Adedeji A. Adepeju*
| Eziyi O. Ibem | Adedapo A. Oluwatayo | Hilary I. Okagbue
© 2024 The authors. This article is published by IIETA and is licensed under the CC BY 4.0 license (http://creativecommons.org/licenses/by/4.0/).
OPEN ACCESS
From the system view of organisations, this study investigated how client relationship management (CRM) strategy responses of architectural firms to market conditions influence their firm performance. Previous studies have proposed empirical models that explored this relationship in several organisational contexts, but there is a dearth of studies that explained the link between CRM strategy and firm performance in the context of architectural firms. The empirical model of the current study closed this gap by explaining how the CRM strategy features used by architectural firms influence their firm performance. A questionnaire survey of 195 samples of randomly selected architectural firms was conducted in Lagos, Nigeria. 82 copies of the questionnaire (42% response rate) were retrieved and the nominal and ordinal data obtained were subjected to descriptive, factor and categorical regression analyses using Statistical Product and Service Solutions (SPSS) software (IBM SPSS Statistics 23). The regression analysis revealed that client collaboration, client communication and service customisation dimensions of CRM strategy had a statistically significant influence on the firms’ overall performance. The model of this study contributed to the empirical literature by revealing how the strategic behaviour of architectural firms in the industrial market optimizes their performance. Managerial implications and areas for further studies were stated.
architectural firms, architectural industry, CRM strategy, organisational performance
Architectural firms and clients are two critical agents that contribute to the development of the built environment. Undoubtedly, mutually satisfying business relationships between them are crucial to sustainable planning and development of the built environment and contribution to goal 11 of the 2030 Agenda for Sustainable Development adopted by all United Nations Member States in 2015. Architectural firms are social entities that are immersed in a market within which they strive for continued existence and relevance [1, 2]. From the system view of organisations, the market is part of the external environment within which firms act in prospect or react in retrospect [3-5]. The market environment is composed of different categories of clients, types of services and firms that compete to win clients for commissions [6, 7]. The competition for clients is aggravated by current global market turbulence, which is characterised by unpredictable and swift changes in technology, client tastes or competitor responses as well as other aspects of the external business environments that affect their performance [8, 9]. In such market conditions, business organisations are known to act proactively by taking strategic actions, or reactively by taking tactical random actions to survive or thrive [10-12].
However, when firms are competing fiercely, clients expect more from them than just the delivery of expert services. They also expect the quality of relationships that accompany the services [13, 14]. In this regard, high-quality client relationships must complement expert service delivery to enhance clients’ perception of high-quality service delivery [15, 16]. CRM strategy is a firm’s high-level plan that aligns company processes to nurture relationships with valuable clients in the external environment of the firm to win their loyalty such that they will always prefer to give jobs to firms and eagerly persuade others to do so through their positive recommendations and referrals [15, 16]. Previous studies have copiously reported the influence of CRM strategy on the achievement of client retention and firm performance by business organisations [17-20]. However, there are insufficient studies that describe the unique manifestation of CRM strategy in architectural firms and how the phenomenon contributes to their firm performance.
In this regard, the aim of the current study is to close this existing knowledge gap by investigating how the CRM strategy responses of architectural firms to market conditions influence their firm performance. Consequently, the first objective of the study is to describe the particular characteristics of the architectural market in the study area. The architectural market is the industrial space in which strategic dyadic relational activities between architectural firms and clients occur to achieve service delivery. The architectural market also represents the external environment that architectural firms pre-empt or respond to. The second objective of this study is to examine the specific CRM strategies that architectural firms engage to respond to their external environment in the study area. The third, objective of the study is to investigate how CRM strategies influence the financial, non-financial and overall performance of architectural firms in the study area.
Consequently, the study operationalized CRM strategy and firm performance as a multidimensional construct after an extensive review of previous authors in the knowledge domain and a deductive causal model was proposed to explain how it contributes to the performance of architectural firms from a system view of the organization. Furthermore, the model of the study was tested with data acquired from responses of randomly selected principals of sampled architectural firms to copies of a validated questionnaire. The nominal and ordinal data obtained were subjected to descriptive, factor and categorical regression analyses using SPSS software (IBM SPSS Statistics 23). The findings of the study presented as tables and charts were interpreted and discussed. Conclusion, as well as limitations and recommendations for further research, were presented. The study makes unique contributions to the empirical literature by modelling, testing and describing how the strategic behaviour mechanisms of architectural firms in the industrial market optimize their performance. Managerial implications and areas for further studies were stated.
2.1 Operationalisation of the architectural market
In the literature, market has been conceptualised by different CRM authors in terms of clientele’s composition (business-to-business [B2B] or business-to-client [B2C]), the competitors, the products or services demanded or geographical location [21-26]. B2B clients are organisational clients, B2C are individual clients, while the literature also recognises the existence of business-to-Government (B2G) clients.
In the current study, the market is viewed as a platform where architectural firms seek opportunities to acquire relationships with potentially profitable clients and develop such relationships into permanent enterprise assets through the engagement of CRM strategies [17, 18]. Thus, the categories of clients and the different service types that they demand from architectural firms are considered important relational indicators that characterise the architectural market [27, 28].
Furthermore, previous studies have used demand-side and supply-side measures to operationalize market phenomena [29, 30]. The current study has a firm-centric focus because its unit of analysis is the architectural firm. Consequently, supply-side measures of the market that require data which are domiciled within architectural firms are proposed. Thus, the frequency of client categories acquired by the firms and the types of services that clients purchased from the firms were used as measures of the architectural market construct.
2.2 Operationalisation of CRM strategy
An organisational strategy is a high-level plan that prescribes how a firm would achieve its goal by focusing organisational processes to respond to market conditions with a view to achieving competitive advantage [31, 32]. Firms that use CRM strategy endeavour to achieve the ultimate goal of attracting potentially profitable clients from the market and optimising the value of their current profitable clientele by prioritizing satisfying their needs such that they would always prefer to give jobs to their firm and speak positively about the firm’s service provisions [18, 20, 33, 34]. Thus, CRM strategy aligns with market conditions and adapts to changes in those conditions [35-37]. This implies that firms adapt their CRM strategy to market conditions like client categories and types of services that they demand.
CRM strategy has been severally conceptualized in the literature as a high-level plan that prescribes groups of tactical enterprise activities that employees should perform towards clients to achieve the company’s desired CRM outcomes in a specific market context. Such activities integrate all client-facing processes to facilitate individualised client relationships so that every client's interaction with the firm is coherent, personalized and satisfying [17, 34, 38]. When this concept is applied to architectural firms, CRM strategy serves as a decision-support protocol that ensures that all enterprise processes are aligned towards achieving client satisfaction and retention as a priority, resulting in optimal organizational performance. Previous authors have copiously reported that CRM strategy is an important multidimensional antecedent to positive firm performance in different sectors of the industrial market [18-20, 39, 40]. Based on an extensive review of the literature, CRM strategy is operationally defined in this study as a multi-dimensional second-order formative construct comprising of (i) knowing clients (ii) communication with clients (iii) partnership with clients, (iv) segmentation of clientele (v) client orientation of company processes and (vi) customisation of service delivery [38, 41-45]. Although these previous studies were carried out in other industries, this study explored the unique manifestation of CRM strategy in architectural firms in the study area.
2.3 Operationalisation of firm performance
Firm performance is a complex phenomenon that is difficult to universally conceptualise and operationalize. Nevertheless, its measurement provides top management with invaluable information to monitor progress, improve employees’ motivation and identify problems [46, 47]. Many authors agree that it is an evaluation that compares enterprise outcomes to pre-determined goals and expectations of relevant stakeholders. Performance measures account for internal and external stakeholders, including firms’ owners, employees, clients, society and government [48-50].
This study employs both financial and non-financial measures, including Balanced Scorecards (BSC) and multi-criteria Key Performance Indicators (KPI) [51, 52], to evaluate the performance of architectural firms. It aligns with previous findings [48, 53], conceptualizing firm performance as fulfilling the diverse needs of stakeholders such as employees, clients, society, and government, in addition to firm owners.
The system theory was found sufficient to explain the structural relationships of the variables of interest in this study which are the architectural market, CRM strategy and firm performance. The general systems theory was proposed by von Bertalanffy [54, 55]. System theory explains that a system is a group of interconnected elements that form a whole and are subject to complex interactions between their parts within a defined boundary that distinguishes it from its external environment. Systems are open in that they possess permeable boundaries through which they exchange material and information from the environment. Systems are also adaptable and self-regulating because they respond to the inputs from the environment in a manner that would maintain their coherence and improve their state.
As applied to this study, architectural firms as systems receive information from the architectural market in its external environment about existing opportunities to initiate and nurture business relationships with different client categories who request different types of service delivery jobs as well as information about the social networks that give access to those jobs. The firms then adapt to these inputs from the environment and deploy internal CRM strategies to attract and convert profitable client relationships into enhanced firm performance.
On the basis of system theory, the conceptual framework of this study as shown in Figure 1 proposed that architectural firms adapt to the relational opportunities presented by features of the architectural market (client categories and services purchased) in the external environment by using unique CRM strategy, while the CRM strategy delivers output in the form of financial, non-financial and overall firm performance.
Figure 1. Conceptual framework of the study
This cross-sectional survey research is underpinned by the positivist philosophy which accommodates deductive strategies as well as a quantitative research approach. The quantitative research approach engages various types of statistical analysis techniques to quantify the relationships and interactions between different variables of interest and deduce the implications of the statistical outcomes in correspondence with the real-life phenomena that the study is focused on literatures [56, 57].
In this regard, the study sourced its sample from a sampling frame of 318 registered architectural firms in Lagos, Nigeria. By using the formula provided in reference [58], as follows:
$n=\frac{N}{1+N(e)^2}$
In this formula, n represents the minimum sample size, N is the research population (318), and e is the allowable error in statistical estimation, set at ±5% margin of error with a 95% confidence level. The calculated minimum sample size was 177 respondents. After accounting for a 10% non-response rate, the sample size was adjusted to 195 firms.
This study employed a questionnaire survey approach to efficiently collect extensive quantitative data on various subjects and phenomena at low cost [10, 59]. The data collection instrument, a questionnaire, was adapted from Kasim et al. [41, 42]. The data on the firm's demographics and characteristics were examined in the first section of the questionnaire. In the second section, respondents were asked a series of close-ended 5-point Likert scale (1-5) questions about CRM strategy, staff support, leadership style and clientele and the kinds of job commissions received by the firms. From the data gathered from a pilot study, a Cronbach alpha coefficient of 0.93 was investigated to validate the 59-item questionnaire. A total of 195 copies of the questionnaire were distributed to respondents from 25th February 2019 to 30th September 2019. Randomly selected principals of architectural firms in the study area participated in the study. Of the 195 copies of a questionnaire distributed, 82 copies were retrieved. This represented a response rate of 42%. The data were processed using descriptive statistics, principal components and categorical regression analyses using the SPSS software (IBM SPSS Statistics 23). The results are presented using tables and charts.
5.1 Demographic characteristics of the respondents
The demographic characteristics of the respondents revealed that the sample was dominated by ages 51-60 years (56.10%). Majority (92.7%) of the respondents were males and 76.8% possessed M.Sc degree as their highest level of education, while about 67.1% had over 26 years of professional experience (refer to Table 1). The descriptive statistics presented in Table 2 presents the mean and standard deviation of CRM Strategy variables.
Table 1. Demographics of respondents
|
Demographics |
Respondents’ Characteristics |
Frequency (N=82), n (%) |
|
Gender distribution |
Male |
76 (92.70) |
|
Female |
6 (7.30) |
|
|
Age range (years) |
31-40 |
3 (3.70) |
|
41-50 |
8 (9.80) |
|
|
51-60 |
46 (56.10) |
|
|
Above 60 |
25 (30.50) |
|
|
Highest educational qualification of the principals |
HND |
3 (3.70) |
|
B.Sc. |
5 (6.10) |
|
|
M.Sc. |
63 (76.8) |
|
|
PhD. |
8 (9.80) |
|
|
B.Arch. |
2 (2.40) |
|
|
PGD |
1 (1.20) |
|
|
Years of experience of the principals |
No response |
1 (1.20) |
|
Less than 11 |
11 (1.00) |
|
|
11-15 |
3 (3.70) |
|
|
16-20 |
7 (8.50) |
|
|
21-25 |
15 (18.30) |
|
|
26 and above |
55 (67.10) |
Source: Results from author’s analysis of acquired data from fieldwork.
Table 2. Descriptive statistics
|
CRM Strategy |
n |
Mean (x̄) |
S.D (σ) |
|
|
Stat. |
Stat. |
S.E. |
Stat. |
|
|
Client collaboration strategy |
|
|
|
|
|
Evaluate cost of client relationship |
82 |
3.43 |
0.13 |
1.20 |
|
Evaluate client relationship quality |
82 |
4.04 |
0.11 |
0.99 |
|
Use information from clients to improve service delivery |
82 |
4.27 |
0.10 |
0.90 |
|
Ask for clients’ opinion / preferences |
82 |
4.07 |
0.09 |
0.83 |
|
Evaluate satisfaction of clients with service delivery |
82 |
3.88 |
0.11 |
0.95 |
|
Client communication strategy |
|
|
|
|
|
Provide interactive communication channels |
82 |
3.39 |
0.13 |
1.14 |
|
Provide different options of interactive communication channels |
82 |
3.10 |
0.13 |
1.18 |
|
Obtain information about clients’ relational preferences |
82 |
3.55 |
0.11 |
1.08 |
|
Client orientation strategy |
|
|
|
|
|
Obtain information about project requirements of clients |
82 |
4.21 |
0.09 |
0.84 |
|
Delivery of services are based on knowledge of clients’ needs and expectation |
82 |
4.32 |
0.09 |
0.80 |
|
Clients’ preferred communication channels are adopted |
82 |
4.01 |
0.10 |
0.91 |
|
Service customisation strategy |
|
|
|
|
|
Valuable clients are given personalised incentives |
82 |
3.66 |
0.12 |
1.05 |
|
Different incentives are offered to current clients proportionate to their referrals |
82 |
3.15 |
0.13 |
1.19 |
Source: Results from author’s analysis of acquired data from fieldwork.
Note: Statistic (Stat.), Standard Deviation (S.D.), Standard Error (S.E.).
5.2 Characteristics of the architectural market
In this section, the results of descriptive analysis revealing the characteristics of the architectural market in the study area are presented.
Figure 2. Client categories in the market
Source: Results from author’s analysis of field data
Note: Individual clients (IndCli), Private Sector Organisations (PSOrg), Religious Organisations (RelOrg), Public Educational Institutions (PEInst), Financial Institutions (FinInst), Government (Govt), International Private Individuals (IntPrInd), Non-Governmental Organisations (NGOs), International Organisations (IntOrg), Community Organisations (ComOrg).
Figure 2 presents the ranking of the frequency of patronage of different client categories in the architectural market in the study area. The results revealed that individual clients were the most dominant in the market, followed by private sector organisations, religious organisations, financial institutions and government clients, while international private individual clients, NGOs, international organisations and community organisations either rarely or never patronized architectural firms in the study area.
Figure 3 presents the ranking of the frequency of different service types in the architectural market in the study area. The results revealed that architectural building design was the most dominant service type being demanded in the market, followed by construction supervision, building re-modelling, building construction and architectural visualisation, respectively. Production of physical models was the least dominant service type demanded in the market.
Figure 3. Service types in the market
Source: Results from author’s analysis of field data
Note: Architectural Building Design (ArcDes), Construction Supervision (ConSup), Building re-modelling (BldRed), Building Construction (BldCon), Architectural Visualisation (ArcVis), Landscape Design (LanDes), Management Consulting (MgtCon), Interior Design (Interior), Feasibility studies (FeaStd), Production of Physical Models (Model).
5.3 Results of factor analysis
The aim of the factor analysis is to define a set of associated factors that manifest as underlying indicator measures of a construct from a set of uncorrelated multivariable input data points [60]. In order to derive factor-analytically manifested indicators of CRM strategy in architectural firms from the dataset, Principal Component Analysis (PCA) extraction method and Varimax rotation with Kaiser Normalisation were used. The results of Kaiser-Meyer-Olkin (KMO) and Barlett’s test on the thirteen variables included in the factor analysis showed a KMO value of 0.81>0.60, Bartlett’s Sphericity (chi-square) is 435.71 and significance (p<0.05). The KMO value of 0.81 indicate that the sample for the indicators of CRM strategy is 81% consistent and adequate while the outcome of Bartlett’s Sphericity (chi-square) showed that the sample is suitable for modelling factor analysis [57].
Table 3 shows the results of the principal components obtained. The study analysed thirteen variables of CRM strategy in the model. Four principal component factors (PCFs) with Eigenvalue greater than one (e>1) came into view. The rotation sum of matrix squared loading revealed a sum of 8.96 which accounted for 68.94% of the variance in the thirteen variables investigated.
From Table 4, the four (4) emerged factors were labelled as follows: Factor 1, client collaboration strategy, Factor 2, client communication strategy, Factor 3, client orientation strategy and Factor 4, service customisation strategy.
Table 3. Extracted PCFs for CRM strategy
|
Co. |
Initial Eigenvalues |
Extraction Sums of Squared Loadings |
Rotation Sums of Squared Loadings |
||||||
|
Total |
% of Var. |
Cum. % |
∑ |
% of Var. |
Cum % |
∑ |
% of Var. |
Cum% |
|
|
1 |
4.92 |
37.84 |
37.84 |
4.92 |
37.84 |
37.84 |
2.90 |
22.33 |
22.33 |
|
2 |
1.83 |
14.10 |
51.94 |
1.83 |
14.10 |
51.94 |
2.20 |
16.93 |
39.27 |
|
3 |
1.20 |
9.23 |
61.17 |
1.20 |
9.23 |
61.17 |
2.00 |
15.40 |
54.67 |
|
4 |
1.01 |
7.77 |
68.94 |
1.01 |
7.77 |
68.94 |
1.86 |
14.27 |
68.94 |
|
5 |
0.81 |
6.22 |
75.16 |
|
|
|
|
|
|
|
6 |
0.67 |
5.12 |
80.27 |
|
|
|
|
|
|
|
7 |
0.57 |
4.34 |
84.62 |
|
|
|
|
|
|
|
8 |
0.47 |
3.61 |
88.23 |
|
|
|
|
|
|
|
9 |
0.42 |
3.23 |
91.46 |
|
|
|
|
|
|
|
10 |
0.39 |
3.01 |
94.46 |
|
|
|
|
|
|
|
11 |
0.31 |
2.38 |
96.85 |
|
|
|
|
|
|
|
12 |
0.25 |
1.89 |
98.73 |
|
|
|
|
|
|
|
13 |
0.17 |
1.27 |
100.00 |
|
|
|
|
|
|
Total variance accounted for=68.94%. Extraction Method: Principal Component Analysis.
Note: Component (Co.), Cumulative percentage (Cum %), Total (∑), percentage of Variance (% of Var.).
Table 4. Rotated component matrixa
|
Factors |
Component |
|||
|
1 |
2 |
3 |
4 |
|
|
Factor 1: Client collaboration strategy |
|
|
|
|
|
Evaluate cost of client relationship |
0.79 |
|
|
|
|
Evaluate client relationship quality |
0.73 |
|
|
|
|
Use information from clients to improve service delivery |
0.70 |
|
|
|
|
Ask for clients’ opinion / preferences |
0.70 |
|
|
|
|
Evaluate satisfaction of clients with service delivery |
0.65 |
|
|
|
|
Factor 2: Client communication strategy |
|
|
|
|
|
Provide interactive communication channels |
|
0.88 |
|
|
|
Provide different options of interactive communication channels |
|
0.88 |
|
|
|
Obtain information about clients’ relational preferences |
|
0.51 |
|
|
|
Factor 3: Client orientation strategy |
|
|
|
|
|
Obtain information about project requirements of clients |
|
|
0.85 |
|
|
Delivery of services are based on knowledge of clients’ needs and expectation |
|
|
0.68 |
|
|
Clients’ preferred communication channels are adopted |
|
|
0.52 |
|
|
Factor 4: Service customisation strategy |
|
|
|
|
|
Valuable clients are given personalised incentives |
|
|
|
0.87 |
|
Different incentives are offered to current clients proportionate to their referrals |
|
|
|
0.85 |
Extraction method: Principal component analysis.
Rotation method: Varimax with kaiser normalization.
a. Rotation converged in 6 iterations.
5.4 Results of regression analysis: Influence of CRM strategy dimensions on firm performance
The results of the model summaries of regression for the three models shown in Table 4 revealed that the models explained 30% of variance in financial performance (Adj. R2=0.30), 43% of variance in non-financial performance (Adj. R2=0.43), 43% of variance in overall performance (Adj. R2=0.43). The coefficients of regression for each of the three models are also presented in Table 5.
The first regression model set financial performance as the criterion that is predicted by CRM strategies. Results of the regression model reveal the influence of CRM strategy on financial performance. Three predictors namely, client collaboration strategy (β=0.62, p=0.01), client communication strategy (β=0.57, p=0.03) and service customisation strategy (β=0.33, p=0.05) had statistically significant influences on financial performance. The second regression model set non-financial performance as the criterion that is predicted by CRM strategies. Results of the second regression model reveal the influence of CRM strategy on non-financial performance. Only client communication strategy (β=0.42, p=0.04) had a statistically significant influence on non-financial performance.
Further, the third regression model set overall firm performance as the criterion that is predicted by CRM strategies. Results of the third regression model revealed that three predictors namely, client collaboration strategy (β=0.63, p=0.01*), client communication strategy (β=0.64, p=0.05*) and service customisation strategy (β=0.41, p=0.00**) had statistically significant influences on overall performance.
Table 5. Regression models of impact of CRM strategy on performance of architectural firms
|
Model Summary |
Criterion |
||
|
Fin. Perf. |
Non-Fin. Perf. |
Ov. Perf. |
|
|
Adj. R2 |
0.26 |
0.43 |
0.42 |
|
F |
2.50 |
4.18 |
4.08 |
|
Sig. |
0.00** |
0.00** |
0.00** |
|
Predictors |
Beta Values |
||
|
Client collaboration Strategy |
0.62* |
0.57 |
0.63* |
|
Client Communication Strategy |
0.57* |
0.68* |
0.64* |
|
Client Orientation Strategy |
0.49 |
0.42 |
0.46 |
|
Service Customisation Strategy |
0.33* |
0.19 |
0.41* |
Note: Financial Performance (Fin. Perf.); Non-Financial Performance (Non Fin. Perf.); Overall Performance (Ov. Perf.)
This study investigated how the CRM strategy responses of architectural firms to market conditions influence their performance. The results of the data analyses helped to achieve the three objectives of this study.
6.1 Characteristics of the architectural market
The first objective of this study was to describe the characteristics of the architectural market in the study area. The results of the mean ranking analysis revealed the unique characteristics of the architectural market in the study area which was defined as comprising client categories and services demanded by clients. The most purchased service in the market is architectural building design, followed by construction supervision, building re-modelling, building construction, architectural visualisation, landscape design, management consulting, and interior design while the most dominant client category is individual clients followed by private sector organisations, religious organisations, public educational institutions, financial institutions and government.
The results in Figure 2 imply that the architectural market in Lagos is dominated by B2C clientele in form of individual clients. Nevertheless, the firms also receive patronage from B2B (private sector and religious organisations, public educational institutions, and financial institutions) and B2G (Government) clients. Similarly, the results in Figure 3 imply that the most purchased architectural services in the Lagos market in Lagos, Nigeria is architectural building design services. These results corroborate the findings of some previous authors that surveyed architectural firms in Nigeria. While Oluwatayo [10] reported the dominance of individual client category in the architectural market in Nigeria, Ibem et al. [61] reported the dominance of design and build service offerings in architectural firms in North Central Nigeria.
6.2 CRM strategies used by architectural firms
The second objective of this study was to examine the CRM strategies that architectural firms engage in the study area. The results of the factor analysis revealed the unique CRM strategy engaged by architectural firms in the study area as comprising (i) client collaboration (ii) client communication (iii) client orientation strategy and (iv) service customisation strategies. These findings corroborate the multi-dimensional ontology of CRM strategy in other industry sectors as revealed by previous studies [19, 39, 62]. Mapped with industry realities, these findings do suggest that architectural firms do not respond with a single strategy to market vicissitudes. Indicators of the manifested dimensions of CRM Strategy presented in Table 3 also reveal that architectural firms that use client collaboration strategy facilitate collaboration with profitable clients by evaluating the cost of achieving satisfaction of clients, they also monitor and improve their service delivery quality based on response to clients' feedback, suggestions, opinion and preferences. This is similar to the concept of client collaboration in references [63, 64].
Also, firms that use client communication strategy provide different interactive communication channels to facilitate effective interaction with clients as a means of acquiring information about clients' relationship preferences. This is similar to the concept of communication strategy in reference [41, 42]. Also, firms that use Client orientation strategy orientate the internal system of the firm to prioritise on interacting with clients on their preferred communication channels to acquire information about their and delivering service to satisfy those needs and expectations. This is similar to the concept of client orientation strategy in references [65, 66]. Further, firms that use service customisation strategy provide individualised incentives to valuable client segments and pragmatically offer incentives to their clients according to their potential to draw job referrals to the firms. This is similar to the concept of service customisation in references [18, 67].
6.3 Influence of CRM strategies on the firm performance of architectural firms
The third objective of this study was to investigate how CRM strategies influence the firm performance of architectural firms. The results of regression analyses revealed the influence of CRM strategies used by the firms on their firm performance. The results imply that each client collaboration, client communication and service customisation strategy improves the financial performance of the firms when the other three strategies are held constant, while there is no improvement in financial performance when the four CRM strategies are used simultaneously. Also, only the client communication strategy seems to improve the non-financial performance of the firms when the other three strategies are held constant, while there appeared to be no improvement in non-financial performance when all the four CRM strategies are used simultaneously. Similarly, client collaboration, client communication and service customisation strategy each seem to improve the overall performance of the firms when the other three strategies are held constant, while there seems to be no improvement in overall performance when all the four CRM strategies are used simultaneously.
In sum, the client collaboration strategy appears to deliver the strongest improvement in financial performance, while client communication strategy was the only CRM strategy that can deliver improvement in non-financial performance and can also deliver the strongest improvement in the overall performance of the firms. Client orientation strategy and the simultaneous deployment of all the four CRM strategy dimensions did not seem to add value to the firms’ financial, non-financial and overall performance due to the lack of statistically significant influence on the criterion. Client orientation strategy is reputed as an important critical success factor of CRM successful implementation [38, 44]. As revealed in Table 4, firms that implement client orientation strategy focus all their internal system on interacting with clients on their preferred communication channels to acquire information about their needs and expectations and deliver service to satisfy them. Nevertheless, there is no consensus amongst reported findings of previous CRM authors about the influence of client orientation strategy on the performance of firms. While some authors reported its direct positive statistically significant influence on firm performance [68, 69], some others reported a lack of significant relationship [40, 70]. The finding of this study thus corroborates the reported lack of significant influence of client orientation strategy on performance of architectural firms. Some authors have suggested and reported that this lack of influence might be explained by the presence of mediators between client orientation and firm performance [68, 71]. The lack of significant joint influence of CRM strategy on firm performance has also been similarly attributed to the probable presence of mediators between CRM strategy and firm performance criterion. For example, Alshourah et al. [72] argued that CRM strategy is realised when it is implemented through enterprise factors like CRM process activities as well as external factors like clients’ responses. Nevertheless, the lack of joint influence of CRM strategy on firm performance whereas some of its dimensions (client collaboration, client communication and service customisation) had a significant influence on the criterion suggests that architectural firms should not invest company resources in all dimensions of CRM strategy simultaneously, but rather, they should prioritise on the strategies that deliver value to the firms.
With the use of analysed data from principals of architectural firms in the study area, this study has validated the proposal of the conceptual framework of this study. The conceptual framework proposed that unique CRM strategy responses of architectural firms to relational opportunities presented by features of the architectural market are viable predictors of variance in the financial, non-financial and overall performance of the firms. Thus, the current study filled the gap in knowledge about how the CRM strategy responses of architectural firms to market conditions influence their firm performance. Three objectives guided the study and from the results of the study, the following conclusions were made.
First, the results of the descriptive data analysis revealed that the architectural market in the study area has a mix of B2C, B2B and B2G clientele with individual clients being the most dominant. The most purchased services in the market are architectural building design services, construction supervision, building re-modelling, building construction and architectural visualisation. Second, the results of Principal Component Analysis (PCA) extraction method and Varimax rotation with Kaiser Normalisation revealed four factor-analytically manifested indicator variables of CRM strategy namely: (i) client collaboration strategy, (ii) client communication strategy, (iii) client orientation strategy and (iv) service customisation strategy. Thus, this corroborates the multi-dimensional ontology of the CRM strategy construct that is well established in the literatures [1-20, 39, 40]. Third, the results of the regression each of client collaboration strategy (β=0.62, p=0.01), client communication strategy (β=0.57, p=0.03) and service customisation strategy (β=0.33, p=0.05) had an independent statistically significant influence on the financial performance of the firms. Also, only client communication strategy (β=0.42, p=0.04) had a statistically significant influence on non-financial performance, while each of client collaboration strategy (β=0.63, p=0.01*), client communication strategy (β=0.64, p=0.05*) and service customisation strategy (β=0.41, p=0.00**) had an independent statistically significant influence on overall performance of the firms. Lastly, considering the absolute beta values of the models, client communication strategy (β=0.64, p=0.05*) emerged the CRM strategy that has the strongest influence on the firms’ performance in this study.
7.1 Managerial implications of the study
These results imply that managers of architectural firms should not invest company resources in all components of CRM strategy simultaneously, but rather prioritise the strategies that deliver value to the firms. This is particularly apt for start-up firms with a limited financial base. Also, managers of architectural firms seeking to improve their financial performance should prioritise enhancing their client collaboration strategy, while those seeking to improve their non-financial and overall performance should focus on improving the implementation of client communication strategy.
7.2 Implications for further studies
The lack of influence of client orientation strategy on firm performance contributes to the ongoing debate about the client orientation strategy → firm performance link. Future studies should investigate the probable existence of mediators between the client orientation strategy and firms’ performance. Also, further studies could investigate the factors responsible for the non-strategic behaviour of architectural firms towards some market conditions.
7.3 Limitations of the study
Regarding the limitations of the current research, it is noteworthy that the architectural market, CRM strategy and firm performance that were operationalised and explored in this study are dynamic phenomena in the industrial market. Longitudinal phenomena are known to possess cross-sectional patterns that could be captured by data and previous studies have copiously studied them accordingly [73, 74]. Nevertheless, the cross-sectional modelling of longitudinal phenomena like market characteristics, CRM strategy and firm performance is a limitation of this study that tempers the applicability of its findings until they are verified by further longitudinal studies. Furthermore, the results of this study are tentatively limited in applicability to the architectural industry in Nigeria until they are verified by further studies in other contexts of the industrial market and other geographical regions. Thus, further studies could use analysed panel data to test the results of this study in longitudinal research. Another limitation of this study is its focus on only the supply side of the dyadic relationship. Further studies could explore the integration of dyadic data from both architectural firms and the clients.
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