Journal of Construction Engineering and Project Management. September 2019. 1-21
https://doi.org/10.6106/JCEPM.2019.9.3.001

# MAIN

• INTRODUCTION

• DEVELOPMENT OF CONCEPTUAL FRAMEWORK AND RESEARCH HYPOTHESIS

•   Interfacial Factors

•   IT Application

•   Project Performance

• RESEARCH METHODOLOGY

•   Demographic Information

•   Data Analysis using PLS-SEM Approach

•   Assessment of Measurement Model

•   Assessment of Structural Model

• MEDIATING EFFECT OF INTERFACE MANAGEMENT

• GLOBAL FIT INDEX OF THE MODEL

• POWER ANALYSIS

• CASE STUDY

•   Development of Template

•   Assessment Results of Firms A & Firm B

• DISCUSSIONS AND PRACTICAL IMPLICATIONS

• CONCLUSIONS

## INTRODUCTION

A project is a cluster of large number of organisations, stakeholders, data/information, technology and other attributes. Each stakeholder/organisations have different objective and interest in viewing the project from their perspective. This difference in opinion gives rise to interfacial conflicts. The poorly managed conflicts weaken the project performance. Thus interface management holds a strategic importance in managing construction projects.

The interface management is the management of common boundaries between people, systems, equipment, or concepts [1]. The management of interfaces can be either internal or external. The management of communication, co-ordination, and responsibility across a common boundary between two organisations, phases, or physical entities which are interdependent is external interface management and internal interface management is managing the problems that often occur among the people, departments, and disciplines rather than within the project team itself [2].

The complex nature of large scale projects makes it monotonous to carry out interface management manually. It requires the support of advanced IT (Information Technology) applications to improve the efficiency of interface management. The emerging IT applications in the construction industry serve to enhance the project performance. The interface management can be enriched by the development of interface management tools with the aid of IT applications.

While many studies have focused on the factors influencing interfacial issues and only a few published studies focused on direct impact on interface management on performance of construction projects. Additionally, prior studies on impact of interface management have not examined the relationship of IT application with interface management in construction and their influence on project performance. The key focus of this research is three fold. The first objective is to develop a framework which gives the quantitative measurement of effectiveness of a project in terms of schedule, cost, quality and safety performance due to implementation of interface management. The second objective is to evaluate the mediating role of interface management in relationship between IT application and project performance. The third objective is to examine the impact of implementation of interface management on interfacial issues influencing factors, namely people/participants, methods/process, resources, documentation, project management & environment.

The analysis of interface management and IT application and their relationships with project performance are based on the survey of construction firms with interface management. A data collection tool was developed to examine the levels of interface management and IT adoption levels in construction firms.

## DEVELOPMENT OF CONCEPTUAL FRAMEWORK AND RESEARCH HYPOTHESIS

A desirable research has been conducted on the adoption of interface management in the construction industry. The prior literatures focused mainly on the factors influencing the interfacial issues, frameworks and methods for implementation of interface management in an organisation. The prior studies indicated the advancement in information and communication technologies should be accompanied with the management process [3].

WBS matrix concept breakdown a project into activity and product oriented structure to identify the interfaces .The interfaces were classified as organisational, technical, geographical, and time interfaces. In the case study of mass rapid transit system, WBS matrix was developed by generating work package sheets and work package reports for each trades like power supply, track works, etc. using excel and the entire interface in each trade was identified to improve the interface management [4].

Integration opportunity assessment tool (IOP Tool) was based on the drivers and hindrance factors for information integration. The benefit and hindrance drivers were classified as “Market/Legal”, “Organisational/process”, “People/Roles/Training”. IOP tool consists of seven worksheets which helps to identify the level of information integration in the project. With the help of these worksheets, the level of information integration in the case studies was measured. If information integration was at low level, the hindrance mitigation plan was proposed [5].

Interface management was categorized as Time interface, Relational interface, Information interface and Environmental interface. Factors influencing these interfaces such as “engineering design and schedule control”, “communication”, “information sharing platform”, “profit”, “law & policy”, “IT ability to apply”, “natural climate”, “contracting strategy” are identified. Using DEMATEL model, design, communication skills, IT ability to apply, information sharing platform & profit were shown to be the most important factors for interface management [6].

A case study was done on the use of the interface management software n-pulse. n-pulse integrates schedule, resources, inventory, BOQ, drawing data and provides proactive information about the schedule delays, cost overruns. The roles of stakeholders like client, PMC, general contractors and subcontractors, consultants in the case study were studied [7].

A model for assessing the relationships among IT application, KM practice adoption and project success was framed. Mediating role of KM practice adoption in relationship between IT application and project performance is studied and also the effect of project type on project success and knowledge management is also studied. This model served as a basic framework for the development of preliminary framework for this research [8].

From the extensive literature reviews it was found that no conceptual model was proposed to measure the influence of interface management on project performance indicators such as cost, schedule, quality and safety and also interrelationships among IT application, interface management, project performance and project benefits was not studied. This study aims at fulfilling these knowledge gaps.

The initial conceptual framework is developed with the aid of literatures on interface management. The initial PLS model comprises 51 attributes for 12 constructs as shown in Figure I The following are the hypothesis set up in PLS path model.

##### FIGURE I.

INITIAL CONCEPTUAL PLS SEM MODEL FOR INTERFACE MANAGEMENT

Interfacial Factors

Based on the relevant literatures, following hypotheses are postulated.

H1.Interface management positively influences people/participants in the project
H2.Interface management positively influences the methods /process involved in the project
H3.Interface management has positively influences resources assigned to the project
H4.Interface management has a positive influence on documentation
H5.Interface management has a positive impact on project management
H6.Interface management has a positive effect on environment

People/participants are considered to be influenced by interface management. The individuals in the organisations perform certain activities which are interrelated and they have to be properly monitored to avoid conflicts and poor project performance. From this perspective people/participants are segmented as communication, coordination, trust, organizational structure, decision making, and financial issues among participants.

The multidisciplinary teams involved in the construction projects implement their own methods/process to attain their objective. The methods/process of individual teams has to be communicated and co-ordinated for the successful outcome of a work. Methods/process focuses on organisation’s potential to choose appropriate construction methods, to resolve the issues in implementing new technologies & methods and ability to resolve construction and assembly problems due to inferior work sequence & handling methods.

Documentation of project information such as shop drawings, change orders, specifications, contracts, etc. is vital to avoid misinterpretations among the stakeholders. Documentation of interface information such as interface registers, interface O&M documents etc. through interface database proves to be crucial for the identification of the characteristics of interfaces and responsibilities of parties involved in the project.

Labor, equipment and material are the conventional resources to support the construction projects. Interface management includes space and information also as resources. The availability of labor, cross functional trained teams, materials, equipment proves to be a difficult task. Inadequate space among labor undertaking concurrent activities, storage of materials, movement of equipment are due to poor interface management.

Interface management is one of the aspects of project management. Inferior interface management affects contractor performance, resource allocation, planning and scheduling, quality performance etc. which are the other aspects of project management. Ignoring interface relationship among the sub-contractors, improper project decomposition, organisation structure, schedule shortening in fast track projects, lack of timely project update are major project management issues due to lack of interface management.

Environment here refers to of construction project. It includes geological, climate and weather conditions, building codes, local laws and regulations, cultural diversity of participants and also integrated work environment.

IT Application

In summary the literatures support the adoption of IT to enhance interface management. This study further extends the previous research by analysing the impact of IT tools on interface management. The following research hypotheses are set up based on the relevant literatures:

H7.IT application positively influences the project’s level of interface management.

DEMATEL (Decision Making Trial and Evaluation Laboratory) model which shows IT ability to apply is the most important factor in interface management of the project [6].

Project Performance

In prior studies the relationship between adoption of systematic Interface management and project performance is investigated and concluded that interface management will positively affect project performance [9, 10]. Interface management process allows early identification of critical interfaces through a structured process which leading to early definitions of cost & schedule issues [11, 12]. Interface management optimizes the design in terms of quality to meet the customer needs [11]. The following hypotheses were proposed based on previous research and the project performance is measured in term of schedule, cost, quality, safety.

H8.Interface management has a positive impact on project’s schedule performance
H9.Interface management has a positive impact on project’s cost performance
H10.Interface management has a positive impact on project’s quality performance
H11.Interface management has a positive impact on project’s safety performance

The above hypotheses and conceptual framework were developed with the help of relevant literatures. The Figure I represents the variables and theoretical framework that links the constructs. This framework validates the association among IT application, interface management, project performance in term of schedule, cost, quality, safety.

## RESEARCH METHODOLOGY

The research was carried out in 3 phases. In the first phase with the help of relevant literatures, factors for interfacial issues were identified and grouped under relevant constructs. The conceptual model for the study was framed with constructs and interfacial attributes.

The second phase comprises the development of the questionnaire with the aid of identified factors and model. Initially for pilot study the questionnaire was distributed to 10 experts in the construction industry. The response from the pilot study validated the effectiveness of the questionnaire. Subsequently necessary update was made in the questionnaire. The construction organisations where a large number of stakeholders, tools, phases involved were spotted, so that it may be ideal to identify the companies with interface management. The questionnaire was then distributed to the targeted organisations.

In the third phase, the data collected from the industry wide survey were filtered for analysis and the data was analysed using PLS-SEM (Partial Least Square- Structural Equation Modelling) technique. The flowchart of reserch methodology is presented in Figure II.

##### FIGURE II.

FLOW CHART OF RESEARCH METHODOLOGY

Demographic Information

The industry wide survey was conducted among top 50 organisations. The questionnaire was distributed to 200 managers in leading multinational companies, who seemed to be more relevant to our research. At the end 101 questionnaires were completely filled. The data were collected through direct interviews and also through online –basis. A data collection tool was developed for this purpose. Thus the final response rate is 51%.

Among the respondents the positions hold by them were, 62% of Engineers (quality, safety, procurement, structural, etc.), 23% of Project Managers, 8% of Construction manager, 3% of Architects, 3% of Contract administrators and 1% of Interface co-ordinators. 67% of respondents holds bachelor degree, 22% having Masters degree, 7% having graduate diploma and 4% having a doctorate degree.

The type of organisations the questionnaire distributed were, 77% of Construction contractors/subcontractors, 9 % of Project management consultants, 7% of Owner/Clients, 6% of Structural consultants, 1% of Architectural consultants. In the pool of organisation responded, 45% of organisations are involved with more than 100 projects, 23% between 51 to 75 projects, 21% less than 50 projects, 11 % between 76 to 100 projects. Some of the organisations are aware of interface management tools. A few interface management tools suggested by the respondents which are used in their organisations are Aconex, CIMS, R construct, Rhythm.

Data Analysis using PLS-SEM Approach

Structural Equation Modeling is a multivariate analysis technique used to examine the interrelationship between multiple variables simultaneously. SEM is the combination of factor analysis and multiple regression analysis to study the relationship between measured variables and latent constructs. SEM is extremely beneficial in investigating the relationship among the significant variables and to solve complex construction problems [13]. SEM serves as appealing tool in the field of construction engineering and management [14]. The SEM analysis can be either covariance based structural analysis or component based structural analysis using Partial Least Square (PLS-SEM). In this research PLS-SEM technique is used for analysis.

The two main components included in the PLS-SEM are: measurement model or outer model and structural model or inner model. The measurement model gives the relationship between latent construct and its indicators and the potential casual dependencies between the endogenous and exogenous constructs is given by structural model. The structural model gives the direct effects (path coefficients) connecting the endogenous and exogenous constructs.

Assessment of Measurement Model

The indicator reliability, convergent validity, discriminant validity are the criteria used for assessing whether the measurement model has acceptable measurement properties [15].The initial model with 51 observed variables is tested using PLS. The indicator reliability is evaluated by examining the outer loadings of the items. Table I shows the final loadings of indicators with value greater than 0.6.

TABLE I. CONSTRUCTS AND INDICATORS OF INTERFACE MANAGEMENT

 Construct Indicators Description of indicators Outer loadings IT APPLICATION AT1 BIM is used to support IM practice. 0.773 AT2 Information sharing platform Tools used to support IM practice. 0.791 AT3 Interface database management system used to support IM practice. 0.750 AT4 Video conference used to support IM practice. 0.709 BT1 Email is used to support IM practice 0.719 BT2 AutoCAD is used to support IM practice 0.653 PEOPLE/ PARTICIPANTS PE2 Lack of negotiation, communication & coordination among relevant stakeholders involved in the project. 0.699 PE3 Lack of personal experience of project teams. 0.761 PE4 Financial issues like Delayed payments, cost disputes, low budget. 0.713 PE5 Lack of trust among project parties 0.738 PE6 Organisation structure 0.633 METHODS/ PROCESS MP1 Ability to predict and resolve problem related to new technology and materials 0.862 MP2 Extent of Mechanisation in the project 0.802 MP3 Ability to design from constructability point. 0.698 RESOURCES RS1 Space conflicts among labor, equipment & materials. 0.808 RS2 Unexpected changes in material, equipment, labor availability & cost. 0.924 DOCUMENTATION DC1 Inadequate specifications and drawings. 0.725 DC2 Level of documentation of interface information. 0.803 DC3 Lack of proper planning and scheduling details. 0.865 DC4 Lack of documentation of change orders, shop drawings. 0.851 PROJECT MANAGEMENT PM1 Lack of proper subcontractor and work packaging system. 0.782 PM2 Responsibilities of interfaces not clearly defined in the contract. 0.750 PM3 Type of contracting strategy adopted doesn't match the project. 0.743 PM4 Insufficient and lack of alignment of work breakdown structure (WBS), Contracting work breakdown structure (CWBS), Cost breakdown structure (CBS), organisation breakdown Structure (OBS). 0.707 PM5 Unclear company standard operating procedures. 0.618 PM6 Multidisciplinary teams are involved 0.649 ENVIRONMENT EN1 Inexperience with local laws and other government regulations and modifications in laws & regulations. 0.771 EN2 Inexperience with building codes, by laws, statutes and other government regulations 0.824 EN3 Unfamiliarity with site geographical and weather conditions. 0.715 SCHEDULE PERFORMANCE SCH1 Each milestone of the project reached as per planned. 0.747 SCH2 Project completed ahead of schedule. 0.75 SCH3 Reduction of stress among the team members. 0.769 SCH4 Disputes among the team members reduced. 0.819 SCH5 Positive impact on social status of our organisation. 0.742 SCH6 Quality of work in the projects has improved. 0.747 COST PERFORMANCE CT1 The cost objectives of the project met. 0.775 CT2 The actual budget of the project is as per planned. 0.798 CT3 Estimated cost has improved the quality of work in our organisation. 0.822 CT4 Economic risks have reduced. 0.83 QUALITY PERFORMANCE QY1 The project quality complied with the owner requirements. 0.841 QY2 Cost due to rework has been reduced. 0.711 QY3 Status and image of organisation have improved. 0.865 SAFETY PERFORMANCE SF1 The project construction and operation complied with all EHS laws and regulations. 0.791 SF2 The recorded accident rate in organisation is low. 0.851 SF3 The recorded injury rate in organisation is low. 0.775 SF4 Safety commitment improved the project key performance indicators like quality, schedule& cost. 0.849 INTERFACE MANAGEMENT- PROJECT BENEFITS PB1 Relationship among the project stakeholders have improved. 0.849 PB2 Project's overall benefit's exceeded the owner's expectation. 0.877 PB3 The project achieved the successful outcome. 0.840

The convergent validity is estimated to measure the extent to which a latent variable shares its indicator variance. It involves measuring the cronbach’s alpha, composite reliability and average variance extracted (AVE). Cronbach’s alpha is a measure of internal consistency and reliability. The internal consistency is found to be good when alpha ranges from 0.7 to 0.9 [16]. The composite reliability is same as cronbach’s alpha except that it takes into account that indicators have different loadings. The cutoff value of composite reliability is 0.6 [17]. Table II shows that all indicators possess Cronbach’s alpha greater than 0.7 and composite reliability greater than 0.6. AVE is the criterion for convergent validity and its cut off value is suggested to be greater than 0.5 (i.e., at least 50% of variances captured by latent variables) [18]. In the initial model, constructs IT application and People/Participants showed AVE less than 0.5. The observed variables with least loadings BT3 and PE1 are dropped to improve the AVE by performing the elimination in two iterations. Table II shows the cronbach’s alpha, composite reliability, AVE value of final path model constructs.

TABLE II. ANALYSIS OF MEASUREMENT MODEL

 Constructs Cronbach's Alpha CR AVE IT application 0.83 0.88 0.54 People/participants 0.75 0.84 0.50 Methods/process 0.71 0.83 0.63 Resources 0.70 0.86 0.75 Documentation 0.83 0.89 0.66 Pro management 0.80 0.86 0.51 Environment 0.70 0.81 0.60 Schedule performance 0.86 0.89 0.58 Cost performance 0.82 0.88 0.65 Quality performance 0.74 0.85 0.65 Safety performance 0.83 0.89 0.67 Interface management-project benefits 0.82 0.89 0.73

The discriminant validity indicates the extent to which each construct is different from other construct in the model. The discriminant validity is examined by Fornell and Larcker criterion and Cross loadings [19]. AVE is found for each latent variable. Square roots of AVE are then compared against the correlations among the latent variables. Square roots of AVE are shown in the main diagonal elements in Table III. The correlations among the latent constructs are shown in the off-diagonal elements in Table III. To satisfy the discriminant validity the square root of AVE should be greater than the off-diagonal elements in the corresponding rows and columns. Thus Table III indicates Fornell and Larcker criterion is met to satisfy the discriminant validity. The results of cross loading show that indicator loading on its own construct is higher than all of its cross loadings with other construct.

TABLE III. CORRELATION AMONG THE CONSTRUCTS

 Constructs CT DC EN IM IT APP MP PE PM QY RS SF SCH CT 0.80 DC 0.40 0.81 EN 0.37 0.54 0.77 IM 0.65 0.49 0.52 0.86 IT APP 0.67 0.51 0.47 0.72 0.73 MP 0.54 0.71 0.61 0.57 0.61 0.79 PE 0.59 0.64 0.51 0.61 0.66 0.73 0.71 PM 0.50 0.67 0.64 0.53 0.48 0.66 0.62 0.71 QY 0.64 0.51 0.43 0.70 0.62 0.58 0.48 0.54 0.81 RS 0.46 0.58 0.49 0.49 0.40 0.64 0.73 0.61 0.30 0.87 SF 0.53 0.52 0.51 0.69 0.66 0.59 0.50 0.56 0.77 0.33 0.82 SCH 0.73 0.44 0.46 0.71 0.62 0.56 0.59 0.61 0.71 0.39 0.61 0.76

Assessment of Structural Model

The structural model is assessed for path coefficients (β value), significance of R2, effect of size of f2, predictive relevance and mediating effects. The validation of structural model is done by calculating Global fit index and power analysis for the adequacy of sample size.

i) Path coefficient (β value) and T- statistics value:

The path coefficients in the structural model are the hypothesized relationship among the constructs. The t- value is found by bootstrapping procedure and is tested at 5% level of significance i.e., 1.98. The analysis of path coefficient shows that interface management has positive significant effect on schedule, cost, quality & safety performance, people/participants, methods/process, resources, documentation, project management and environment with β values as in Table IV and Figure III The IT application has significant influence on interface management with β value of 0.723 and also the β value of 0.711 implies that interface management strongly influences schedule performance of the project. All other inferences for the path coefficients are given in the Table IV.

TABLE IV. PATH COEFFICIENTS AND T STATISTICS

 Code Hypothesis Path Coefficients T values Inference H1 Interface Management - People/Participants 0.61 10.13 Significant H2 Interface Management - Methods/Process 0.57 10.56 Significant H3 Interface Management - Resources 0.49 5.86 Significant H4 Interface Management - Documentation 0.49 5.26 Significant H5 Interface Management - Project Management 0.53 8.05 Significant H6 Interface Management - Environment 0.52 6.59 Significant H7 IT Application - Interface Management 0.72 9.66 Significant H8 Interface Management - Schedule Performance 0.71 8.06 Significant H9 Interface Management - Cost Performance 0.65 7.05 Significant H10 Interface Management - Quality Performance 0.70 7.51 Significant H11 Interface Management - Safety Performance 0.69 7.59 Significant

##### FIGURE III.

FINAL PLS SEM MODEL FOR INTERFACE MANAGEMENT

Concerning the hypothesized relationship, all hypothesis from H1 to H11 are supports with t-values greater than 1.96 for the significance level of 5% as shown in the Table IV.

ii) Measuring the value of R2

The explained variance is assessed using R2 of the endogenous latent variable. The R2 indicates the change in the endogenous construct, when there is a change in the predictor construct. R2 of endogenous construct can be assessed as substantial when the value is 0.26, moderate when the value is 0.13 and weak at the value of 0.02 [20]. The R2 value of each endogenous construct is shown in Figure IV.

##### FIGURE IV.

MEASURING THE VALUE OF R2

iii) Effective size f2

The impact of each predictor construct or exogenous construct on the dependant or endogenous construct is measured by means of effective size. When a predictor construct is eliminated from the PLS model, it measures the changes in the value of R2 and determines whether the eliminated predictor construct has a significant effect on the value of dependant construct. The effective size f2 is calculated using the following formula given by [21].

 $$f^2=\frac{R^2included-R^2excluded}{1-R^2included}$$ Eq. (1)

The effect of predictor construct is large if f2 is 0.35 and it is medium if f2 is 0.15 and less if f2 is 0.02 [6] and the results and inference for this model are given in Table V.

TABLE V. EFFECTIVE SIZE f2

 Independent Construct Dependent Construct f2 Inference Interface Management People/Participants 0.59 Large Interface Management Methods/Process 0.49 Large Interface Management Resources 0.31 Medium Interface Management Documentation 0.31 Medium Interface Management Project Management 0.40 Large Interface Management Environment 0.37 Large Interface Management Schedule Performance 1.03 Large Interface Management Cost Performance 0.72 Large Interface Management Quality Performance 0.98 Large Interface Management Safety Performance 0.91 Large IT Application Interface Management 1.09 Large

## MEDIATING EFFECT OF INTERFACE MANAGEMENT

The indirect effects are studied to determine whether interface management mediates the relationship between IT application and Project performance in term of schedule, cost, quality and safety. The IT application possesses significant β coefficients and t- value as shown in Table VI This suggests interface management fully mediates the effect of IT application on project performance.

TABLE VI. MEDIATING EFFECT

 Construct Mediating construct Direct Effect Indirect Effect Total Effects T-Value Inference IT Application -Cost Performance Interface management 0 0.467 0.467 4.435 Significant IT Application -Documentation Interface management 0 0.353 0.353 4.787 Significant IT Application - Environment Interface management 0 0.377 0.377 5.969 Significant IT Application - Methods/Process Interface management 0 0.414 0.414 6.111 Significant IT Application - People/Participants Interface management 0 0.440 0.440 6.377 Significant IT Application - Project Management Interface management 0 0.386 0.386 5.493 Significant IT Application - Quality Performance Interface management 0 0.509 0.509 4.747 Significant IT Application - Resources Interface management 0 0.353 0.353 5.749 Significant IT Application - Safety Performance Interface management 0 0.499 0.499 4.686 Significant IT Application - Schedule Performance Interface management 0 0.514 0.514 4.838 Significant

## GLOBAL FIT INDEX OF THE MODEL

GoF(Global Fit measure) is calculated for PLS path modelling, which is defined as geometric mean of average communality and average R2.GoF is used to assess the model fitness and explaining power of model. The results of global fit index of the model is presented in Table VII The cut-off values of GoF small=0.1, medium = 0.25, large = 0.36. GoF value for PLS model is estimated using the following equation [22].

 $$\mathrm{Goodness}\;\mathrm{of}\;\mathrm{fit}\;=\;\surd\mathrm{Average}\;\mathrm{communality}\;\mathrm x\;\mathrm{Average}\;R^2\;$$ Eq. (2)

 $$\mathrm{Average}\;\mathrm{Communality}\;=\;0.622$$ Eq. (3)

 $$\mathrm{Average}\;R^2\;=\;0.377$$ Eq. (4)

 $$\mathrm{Goodness}\;\mathrm{of}\;\mathrm{fit}\;=\;0.48$$ Eq. (5)

In this study, GoF value is 0.48, which indicates the model has 48% explaining power on interface management.

TABLE VII. GLOBAL FIT INDEX FOR THE MODEL

 Constructs R2 Communality Cost performance 0.418 0.651 Documentation 0.239 0.660 Environment 0.272 0.595 Interface management 0.523 0.732 IT Application 0 0.539 Methods/Process 0.328 0.625 People/Participants 0.370 0.504 Project management 0.286 0.505 Quality performance 0.495 0.654 Resources 0.238 0.754 Safety performance 0.476 0.667 Schedule performance 0.506 0.582 Average 0.377 0.622

## POWER ANALYSIS

The stability of model’s parameter with the sample size is tested using power analysis [21]. The parameters required for power analysis are significance level (α) of the test, sample size (N) of the study and effect size (ES) of the population. The power of the model is calculated using G power 3.1 software, The input parameter for this model are significance level =5%, sample size N (101), and the effective size ES is calculated using the following equation [23].

 $$\mathrm{Effective}\;\mathrm{size}=\frac{R^{\mathit2}}{1-R^2}=\frac{0.377^2}{1-0.377^2}=0.61$$ Eq. (6)

Figure V indicates the power of the overall model increases as the number of sample size increases. With the sample size of 40, the power of 100% is achieved.The sample taken up for this research is 101. Therefore the sample size used for this study is adequate for achieving substantial power.

POWER ANALYSIS

## CASE STUDY

The validated model was applied in the construction firms through case studies. The results of the analysis were used to develop the template. The case study comprises two templates. The first template was to evaluate the impact on interface management factors in the particular organisation. The second template measures the improvement in project performance due to interface management.

Construction firms with interface management were identified and two organisations were selected for the case study namely company A and B. A questionnaire was framed and then distributed to the firms A and B. Questionnaire comprises three parts with the first part framed to gather information about the organisation and personal information of the respondent.

The second part consists of 22 statements to evaluate the impact on interfacial management factors in the firms A & B under six constructs namely people/participants, methods/process, documentation, project management, and environment. The third part is designed to measure the improvement in project performance due to interface management with 20 statements under 4 constructs i.e., schedule performance, cost performance, quality performance and safety performance.

Each statement was framed to obtain the organisations status on the various attributes in the context of interface management. The respondents were asked to rate their organisation’s level in percentage from 0 to 100(Strongly Agree-80-100%,Agree-60-79%, Neutral-40-59%, Disagree-20 -39%, Strongly Disagree-0-19%) for each statement in the questionnaire from the perspective of interface management in their organisation.

Development of Template

The first template is developed to measure the impact on interfacial management factors as shown in Table VIII. From the results given by the PLS-SEM, the outer weights of all attributes of constructs namely people/participants, methods/process, documentation, project management, and environment were used.

TABLE VIII. IMPORTANCE % INDEX FOR INTERFACE MANAGEMENT FACTORS

 Constructs Indicators Outer Weights Mean Weight Importance percentage index of each construct Contribution each attribute towards its corresponding construct Importance percentage index of each attribute People/Participants PE2 0.276 0.196 0.0247 PE3 0.289 0.205 0.0258 PE4 0.283 0.282 12.61 0.201 0.0253 PE5 0.289 0.205 0.0258 PE6 0.273 0.194 0.0244 Methods/Process MP1 0.554 0.445 0.0826 MP2 0.389 0.415 18.54 0.313 0.0580 MP3 0.301 0.242 0.0449 Resources RS1 0.447 0.569 25.44 0.393 0.0999 RS2 0.691 0.607 0.1544 Documentation DC1 0.236 0.193 0.0264 DC2 0.314 0.306 13.66 0.257 0.0351 DC3 0.345 0.282 0.0386 DC4 0.327 0.268 0.0365 Project Management PM1 0.275 0.196 0.0205 PM2 0.24 0.171 0.0179 PM3 0.247 0.234 10.47 0.176 0.0184 PM4 0.17 0.121 0.0127 PM5 0.209 0.149 0.0156 PM6 0.264 0.188 0.0197 Environment EN1 0.407 0.314 0.0606 EN2 0.471 0.432 19.31 0.363 0.0702 EN3 0.418 0.323 0.0623

The importance percentage index of each construct and also importance percentage of each attributes to its corresponding constructs are calculated. The respondents give the impact of interface management factors in their organisation in terms of percentage. This percentage is multiplied with importance percentage index of each attributes to measure the contribution each attribute towards interface management.

The second template is used to measure the improvement in project performance of the firms due to interface management as indicated in Table IX. The outer weights of project performance indicators, namely schedule performance, cost performance, quality performance and safety performance are measured and the calculations are done similar to first template.

TABLE IX. IMPORTANCE % INDEX FOR PROJECT PERFORMANCE

 Constructs Indicators Outer Weights Mean Weight Importance percentage index of each construct Contribution each attribute towards its corresponding construct Importance percentage index of each attribute Schedule Performance SCH1 0.207 0.218 17.57 0.158 0.0278 SCH2 0.197 0.150 0.0264 SCH3 0.246 0.188 0.0330 SCH4 0.241 0.184 0.0323 SCH5 0.202 0.154 0.0271 SCH6 0.217 0.166 0.0291 Cost Performance CT1 0.351 0.310 24.96 0.283 0.0706 CT2 0.255 0.205 0.0513 CT3 0.298 0.240 0.0599 CT4 0.337 0.272 0.0678 Quality Performance QY1 0.416 0.408 32.85 0.340 0.1116 QY2 0.32 0.261 0.0858 QY3 0.489 0.399 0.1311 Safety Performance SF1 0.311 0.306 24.62 0.254 0.0626 SF2 0.288 0.235 0.0579 SF3 0.286 0.234 0.0575 SF4 0.339 0.277 0.0682

Assessment Results of Firms A & Firm B

Company A is one of the largest construction contracting firms in India which has done more than 100 projects. The main industry the company working are Infrastructure, Oil & Gas, Commercial and Industrial Buildings. The company uses ERP to manage interface. Company B is also a large contracting firm with its headquarters in UAE. The company has done more than 50 Oil & Gas and Industrial projects. Aconex is the interface management tool used in the company B to handle the interfaces.

The Tables X and XI gives the respondent’s answer and the corresponding company’s actual level of impact on interface management factors and project performance.

TABLE X. IMPACT ON INTERFACE MANAGEMENT FACTORS FOR FIRM A & B

 Constructs Indicators Response from company A in % Actual Level Response from company B in % Actual Level People/Participants PE2 80 1.974 75 1.851 PE3 70 1.809 80 2.067 PE4 90 2.277 85 2.151 PE5 75 1.938 80 2.067 PE6 90 2.197 75 1.831 Methods/Process MP1 80 6.604 75 6.191 MP2 80 4.637 80 4.637 MP3 85 3.812 85 3.812 Resources RS1 60 5.995 85 8.492 RS2 65 10.039 50 7.722 Documentation DC1 70 1.846 80 2.110 DC2 75 2.632 85 2.983 DC3 80 3.084 80 3.084 DC4 85 3.106 80 2.924 Project Management PM1 75 1.537 70 1.434 PM2 80 1.430 75 1.341 PM3 85 1.564 80 1.472 PM4 90 1.140 85 1.077 PM5 80 1.246 85 1.324 PM6 80 1.574 90 1.770 Environment EN1 85 5.155 85 5.155 EN2 85 5.966 70 4.913 EN3 70 4.360 80 4.983

TABLE XI. IMPROVEMENT IN PROJECT PERFORMANCE IN FIRM A & B

 Constructs Indicators Response from company A in % Actual Level Response from company B in % Actual Level People/Participants PE2 80 1.974 75 1.851 PE3 70 1.809 80 2.067 PE4 90 2.277 85 2.151 PE5 75 1.938 80 2.067 PE6 90 2.197 75 1.831 Methods/Process MP1 80 6.604 75 6.191 MP2 80 4.637 80 4.637 MP3 85 3.812 85 3.812 Resources RS1 60 5.995 85 8.492 RS2 65 10.039 50 7.722 Documentation DC1 70 1.846 80 2.110 DC2 75 2.632 85 2.983 DC3 80 3.084 80 3.084 DC4 85 3.106 80 2.924 Project Management PM1 75 1.537 70 1.434 PM2 80 1.430 75 1.341 PM3 85 1.564 80 1.472 PM4 90 1.140 85 1.077 PM5 80 1.246 85 1.324 PM6 80 1.574 90 1.770 Environment EN1 85 5.155 85 5.155 EN2 85 5.966 70 4.913 EN3 70 4.360 80 4.983

In this case study for company A, the first template reveals interface management has an impact of 10.19% on people/participants, 15.05% on methods/process, 16.03% on resources, 10.67% on documentation, 8.49% on project management, 15.48% on environment. The second template depicts 14.29% of schedule performance, 20.66% of cost performance, 28.48% of quality performance, 21.58% of safety performance have improved due to the interface management in the company A.

For company B interface management has an impact of 9.97% on people/participants, 14.64% on methods/process, 16.21% on resources, 11.10% on documentation, 8.42% on project management, and 15.05% on environment. In case of project performance 12.59% of schedule performance, 17.65% of cost performance, 27.70% of quality performance and 21.50% of safety performance are due to interface management in particular organisation.

## DISCUSSIONS AND PRACTICAL IMPLICATIONS

The number of research dealing with impact of IT tools and interface management on project performance is scarce. The first objective of this study is to validate a model for assessing the relationship among IT application, interface management and project performance. The PLS-SEM approach is used to validate the model. The findings suggest the IT tools are widely used to support the Interface management, which can be inferred from the hypothesis H7.The path coefficient of 0.723 indicates the influence of IT tools on interface management. The model suggests that IT tools like BIM, Information sharing platforms, Interface database management system, Video conference, E-mail, Auto-CAD are the effective tools that can be used to support the interface management system. The construction managers should be aware of these IT tools to enhance the Interface management. Though the previous studies shows that application of IT improves the interface management, no attempt is taken to develop a model for assessing the relationships among IT application and Interface management [6]. This study attempted to fill this knowledge gap in the literatures.

The hypothesized relationships H8-H11 are all positively significant which implies Interface management has a significant effect on project performance in term of schedule, cost, quality & safety. Interface management improves the communication chain among the stakeholders which helps in early detection of misinterpretations, disputes which indirectly reduces schedule, cost, quality and safety issues. The findings show interface management has more impact on schedule performance with a path coefficient of 0.711 in improving the project performance. The interface management improves the schedule performance by reducing the disputes, stress among the team and ensuring the timely completion of the project. The cost performance is enhanced by managing financial risks and meeting the cost objectives of the project with the aid of interface management. The Interface management helps in the reducing reworks by prior identification of flaws thus ensuring the quality performance. The accidents and injury rate are reduced, which contributes to the safety performance of the project. The results of this research show that project performance can be strengthened by identifying the interface points and effective interface management. These results are also in line with the previous studies which show that interface management practice act as an enabler for project performance [9,10,11,12]

The second objective is to evaluate the mediating role of interface management in relationship between IT application and project performance. Prior research indicates that IT plays an important role in interface management [6]. The interface management is found to be associated with the project outcomes. However the previous studies have not provided any insights into the mediating role of interface management in relationship between IT application and project performance. By examining the indirect effects of IT application on project performance in terms of schedule, cost, quality, safety, the research confirms that use of IT tools influence the project performance via interface management.

The third objective is to examine the impact of interface management practice in solving the interfacial issues. The hypotheses H1-H6 are positively significant which portrays proper interface management will have a positive impact on people/participants, methods/process, documentation, project management and environment. The path coefficients of these factors suggest interface management has greater impact (0.608) on people/participants, which suggests interface management improves co-ordination, communication and trust among the project participants which is in line with the previous studies [24]. The findings suggested proper sharing of interface information will help to implement new technologies without any construction and assembly problems. The resource utilisation can be optimised by interface practice by spotting the resource conflict points in advance. The interface management practice uses interface management tools which make it easy for the construction practitioners to document the interface information, change orders, etc. The findings report enhancement of interface management will have a positive eye on project management practices. The Mega projects have cultural diversities due to the involvement of multidisciplinary teams. These interface points can be effectively managed or improved by proper interface management practice.

The case study reveals interface management has the greatest impact on resources in both organisations i.e., 16.03% & 16.21% respectively. In case of company A project performance has improved by 85.01% and for company B, 79.44% of project performance have enhanced due to interface management.

## CONCLUSIONS

In summary, this research provided empirical evidence for gaining the project benefits with higher levels of interface management practice and IT application adoption. The research findings provide that ensuring the awareness of interface management, helps the project managers to identify the focus arena in a particular project to enhance the project performance. The result of this study aids the construction organisations to predict their level of interface management in their organisations and also to identify the factors to be focused to improve the interface management in the organisation. The interface management can be enriched by the usage of IT application which ultimately improves the project performance.

The major research limitation of this research is small sample size, although it is enough to carry out the analyses using PLS-SEM approach. Further parts of model can be investigated in detail by introducing further casual relationships among the constructs. The templates can be further developed to do study the impact of IT application on interface management in construction firms.

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