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Influence of Asset Tangibility on Financial Performance of Non-

Listed Building and Construction Firms in Kenya

Bonface Onyango Okombo

, Dr. Jackson Lumbasyo

, Moses Wanyoike

Degree of Master of Business Administration, University of Nairobi

Mount Kenya University

Lead Researcher, Gofuture Insights

DOI: https://doi.org/10.51583/IJLTEMAS.2026.150600143

Received: 28 June 2026; Accepted: 03 July 2026; Published: 17 July 2026

ABSTRACT

Asset tangibility constitutes a fundamental determinant through which business entities secure financing and

enhance their operational capacity, thus necessitating strategic management of tangible asset portfolios. The

principal challenge resides in optimizing the utilization of fixed assets to generate superior financial returns

while maintaining adequate collateral value for borrowing purposes. Kenya’s building and construction industry

recorded performance metrics of 3.2/3.5 in third order during the 2014/2016 study period, representing a notable

decline when juxtaposed against the 5.8 and 6.0 percentages achieved during 2005/2006. This suboptimal

performance trajectory within the construction sector, according to extant literature, was attributable to the asset

composition and utilization patterns among industry participants. This circumstance prompted the current

investigation into the effect of asset tangibility on the financial performance of non-listed building and

construction enterprises operating in Kenya. The research endeavor sought to assess the influence of asset

tangibility ratios on profitability metrics of these non-listed construction firms. The study employed Return on

Assets (ROA) and Return on Equity (ROE) as proxies for financial performance evaluation. The investigation

covered the period spanning 2014 to 2016. The theoretical framework incorporated Pecking Order theory. A

descriptive survey design was adopted as the research methodology. Secondary data were extracted from

consolidated financial statement records maintained at the National Construction Authority and the Kenya

Association of Manufacturers. The target population encompassed all 10 Tier 1 non-listed building and

construction firms registered with the National Construction Authority during the three-year study window. The

sample size corresponded to the entire target population, with secondary data serving as the primary information

source. Analytical techniques comprised mean calculations, correlation regression modeling, and ANOVA (F-

test). Findings were interpreted and presented through tabular and graphical representations, utilizing SPSS

software version 2.1 for efficient data processing. The outcomes derived from this analysis demonstrated that

asset tangibility exerts a discernible influence on the financial standing of non-listed building and construction

firms in Kenya. The evidence indicated that financial performance tends to improve when tangible assets are

effectively managed and utilized within the capital structure of the respective firm. This observation provides

compelling justification for strategic investment in fixed assets as opposed to maintaining excessive liquid

holdings. Proper asset management proved to enhance operational efficiency as it facilitates access to credit

through collateralization while generating productive capacity that exceeds the benefits expected of holding non-

productive assets. The findings of this study will enable management and financial practitioners to evaluate

corporate growth characteristics, asset utilization efficiency, and financial performance metrics to project future

enterprise value. The research recommends that business entities should work on optimizing asset tangibility

ratios within their capital structures as a strategy for enhancing financial performance and maximizing

shareholder wealth creation.

Keywords: asset tangibility, financial performance, non-listed building and construction firms, Kenya

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INTRODUCTION

Background of the study

Determining optimal levels of asset tangibility consistently presents a significant consideration for corporate

managers, as imprudent asset acquisition and management decisions can adversely affect organizational

performance unless thorough due diligence precedes the adoption of a viable asset structure. Whenever an

enterprise requires capital to sustain its operations and fund capital expenditures, deliberations regarding asset

composition inevitably emerge. Asset tangibility represents the proportion of a firm’s total assets that are

comprised of tangible fixed assets such as property, plant, and equipment, reflecting the extent to which an

organization possesses physical assets that can serve as collateral or generate productive capacity (Myers, 2014).

Business activities cannot proceed without adequate physical resources, making the availability of tangible

assets indispensable for organizational functionality. Every investment decision concerning fixed assets

necessitates concurrent consideration of funding mechanisms, given the direct implications for corporate

profitability. Various theoretical perspectives offer divergent views on the optimal asset composition,

underscoring the importance of rigorous analysis in formulating asset management policies that can serve as

strategic guides for enhancing corporate performance and delivering superior shareholder returns (Mwangi et

al, 2014).

Asset tangibility quantification is accomplished through the comparative analysis of fixed assets against total

assets, expressed as a ratio or percentage. Well-managed enterprises typically integrate both tangible and

intangible assets as complementary elements of their financial strategy (Dawar, 2014). Theoretical discourse

surrounding asset structure and profitability has remained particularly significant since Modigliani and Miller

(1958) posited that, in the absence of corporate taxes, bankruptcy costs, information asymmetry, market

inefficiencies, and transaction costs, firm value would ultimately remain indifferent to asset composition

decisions (Jermias, 2008). Collateral value can be enhanced through tangible asset accumulation, suggesting that

appropriate asset structure could optimize corporate value. Numerous theoretical frameworks have subsequently

emerged to elucidate corporate asset management patterns. Understanding the composition and utilization of

assets is essential, as this knowledge directly influences a firm’s competitive positioning within its industry. It

therefore falls upon corporate management to determine the optimal asset mix that will maximize financial

performance (Abor, 2007).

Asset acquisition and management through securities exchange markets has gained increasing prevalence in

Kenya. Non-listed building and construction firms have accumulated substantial tangible asset portfolios as a

mechanism for raising operational capital through collateralization and asset-backed financing (Anyanzwa,

2015). Many organizations employ asset tangibility to leverage their capital base with the objective of enhancing

profitability. Nevertheless, the efficacy of tangible assets in improving corporate financial health varies

considerably across enterprises, contingent upon prevailing economic conditions and asset utilization efficiency

at any given time (Maher & Andersson, 2013). Asset tangibility fundamentally represents the share of a firm’s

assets that are physical and can serve as collateral, encompassing land, buildings, machinery, equipment, and

vehicles. This metric has direct implications for organizational financial health and shareholder returns. The

increasing reliance on tangible asset accumulation by non-listed companies provided the impetus for

investigating its effects on financial position, constituting the primary motivation for this research. Furthermore,

the absence of consolidated theoretical perspectives on the causal chains linking asset tangibility to financial

performance reinforced the necessity for this investigative undertaking.

The manner in which an organization structures its asset portfolio fundamentally shapes its financial profile and

performance trajectory. This represents one of the most consequential financial decisions confronting

management, as it determines the enterprise’s capacity to satisfy the diverse expectations of its stakeholders

(Jensen, 2015). Asset tangibility involves the acquisition and maintenance of physical resources such as land,

buildings, machinery, and equipment. Unlike liquid assets, tangible assets provide collateral value that can

facilitate access to credit while simultaneously generating productive capacity. The organization bears the

obligation to maintain and depreciate these assets while ensuring they generate sufficient returns to justify their

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acquisition costs. Inefficient asset utilization can result in reduced profitability, liquidity constraints, or business

collapse (Bichsel & Blum, 2015). Tangible assets present both advantages and disadvantages that affect

organizational growth and long-term viability.

The utilization of tangible assets can confer certain benefits, including collateral provision for borrowing,

enhanced operational capacity, and improved creditor confidence, while simultaneously reducing the risk of

financial distress through productive asset deployment (Fama & French, 2010). Prudent management dictates

that executives should carefully balance such benefits against the costs of asset acquisition and maintenance,

making judicious decisions regarding asset composition to optimize performance (Krause & Litzenberger,

2010). Asset tangibility ratios serve as the primary metrics for evaluating asset structure, enabling comparison

of fixed assets against total assets. Lower ratios indicate greater reliance on intangible or liquid assets, whereas

higher percentages reflect substantial investment in physical assets.

Financial performance essentially represents an organization’s effectiveness in utilizing available resources to

generate revenue. It provides a basis for informed decision-making regarding business expansion strategies,

asset acquisition, and management oversight (Tehrani & Rahnama, 2016). Performance measurement reflects

managerial accomplishments in quantitative terms over specified periods, enabling comparisons with industry

competitors. According to Ongeri (2014), financial performance constitutes the monetary expression through

which business activities can be evaluated. It illustrates the extent to which shareholders have experienced

financial improvement over a given trading or accounting period compared to their initial position. This can be

effectively demonstrated through financial ratios derived from financial statements or market share price

movements. The primary corporate objective centers on maximizing shareholder wealth, with performance

measurement essentially assessing how much richer shareholders have become as a consequence of prudent

investment decisions over time (Barger & Pati, 2013).

Various absolute and relative indicators serve as measures of financial performance, including expenses,

earnings before tax and interest (EBTI), revenues, income levels, returns on assets, and returns on equity. The

most commonly employed performance metrics are ROA and ROE (Reese & Cool, 2016). Return on Equity

reflects the returns generated for shareholders, calculated by dividing net profit after tax (NPAT) by total equity

capital (TEC). This indicator demonstrates a firm’s profitability relative to the total shareholder investment.

Similarly, Return on Assets reveals the returns generated by all assets employed, serving as a comprehensive

index of financial health. This is computed by dividing net income after tax (NIAT) by total assets (TA)

(Khrawish, 2014). For the purposes of this investigation, ROA was utilized to measure the performance of non-

listed building and construction firms.

Kenya hosts a well-established and progressive construction industry within the East African region. The sector

encompasses enterprises engaged in the construction of commercial and residential structures, engineering

projects, and related trade services. The construction industry makes substantial contributions to the national

Gross Domestic Product (GDP), serving not merely as a significant economic player but also as a catalyst for

broader economic growth. According to the Kenya National Bureau of Statistics (KNBS), the construction and

real estate sectors have emerged as the most significant drivers of Kenya’s economic expansion over the past

five years. The sector contributed 7 percent of the country’s GDP in 2015, establishing its status among the

nation’s most developed industries.

The construction sector has prioritized the maintenance of existing infrastructure while simultaneously

integrating efficient and safer transportation systems and benchmarking infrastructural services against

international standards. The industry seeks to establish globally accepted performance standards that ensure

customer satisfaction and attract private sector participation in infrastructure provision, complementing

government interventions. As documented in the Economic Survey 2016 published by KNBS, the economy

experienced significant growth within the construction sector in 2015, registering a 13.06 percent increase in

value addition. Employment within the sector also grew by 11.4 percent, reaching 148.00 thousand employees

in 2015 compared to 132.90 thousand in the preceding year. Road expenditure increased by 79.2 percent during

the same period. The Government’s expenditure index rose from 263.4 in 2014 to approximately 386.7 in 2015,

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reflecting support for various projects. The sector expanded by 9.2 percent in 2016 compared to the slightly

higher growth rate of 13.9 percent recorded in 2015. The moderated growth rate was attributable to reduced

activity levels within the sector, partly due to the nearing completion of the Standard Gauge Railway (SGR)

project.

Building and construction firms operate within a regulated environment, with the National Construction

Authority (NCA) serving as the primary regulatory body for standardization purposes within the industry. The

NCA was established through an Act of Parliament and mandated with the responsibility of streamlining,

regulating, and building capacity within the construction sector. This regulatory framework encompasses project

registration, worker and supervisor accreditation, and contractor registration processes. The NCA maintains

comprehensive records of individual firms, serving as the final reference in case of disputes.

Research Problem

Asset tangibility plays a significant role in revealing the financial condition of enterprises, provided that the

results are accurately analyzed and applied. Nevertheless, determining what constitutes an optimal asset structure

remains an unresolved paradox within financial circles (Kajola, 2010). The relationship between asset

composition and profitability continues to generate debate, with prevailing theories and empirical studies

offering inconsistent conclusions. Modigliani and Miller (1984) proposed that asset structure may not affect firm

value in perfect markets. Conversely, other theoretical perspectives suggest that tangible assets enhance firm

value through collateral provision and operational efficiency. Jensen and Meckling (2010) supported this

perspective by characterizing tangible assets as a mechanism that reduces information asymmetry and enhances

creditor confidence, thereby positively influencing financial performance. These theoretical contradictions and

the ongoing debate provided the impetus for further investigation, motivating the present research.

The government’s commitment to undertaking major construction projects as part of its development agenda

has prompted many non-listed building and construction companies to pursue enhanced performance through

substantial asset accumulation. There exists considerable argumentation regarding asset tangibility as a

mechanism for enhancing profitability, provided that assets are acquired at favorable terms and deployed

productively. Tangible assets facilitate access to financing through collateralization while generating productive

capacity that can improve organizational performance if efficiently utilized (Anyanzwa, 2015). However, many

non-listed companies that have accumulated substantial fixed assets to improve their financial health have failed

to achieve their objectives, instead experiencing significant losses and eventual dissolution, as exemplified by

Athi River Mining Company, a cement manufacturer (Juma, 2016). The poor performance of such non-listed

entities despite substantial asset holdings underscores the necessity of investigating whether asset tangibility

genuinely affects performance outcomes.

Empirical investigations have produced divergent findings. Abor (2010) examined the relationship between

asset structure and profitability among listed Ghanaian corporations, finding a positive correlation between

tangible asset utilization and financial position. Kajirwa (2016) investigated the impact of asset structure on the

performance of Kenyan banks listed on the Nairobi Securities Exchange (NSE) using secondary data and

qualitative analysis techniques. The findings revealed a positive effect of tangible assets on bank profitability,

leading to recommendations for strategic asset acquisition.

Gleason (2011) conducted a study on performance and asset structure using data from 2008-2009 across 14

European Union countries, utilizing ROA as the performance metric. The results indicated that asset tangibility

significantly affected firm performance as measured by ROA. Abor (2010) similarly investigated the

relationship between asset structure and profitability among listed Ghanaian firms, finding substantial

significance for both parameters. Kaumbuthu (2010) examined the effects of asset structure on the financial

performance of manufacturing firms listed on the NSE, revealing a positive asset tangibility relationship. Raza

(2013) studied the impact of asset structure on firm performance among construction companies listed on the

Karachi Stock Exchange in Pakistan over the period 2004-2009, confirming that tangible assets positively

affected firm performance. These findings collectively reveal an empirical gap regarding the optimal asset

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composition and its subsequent effects on financial performance.

LITERATURE REVIEW

Theoretical Literature Review

Pecking Order Theory

This significant theoretical framework was primarily developed by Myers and Majluf in 1984. It posits that

organizations consistently prefer to utilize internal resources before considering external borrowing. When

companies require financing, they typically favor long-term tangible asset investment over short-term liquid

asset accumulation. Tangible assets are generally regarded as a preferred investment option due to their collateral

value. Due to information asymmetry, firms maintain a distinct hierarchy of asset preferences, typically investing

in fixed assets to enhance long-term operational capacity.

The theory further illustrates that companies maintain a preferred order of asset investment when funding their

operations (Cooper & Holmberg, 2015). In the absence of adequate information about investment opportunities,

firms prefer investing in tangible assets over intangible alternatives. Myers and Majluf further argued that by

investing in tangible assets, firms can mitigate information asymmetry problems. This explains why tangible

asset investments are particularly valuable, as information asymmetry between internal and external dimensions

is reduced through the observable nature of physical assets. The theory recommends that companies with

substantial information asymmetry should consider tangible asset investment, which provides collateral and

signals financial strength.

Bhaduri (2012) confirmed that when firms require external capital, they exhibit a preference for tangible asset

investment as a signal of creditworthiness. This creates a hierarchy of preference: fixed assets followed by other

investment types as an extreme choice. Regardless of the specific preference order, the critical element remains

the availability of financing sources. Internal earnings are preferred when available, but when external financing

is required, tangible assets become more attractive as they facilitate borrowing. Pandey (2010) concurred with

the pecking order proposition that corporate managers first resort to internally generated resources, only

considering external financing as a last option, with tangible assets serving as important collateral.

However, this theory has attracted criticism regarding its specific and general propositions. Adedji (2013) argued

that the theory’s assertion that tangible assets serve as optimal motivators for resource mobilization is

problematic, as it fails to account for other significant factors in asset investment decisions, including

depreciation rates, maintenance costs, and regulatory authority interventions. Cull and Xu (2014) confirmed that

the utilization of tangible assets remains contingent upon the firm’s ability to mobilize funds from external

sources and maintain asset efficiency.

Empirical Literature Review

Al-Tal (2014) investigated the relationship between profitability and asset structure among Ghanaian listed firms

over the period 1998-2002. The findings indicated that tangible assets positively correlate with profitability due

to enhanced operational capacity and collateral value. The study also found a positive relationship between asset

tangibility and profitability, attributed to the operational efficiency generated by fixed asset investment.

Adekunle (2014) examined the effects of asset structure on profitability among non-financial Nigerian listed

firms during 2001-2007. Utilizing secondary data and asset tangibility ratios as independent variables with ROE

and ROA as dependent indicators, the ordinary least squares estimation revealed that asset tangibility ratios have

a significant positive impact on firm performance.

Dufera (2010) conducted research on asset structure effects on profitability among Nigerian listed entities over

2001-2007. The investigation targeted 30 companies, employing asset tangibility ratios as independent variables

and ROE and ROA as dependent measures. Secondary data analysis revealed positive effects of asset tangibility

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on profitability for the sampled firms. Aliu (2015) examined asset structure determinants among manufacturing

corporations across America, France, Britain, Japan, and Italy, sampling 4,557 manufacturing firms and utilizing

secondary data. The findings indicated that asset tangibility positively correlates with profitability, although the

impact varies with firm size.

Langat et al. (2014) assessed the effect of asset structure on profitability among Kenyan tea manufacturing

companies. The study concluded that fixed asset investment positively relates to profitability at 1% and 5%

significance levels respectively. Pouraghajan and Malekian (2012) investigated how asset structure affects

profitability, establishing a positive correlation between asset tangibility and corporate profitability among 100

Iranian-listed construction firms. Muchugia (2013) examined the effects of asset structure on Kenyan

commercial bank financial performance. The study utilized firm size, tangible assets, and fixed assets as

independent variables with ROE as the dependent measure across 46 banks. The findings indicated that tangible

assets positively affect profitability. Masiega et al. (2013) investigated asset structure effects on profitability

among Kenyan listed manufacturing firms over 2007-2011, sampling 30 companies. The results demonstrated a

positive correlation between asset tangibility and performance, with positive performance impacts.

RESEARCH METHODOLOGY

The selected design of research was descriptive with a significant set of quantitative analysis (Abubakar, 2015).

This type of research design was selected owing to its enabling nature of giving descriptions on a given research

area, making an establishment on a relationship, and giving explanations on collected data in order to pay

attention to and prosecute both the differences and prevalent similarities on the subject references over a

stipulated time scope. The main focus was to establish the relationship between capital structure and financial

performance of the firms. In accordance to Construction Kenya, there are 10 tier one construction companies in

Kenya. The intended population of this work included all the 10 Tier 1 building and construction non-listed firms

registered and regulated by the National Construction Authority within the three-year study period of 2014 to

2018. All 10 tier 1 firms were included, therefore arose no need for sampling.

The study employed the use of predominantly data which is secondary. Data thus was collected through yearly

reports which included statements of financial position including all other corresponding relevant reports

published within study period of 2014- 2018. Such relevant financial information was thus collected from stored

sampled companies’ finance statements from the information desk upon submission of an introductory letter

from the school. A letter of introduction handed to the researcher by the school was in turn presented to respective

non-listed building and construction firms’ managers for purposes of gaining both consent and access to

published statements of financial position for the sole purpose of due analysis.

Collected data were however analyzed by clear use of mean, correlation (Pearson’s), and the regression model.

Analyzed data were interpreted and presented using figures and tables. A correlation technique was used to

illustrate the level of relationship among the identified variables. Correlational technique is important in research

as it aids knowing the level and nature in relationship over the list of variables used in the study. Correlation

results are also easier to interpret, cost friendly, and is commonly used in modern day to day decision making

among business entities. For the purposes of testing this respective research activity hypotheses, adoption of

descriptive type of data analysis; Pearson’s means of correlation, multiple regression analysis was also made use

of in order to test the relation between liquidity, asset tangibility and ratios of debt on firm performance. The

significance of regression co-efficient was established by looking at t-values

Data Analysis and Research Findings

Descriptive Statistics

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The descriptive statistics in this section laid down maximum, minimum, mean, and the standard deviations used

in describing data. It summarized the sampled information. It simplifies the information for ease of

understanding of the used data, by displaying the standard deviation, mean, maximum and minimum of the

sampled set of data.

Table 1. Descriptive Statistics

Minimum

Maximum

Mean

Std. Deviation

AssTang

0.27

1.21

.5281

.63725

ROE

-1.06

1.27

.0506

.52532

Valid N (listwise)

Source: Research Findings, (2023)

Asset tangibility and utilization is normally used to test ratios of tangible assets to total assets. The mean of

assets tangibility based on the observations is 0.5281, the standard deviation is 0.63725, suggesting uniformity

in the industry. This ratio suggests these companies can use their fixed asset to secure the amounts they borrow.

The mean ROE is indicated as 0.0506 or 5.06%, not surprising is that some firms reported negative return on

equity.

Asset Tangibility and Firms Performance (ROE)

The results on table 2 on show significant effect on a firm’s performance at a set significance level of less than

0.05.

In this section asset tangibility is used to predict financial performance, measure as return on equity. Presented

and explained below are model summary, analysis of variance, and the coefficient of predictor variable.

Dependent indicator is ROE, while independent one is asset tangibility. Such an idea is aimed to establish

whether asset tangibility on its own strength explain variation in return on equity.

Table 2. Model Summary, Asset Tangibility

Model

R Square

Adjusted R Square

Std. Error of the Estimate

.033

.001

-.020

.53047

a. Predictors: (Constant), AssTang

The above summary, exhibits relationship strength between model and the dependent indicator. The R-square, a

statistic that show the variation in independent variable (ROE) explained by variations in debt level (independent

variable) is at a low of 0.001 or 1%. Suggesting asset tangibility may not be used in instances of predicting return

on equity (ROE) because debt explains only 1% of variation in ROE.

Table 3. Coefficients: Asset Tangibility and ROE

Model

Unstandardized

Coefficients (B)

Std. Error

Standardized

Coefficients (Beta)

Sig.

(Constant)

0.050

0.075

—

0.663

0.510

Asset Tangibility

-0.027

0.119

-0.033

-0.230

0.819

Model Summary

R²

Interpretation

0.001

Asset Tangibility explains 0.1% of the variation in ROE.

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Dependent Variable: Firm performance (ROE

Table 3. Anova

Model

Sum of Squares

Mean Square

Sig.

Regression

.015

.053

.819

Residual

13.507

.281

Total

13.522

a. Predictors: (Constant), AssTang

b. Dependent Variable: ROE

ANOVA does check the model’s fitness, that is, tests the acceptability of the model. There were 50 observations.

The Regression row does display the respective models accounted for information, in this respect, 0. 015.

Residual that is, the model’s none accounted for variation, is 13.507, much higher than the regression (0.15),

suggesting that asset tangibility does not predict ROE. The significance value of the regression, which is 0.819,

is more than α -level of 0.05, a clear indication that explained variations by the model is simply by chance.

As exhibited in table 3 above, Asset tangibility can evidently explain 6.4% subsequent changes over firm’s

performance. Total assets turnover is 0.17, a clear suggestion that returns on assets make improvement by the

said margin of 0.17 in percentage. Significantly, this can give an explanation that in instances where assets’

tangibility is rightly managed, it does have an effect on a firm’s success. Hence, that denotes some form of

improvement on the performance of the business entity. In accordance to displayed results, hypothesis H01 is

thus accepted, that asset tangibility has statistical significance; positive in effect on firm performance.

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

Summary

This research investigation was undertaken to ascertain the effects of asset tangibility on the financial

performance of non-listed building and construction firms in Kenya over the designated period 2014-2018. The

independent variable of this study was asset tangibility, while the dependent variable was financial performance

measured through return on equity (ROE). Descriptive statistics derived through mean, standard deviation, and

regression analyses were employed to examine the effects of asset tangibility on financial performance. The

descriptive analysis findings indicated that the mean asset tangibility ratio was 0.5281 with a standard deviation

of 0.63725. The average ROE stood at 0.0506 with a standard deviation of 0.52532.

The research concluded that there exists no statistically significant association between asset tangibility and firm

performance. The coefficient of asset tangibility (-0.027) with a significance value of 0.819 indicates that

tangible assets do not exert a measurable influence on return on equity. The relationship between asset structure

and performance, while suggesting a weak inverse pattern, fails to achieve statistical significance, indicating that

asset tangibility levels cannot reliably predict firm performance in the context of the sampled firms.

Conclusions

This research exercise examined the influence of asset tangibility on the financial performance of non-listed

building and construction firms in Kenya. Data were sourced from secondary sources, with the sample

comprising all 10 Tier 1 non-listed building and construction companies. The findings indicate that tangible asset

investment does not necessarily enhance shareholder value through improved ROE. This conclusion aligns with

certain earlier studies while contradicting others, suggesting that the relationship between asset structure and

firm performance remains a subject requiring continued investigation.

Recommendations

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The findings of this research carry compelling significance for individual firms, the broader industry, and the

macro-economy. Given the observed negative correlation between asset tangibility and firm performance, this

study recommends that business managers should exercise prudence in optimizing asset composition within their

capital structures. Strategic asset investment can serve as a mechanism for increasing firm value and enhancing

shareholder wealth.

This research further recommends that firms should carefully evaluate the cost-benefit implications of significant

fixed asset investments. Since many firms rely on collateralization for borrowing, the relationship between asset

acquisition costs and operational benefits should be carefully assessed. Financial managers must remain

proactive in comprehending the effects of asset structure fluctuations on their firms’ financial performance.

Firms with balanced asset portfolios appear to perform better compared to those with excessive fixed asset

concentration within the industry.

Limitations of the Study

This research exercise focused exclusively on the 10 Tier 1 non-listed firms registered with the National

Construction Authority. Consequently, the research findings cannot be generalized to all firms operating in

Kenya. The primary objective of this study was to examine the relationship between asset structure and financial

performance of building and construction companies; therefore, the results are limited specifically to non-listed

building and construction firms. Additionally, the investigation was conducted within Kenya’s geographical

boundaries, limiting applicability to other jurisdictions.

The study was constrained by information deficiencies regarding the relationship between asset tangibility ratios

and enterprise performance. Furthermore, the research was confined to the three-year period between 2014 and

2016, which may have been limiting, as a longer timeframe could have revealed more comprehensive patterns.

The study also focused on a limited number of performance metrics, specifically ROE, for assessing firm

performance. Finally, this work concentrated predominantly on major construction companies, excluding

smaller medium-sized construction enterprises in Kenya.

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