This study sought to understand the relationship between project delivery success and the strength of client-consultant relationships. It then tested the relationship between project delivery success and client-consultant relationship using the identified set of factors.
B ACKGROUND
Such ambiguity means that clients and consultants may perceive and measure project success differently, which can ultimately affect their relationships. This study investigated whether consultants and their clients measure and experience project success in the same way or not.
R ESEARCH P ROBLEM
The study used a list of success factors identified in the previous studies above, against which both advisors and clients had to rate whether they found them valid or not. Clients and consultants also had to rate these factors, indicating how much importance they placed on each of them.
R ESEARCH P URPOSE
R ESEARCH A IM
R ESEARCH O BJECTIVES
R ESEARCH M OTIVATION
Why professional services firms?
Based on these views, a good understanding of the impacts of project delivery on the strength of these interactions is critical. Thus, this research sought to establish the relationship between project delivery and client-consultant relationship strength.
Why engineering consulting industry?
Second, research has also shown that professional services depend on the cooperative interaction between buyers and sellers.
Why South African context?
R EPORT S TRUCTURE
To the best of this researcher's knowledge, this has not been covered in previous research. This was done to create the necessary theoretical constructs on which the investigations were based.
O VERVIEW
B ACKGROUND TO THE P ROFESSIONAL S ERVICE I NDUSTRY
K EY P LAYERS IN THE P ROFESSIONAL S ERVICES I NDUSTRY
Consultants
This model uses a diagnostic approach where the role of the consultant is to examine the client's organizational challenges. To achieve their goals, they must work in close collaboration with the customer.
Clients
These are members of the primary client organization who, unlike the unwitting clients, would be aware of the impact of the project on them, but are unfortunately unknown to the consultant. The consultant will need to work closely with the primary client to understand the needs of the indirect clients and the impact of the project on them.
C LIENT - CONSULTANT ENGAGEMENTS
Common fatal flaws in client-consultant engagements
Projects must be defined according to the specific goals that the client wants to achieve. There will also be no risk sharing, with the weakest people likely to be delegated to the riskiest parts of the project.
P ROJECT P ERFORMANCE
- Background
- Project management success
- Project success
- Framework of metrics used this research
- Section summary
- Client-consultant relationships
- Section summary
Despite these shortcomings, metrics for project management success remain very important in evaluating and measuring project delivery and performance. Therefore, evaluating project delivery based on project success metrics provides a holistic basis for considering downstream effects.
I NTRODUCTION
R ESEARCH Q UESTIONS
R ESEARCH H YPOTHESES
- Hypothesis 1
- Hypothesis 2
- Hypothesis 3
- Hypothesis 4
- Hypothesis 5
Where: H0 is the null hypothesis, CONSEC is the consultant relationship evaluation criterion, and CLIENTEC is the client relationship evaluation criterion. Where: H1 is the alternative hypothesis, CONSEC is the consultant relationship evaluation criterion, and CLIENTEC is the client relationship evaluation criterion.
I NTRODUCTION
R ESEARCH P HILOSOPHY
R ESEARCH A PPROACH
Based on this view, this study described the relationship between project delivery success and buyer-seller relationships as they have been found to be central to professional services. In this study, this was done through a detailed literature review of previous research, which focused on the professional services sector.
C HOICE OF R ESEARCH D ESIGN
R ESEARCH S TRATEGY
R ESEARCH S COPE
Evaluation of project performance metrics by clients and consultants Identification and categorization of metrics used for.
U NIT OF A NALYSIS
S TUDY P OPULATION
S AMPLING M ETHOD
Primary sampling unit
Quota sampling was used for this purpose, targeting engineering consultancy companies and public sector clients. Therefore, quota sampling was used for this study to ensure that only targeted respondents, (engineering consulting companies and public sector clients) were included.
Secondary sampling unit
The researcher acknowledged the fact that while such a sampling approach offers the benefit of convenience and ease of access to respondents, there are challenges involved. Furthermore, despite the fact that respondents were asked to forward the uncompleted questionnaires to their colleagues who were outside the researcher's database, their responses were sent directly to the researcher.
S AMPLE S IZE
However, he believed that the opportunity to influence any response was limited given the fact that no one was asked to identify themselves. Based on this assumption, a total of about 90 responses were expected, which were considered sufficient to perform statistics.
D ATA C OLLECTION I NSTRUMENT
Questionnaire design
Overall, the project implementation success and relationship measurement constructs used in the questionnaire design are summarized in Table 5 below. Adherence to functional specifications Adherence to technical/scope requirements Customer satisfaction with the final product.
Questionnaire distribution
This worked well and supported the use of snowball sampling in cases where respondents were not part of the researcher's database. The latter refers to the extent to which the questions asked result in the collection of the data it was intended to measure.
Pretesting of the questionnaire
For this research, the questionnaire was considered a good instrument for achieving the required levels of reliability. The questionnaire should also be pre-tested for validity in terms of answering the following questions.
D ATA A NALYSIS
Data preparation
A factor analysis was used to appropriately group the factors and also test for internal validity. Factor analysis was used to appropriately group the factors and also test for internal validity.
Statistical description and examination of data
A cross-tabulation and chi-square test were used to test hypothesis 1 and hypothesis 3. The research focused on establishing and describing the relationship between project implementation and the client-consultant relationship. Between -0.2 and -0.35 weak negative correlation Between -0.35 and -0.6 moderate negative correlation Between -0.6 and -0.8 strong negative correlation Between -0.8 and -1 very strong negative correlation.
Exploring and presenting data
I NTRODUCTION
Cross-tabulations were run between clients and consultants and each item on the relationship measurement scale to determine similarities and differences in responses. Pearson's correlation was run across all items under the project delivery and relationship measurement scales.
S AMPLE D ESCRIPTION (R ESPONSES )
Null hypothesis (H0): consultants and their clients use the same metrics to evaluate good consultant-client relationships. Alternative hypothesis (H1): consultants and their clients do not use the same metrics to evaluate good consultant-client relationships.
R ESPONDENTS D ESCRIPTION
- Sample Description (Demographics)
- Respondent categories
- Type of organisation
- Project management capacity
- Number of months in the project management capacity
- Age
- Gender
- Race
The distribution of respondents in relation to their tenure in project management capacity is provided in Figure 8. For both clients and consultants, the highest number of respondents had been involved in project management roles for less than five years.
P SYCHOMETRIC P ROPERTIES OF THE S CALES
Selected scales for data analysis
Based on the factor analysis and the related results of the internal consistency test (Cronbach's alpha), the factors from categories 1 and 2 were retained, and those from category 3 were discarded. Cronbach's alpha coefficients were acceptable, so the factors were suitable for use in detailed analysis.
D ESCRIPTIVE S TATISTICS (I NDIVIDUAL F ACTORS )
A descriptive summary of the relationship measurement factors used in the study is provided in Table 14. Mean scores indicate that both clients and counselors rate the relationship measurement factors as between only important (score 3) and very important (score 2).
D ESCRIPTIVE S UMMARIES FOR A GGREGATE F ACTOR C ATEGORIES
D ESCRIPTIVE S TATISTICS (C ROSS TABULATION )
The largest difference between client and consultant responses was related to "project implementation that adheres to an agreed schedule or time," as shown by a difference in standard deviations of 0.324. Both clients and consultants rated adherence to the schedule as the most important priority (1.22 and 1.13, respectively).
T ESTING THE H YPOTHESES
Hypothesis 1
The results of the chi-square test suggest that there is no significant difference between clients and advisors regarding their response to this measure (p-. The results of the chi-square test suggest that there is no significant difference between clients and advisors regarding their response to this measure (p-value of 0.055 > 0.05).
Hypothesis 2
The ratings by clients and consultants regarding "project execution meeting budget" are marginally similar. The ratings by clients and consultants regarding project execution adherence to budget are marginally similar.
Hypothesis 3
Chi-square test results indicate that there is a significant difference between clients and consultants regarding their response to this measure (p-value of. Chi-square test results indicate that there is a significant difference between clients and consultants regarding of their response to this criterion (p-value of 0.000 < . 0.05).
Hypothesis 4
The independent sample t-test indicates that there is a significant difference between clients and consultants regarding their response. The independent samples t-test indicates that there is a significant difference between clients and consultants regarding their response to this measure (a significance coefficient of 0.000 < 0.05).
Hypothesis 5
Therefore, the results show that there is no connection between the success of the project implementation and the strength of the relationship between the client and the consultant. There is no correlation between the performance of the project and the ratio measurement factors (correlation coefficients are between 0 and 0.1 and 0 and
Chapter conclusions
This meant that customers and consultants assess the success factors for the project's delivery in roughly the same way. This meant that clients and consultants do not evaluate the various ratio measurement factors in the same way.
I NTRODUCTION
A DDRESSING THE R ESEARCH H YPOTHESES
Hypothesis 1
They emphasize the need to balance both project management and project success factors in project delivery evaluations. However, the findings remain valid as confirmed by previous literature regarding success factors for project management.
Hypothesis 2
Instead, research should distinguish between project management success and project success factors in the analysis. This study attempted to use this recommended approach, although project success factors were excluded due to low levels of internal validity and reliability (consistency).
Hypothesis 3
They also used three models to explain the nature of engagement, namely "the expert model", "the critical model" and the "social learning model". Therefore, the findings of this study are not consistent with the requirements of "the critical model" and the "social learning model".
H YPOTHESIS 4
According to Appelbaum (2009, Kakabadse, Louchart and Kakabadse, 2009), different types of clients and consultants warrant different engagement models. Therefore, this study has contributed to the body of knowledge by empirically proving that clients and consultants do not value relationship measurement factors similarly.
H YPOTHESIS 5
No correlation was established between project implementation success and relationship measurement factors (correlation coefficients were below 0.2). The question is "if good project delivery is not attractive enough to enhance relationships, especially between clients, then what could be the explanation for this?" The following insights drawn from past literature are used by this study to attempt to provide some explanations and answers to this question.
C HAPTER C ONCLUSION
The results have shown that the mere delivery of a project, no matter how good, is enough to improve and grow the relationship between client and consultant.
P ROPOSED CLIENT - CONSULTANT ENGAGEMENT MODEL
I NTRODUCTION
M AIN C ONCLUSIONS
- Research question 1
- Research question 2
- Research question 3
- Research question 4
- Research question 5
The results of the study concluded that clients and consultants generally rated project delivery success factors with quite the same level of importance. However, the results have been contested under the "process consultation", "the critical model" and the "social learning model".
R ESEARCH C ONTRIBUTIONS AND R ECOMMENDATIONS
Managerial
With this understanding, project delivery can be tailored to best address the client's priority interests and expectations. The study also highlighted the need to focus beyond the implementation of individual projects, as it does not provide enough understanding of the client's environment.
Academic
The study also reinforced the findings of past studies that project success and relationship management are complex focus areas for academic research. Most of the factors involved are context specific and therefore vary between clients and groups of consultants.
S TUDY LIMITATIONS AND SUGGESTIONS FOR FUTURE RESEARCH
- Research methodology
- Research design
- Design of the research instrument
- Sample of the study
- Context and scope of the study
- Suggestions for future research
Time and resource constraints on the part of the researcher made it necessary to focus on only one sector. This will help in the selection, design and deployment of research instruments in different situations.
C ONCLUDING S TATEMENT
Relationships and influences of service quality, perceived value, customer satisfaction and image: an empirical study. Understanding the value of project management from a stakeholder perspective: Case study of mega-project management.
DRAFT QUESTIONNAIRE
Please indicate your gender by ticking the box below. In the table below, I would like to ask you to indicate the category of your organization by checking the appropriate box.
CORRELATION BETWEEN PROJECT DELIVERY AND CLIENT-CONSULTANT RELATIONSHIP
