience REL19 - 1 Management team lack of knowledge REL21 - 1 Perceived satisfaction of partners' expectations REL26 - 1 R eliability REL27 + 1 TOTAL 132 109 Table 15 (C ) : Key P artnering Driver Constructs a nd Variables . PROCESS ORIENTED VARIABLE RELATIONSHIP TOTAL Top management commitment/support PROC69 + 20 Effective communication PROC19 + 16 Open communi cations PROC47 + 16 Workshops PROC72 + 14 Early involvement of designer / contractor / subcontractors PROC17 + 13 Regular monitoring of partnering process (Benchmarking) PROC54 + 12 Team building session PROC68 + 11 Free flow of information PROC27 + 10 Facilitator / Partnering champion / Neutral third party PROC23 + 8 Lack of training and guidance in the arrangement PROC39 - 8 Clear understanding of objectives PROC 0 3 + 7 Commitment to continuous improvement PROC 0 5 + 7 Long - term relationships PRO C43 + 6 Clear definition and lines of responsibility PROC 0 2 + 5 Integrated information systems PROC30 + 5 Problem resolution process PROC48 + 5 Problem - solving process PROC49 + 5 Adopt Alternative Dispute Resolutions (ADR) PROC 0 1 + 4 Creativity and innovation PROC12 + 4 Formation at design stage PROC26 + 4 Long - term commitment PROC41 + 4 More frequent meetings PROC46 + 4 Respect and appreciation of the system PROC58 + 4 Total cost perspective PROC70 + 4 Commitment to quality PROC 0 6 + 3 Flexibi lity to change PROC25 + 3 Lack of appropriate information technology PROC35 - 3 Lack of empowerment in client's representatives PROC36 - 3 Long - term perspective PROC42 + 3 Questioning attitudes PROC51 + 3 Conflict identification and resolution strateg y PROC 0 7 + 2 Consultants used PROC 0 8 + 2 Effective coordination PROC10 + 2 Failure to compromise PROC11 - 2 Design criteria established early on PROC14 + 2 Eliminating non - value added activities / value engineering PROC21 + 2 Establishment and comm unication of conflict resolution strategy PROC22 + 2 Joint problem solving PROC33 + 2 Joint project office PROC34 + 2 Lack of supply chain partnering PROC37 - 2 Lack of top management support PROC38 - 2 Learning climate PROC40 + 2 Low commitment of p artners PROC44 - 2 Provisions for continuous improvement PROC50 + 2 Risk allocation PROC53 + 2 Resource sharing and open books PROC59 + 2 Reward system for meeting objectives PROC60 + 2 110 Table 15 (C ) : Key P artnering Driver Constructs a nd Variables . PROCESS ORIENTED VARIABLE RELATIONSHIP TOTAL Target cost set early PROC67 + 2 Cost driven PROC 0 9 + 1 Design / supplier based onsite PROC13 + 1 Detailed plan for operating critical path PROC15 + 1 Early implementation PROC16 + 1 Education and train ing PROC18 + 1 Effective process for change orders PROC20 + 1 Fear of micromanagement PROC24 - 1 Funding plan PROC28 + 1 Holding design information in common PROC29 + 1 Involvement of participants in design process PROC31 + 1 Joint business planning PROC32 + 1 Closer links between demand/supply PROC 0 4 + 1 Manpower development PROC45 + 1 Quick decision making PROC52 + 1 Relationships are effectively managed PROC55 + 1 Reliable cost data PROC56 + 1 Reluctance to commit extra resources PROC57 - 1 Schedule management on milestones PROC61 + 1 Selection of items for early procurement PROC62 + 1 Shared resources PROC63 + 1 Standardized resources PROC64 + 1 Staff continuity and availability PROC65 + 1 Strategy for checking resources / facilities PR OC66 + 1 Work processes established to achieve discipline and goals PROC71 + 1 TOTAL 274 111 APPENDIX E : EXTERNAL MODERATOR CONSTRUCT AND VARIABLES Table 16 : External Moderator Construct a nd Variables . EXTERNAL MODERAT ORS VARIABLE RELATIONSHIP TOTAL Bureaucratic public client organization EXT 0 1 - 6 Stringent public rules, regulations and laws EXT10 - 4 Conservative industry culture inhibits changes (status quo) EXT 0 4 - 3 Client only has occasional need for proj ect development EXT 0 2 - 2 Need to avoid allegations of corruption EXT 0 7 - 2 Public sector accountability concerns EXT 0 8 - 2 Commercial pressures comprised partnering attitude EXT 0 3 - 1 Flexibility restricted by bidding approach EXT 0 5 - 1 Local labor a nd community benefits EXT 0 6 - 1 Public sentiments EXT 0 9 - 1 TOTAL 23 112 APPENDIX F : PERFORMANCE OUTCOME CONSTRUCT S AND VARIABLES Table 17 : Performance Outcome Constructs a nd Variables . COST PERFORMANCE VARIABLE TOTAL Meeting budget cost targets COSTP11 10 Cost savings COSTP 0 3 7 Reduce additional expenses COSTP16 6 Claims cost percent of original cost COSTP 0 4 5 Increased opportunity for innovation (Cost Savings) COSTP 0 7 4 Cost growth per change order COS TP 0 2 3 Liquidated damage cost as percent of total cost COSTP 0 9 3 Reduce total project cost COSTP19 3 Reduced cost COSTP21 3 Reduced paperwork COSTP22 3 Change order cost COSTP 0 1 2 Dispute cost percent of original cost COSTP 0 5 2 Improve cost savings for client COSTP 0 6 2 Liquidated damage cost as percent of change order COSTP 0 8 2 Maximize resource utilization COSTP10 2 Number of change orders COSTP12 2 Percent cost growth per change order COSTP13 2 Percent of projects with deducts COSTP14 2 Perce nt of projects with liquidated damages COSTP15 2 Reduce cost of changing partner in project COSTP17 2 Reduce public client's admin burden COSTP18 2 Reduced admin cost - defensive case building COSTP20 1 Value engineering savings COSTP23 1 TOTAL 71 SCHEDULE PERFORMANCE VARIABLE TOTAL Meeting schedule targets SCHP 0 6 12 Reduce time in delivering the project SCHP 0 9 6 Better productivity SCHP 0 1 5 Project schedule growth SCHP 0 8 4 Time variance SCHP11 3 Improved construction time SCHP 0 2 2 I ntegrated solutions to improve efficiency SCHP 0 4 2 Liquidated damage percent of total contract days SCHP 0 5 2 Percent of additional days granted SCHP 0 7 2 Improved productivity SCHP 0 3 1 Time SCHP10 1 TOTAL 40 113 Table ) : Performan ce Outcome Constructs a nd Variables . QUALITY / SAFETY PERFORMANCE VARIABLE TOTAL Improve the quality of project QUALP10 14 Environmental issue complaints QUALP 0 6 5 Increase client satisfaction QUALP13 5 Reduce wasted work or re - work QUALP17 5 Imp rove design QUALP 0 8 4 Improve non - conformance reports QUALP 0 9 3 Improved safety performance QUALP11 3 Incident rate QUALP12 3 Achieve better safety performance QUALP 0 1 2 Customer needs QUALP 0 4 2 Increased customer satisfaction QUALP15 2 Quality imp rovements QUALP16 2 Safety QUALP20 2 Better quality design QUALP 0 2 1 Better workmanship QUALP 0 3 1 Design cycle reductions QUALP 0 5 1 Improve collaboration in design QUALP 0 7 1 Increase safety performance QUALP14 1 Reduced engineering rework QUALP18 1 Reduced variations QUALP19 1 TOTAL 59 DISPUTE / LITIGATION PERFORMANCE VARIABLE TOTAL Reduce disputes DISPP 0 3 10 Claim and issue resolution DISPP 0 1 7 Reduced litigation DISPP 0 4 7 Improved conflict resolution strategies DISPP 0 2 3 Reduced risk exposure DISPP 0 5 3 Reduction in monetary claims DISPP 0 6 1 Reduced time to resolve claims DISPP 0 7 1 TOTAL 32 114 Table ) : Performance Outcome Constructs a nd Variables . PROCESS PERFORMANCE VARIABLE TOTAL Improved relationship for project participants PROCP 0 7 16 Long - term trust PROCP17 10 Improved communications PROCP 0 6 9 Continuous improvement increased PROCP 0 3 6 Win - win attitude PROCP20 5 Less adversarial relationship PROCP16 4 Better teamwork PROCP 0 2 3 J oint satisfaction for project participants PROCP15 3 More flexibility to changes PROCP19 3 Better decision making PROCP 0 1 1 Decrease micromanagement PROCP 0 4 1 Improved administration PROCP 0 5 1 Increased involvement of user and end customer PROCP 0 8 1 Increased equality and fairness PROCP 0 9 1 Increased openness and honesty PROCP10 1 Increased participation PROCP11 1 Increased subcontractor contributions to innovation and problem solving PROCP12 1 Increased support for innovation and improvements PRO CP13 1 Improved commitment PROCP14 1 Lower level decision making PROCP18 1 TOTAL 70 115 Table ) : Performance Outcome Constructs a nd Variables . ORGANIZATIONAL PERFORMANCE VARIABLE TOTAL Improved profit margins ORGP1 4 8 Enhance organization's reputation in industry ORGP 0 4 7 Improved corporate culture ORGP13 7 Opportunity to continuously access additional projects ORGP19 6 Build closer relationships with parties ORGP 0 3 5 Achieve continuity with prior developments ORGP 0 1 4 Improve organization's competency ORGP 0 9 4 Improve long - term competitive advantage ORGP10 4 Seize new market opportu ni ties ORGP23 4 Shared risk ORGP25 4 Respond to collaborative culture ORGP20 3 Facilitate creative and innovative approaches ORGP 0 5 2 Increase bidding advantage ORGP 0 8 2 Increased market share ORGP15 2 Obtain support of partner's expertise and knowledge ORGP18 2 Respond to competitors' actions ORGP21 2 Respond to technology changes ORGP22 2 Technical performance ORGP26 2 Assure financing ORGP 0 2 1 Good public relations ORGP 0 6 1 Greater certainty to the contractor ORGP 0 7 1 Improve social responsibilities ORGP11 1 Improved life - cycle cash flow ORGP12 1 Individuals' job satisfaction ORGP16 1 Meet local government/trade/ project requirements ORGP17 1 Serve core customers ORGP24 1 TOTAL 78 116 REFERENCES 117 REFERENCES Abudayyeh, O. 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