Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia

Birhan Ambachew Taye; Aychew Kassa Belete; Bantie Getnet Yirsaw

doi:doi:10.11648/j.ijber.20241302.12

Research Article |

| Peer-Reviewed

Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia

Birhan Ambachew Taye^*

, Aychew Kassa Belete

, Bantie Getnet Yirsaw

Published in International Journal of Business and Economics Research (Volume 13, Issue 2)

Received: 9 April 2024 Accepted: 22 April 2024 Published: 17 May 2024

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Abstract

Introduction: Saving behaviour is a critical aspect of financial planning, where individuals defer present consumption to enhance their quality of life and meet future needs. The study aims to gain a comprehensive understanding of their financial behaviours, identify the factors that influence their financial decision-making, and compare the financial behaviours among different groups of academic employees. Methods: Employing a quantitative research approach, this study utilizes a structured questionnaire to gather data from academic employees. The questionnaire evaluates variables such as income level, education, job security, and financial goals to examine their impact on saving behaviours and financial readiness. Binary logistic regression analysis is employed to assess the influence of each factor on the dependent variable. Results: The findings indicate that a majority (83.3%) of academic employees have not previously saved, while a minority (16.7%) have managed to accumulate some savings. Statistical analyses, including chi-square tests, demonstrate significant associations between saving habits and variables such as gender, age, marital status, monthly expenses, and housing. The binary logistic regression analysis further highlights the significance of factors such as gender, age, education level, expenses, housing, additional income, and participation in savings groups in shaping employees' saving behaviours. Conclusion: This study contributes to the understanding of Ethiopian savings practices and personal finance by examining and comparing saving behaviours and financial preparedness across different academic institutions. It provides insights into the factors influencing financial decision-making and proposes strategies for enhancing financial literacy.

Published in	International Journal of Business and Economics Research (Volume 13, Issue 2)
DOI	10.11648/j.ijber.20241302.12
Page(s)	36-45
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Saving Habits, Financial Preparedness, Academic Employees, Ethiopia, Logistic Regression

1. Introduction

Saving is a deliberate act of deferring present consumption in order to enhance one's quality of life and meet future needs. Various methods, such as depositing money in a bank account or making investments, can be employed to save funds. Implementing an automatic savings plan is considered an effective approach to saving

[1]

. Saving behaviour plays a pivotal role in fostering long-term economic growth, particularly at the individual and household levels. Accumulating substantial savings provides individuals with enhanced financial freedom, investment opportunities, and the ability to plan for future financial requirements. It is imperative to view saving within the framework of comprehensive financial planning and effective management practices

[2]

Savings institutions, including savings associations, building loan associations, and cooperative banks, primarily function to provide mortgage loans for residential properties. These organizations prioritize single-family homes and possess the necessary expertise in promoting savings in this domain

[3, 4]

. However, in Ethiopia, the savings rate has exhibited fluctuations over time. Moreover, although Ethiopia may be witnessing increased savings, it is often happening outside the formal financial sector

[5]

. Encouraging financial saving habits aims to raise awareness among individuals about financial opportunities, choices, and potential consequences

[6]

. There is a growing recognition of the significance of financial education in promoting saving behaviours

[7]

. Financial education serves as a means to enhance savings and asset accumulation. Understanding the process and benefits of asset accumulation is likely to influence an individual's willingness to save

[8]

. Previous research emphasizes the importance of prioritizing saving practices in various areas, including education, consumption, healthcare, family support, job creation, and income generation, particularly in southern Ethiopia

[9]

. Examining the savings services utilized by individuals in the community has been shown to enhance their saving behaviours

[10]

. To address this, it is essential to involve governmental entities and implement recommended saving strategies within households, institutions, and sectors of the community.

However, existing studies primarily rely on descriptive statistics, limiting the broader application of their findings. Furthermore, there is a lack of understanding and knowledge regarding the financial behaviours and readiness of academic staff members in Ethiopia. This knowledge gap hampers their ability to make informed financial decisions and adequately plan for their future. Therefore, this research aims to gain a comprehensive understanding of the financial behaviours and preparedness of academic employees, identify the factors influencing their financial decision-making, and compare the financial behaviours among different groups of academic employees. Consequently, it is crucial to examine the saving patterns of employees. Logistic regression models are predominantly applied in this study to identify significant factors associated with employees who do not save. Therefore the purpose of this study is to address the knowledge gap regarding the financial behaviours and preparedness of academic staff members in Ethiopia. The study aims to gain a comprehensive understanding of their financial behaviours, identify the factors that influence their financial decision-making, and compare the financial behaviours among different groups of academic employees. The research seeks to examine the saving patterns of employees and identify significant factors associated with employees who do not save. By conducting this study, the researchers aim to provide insights that can help academic employees make informed financial decisions and adequately plan for their future. Additionally, the study aims to contribute to the existing body of knowledge by going beyond descriptive statistics and using logistic regression models to analyse the factors influencing saving behaviours. Ultimately, the findings of the study can inform the development of recommended saving strategies and financial education initiatives that involve governmental entities, households, institutions, and sectors of the community, with the goal of improving financial preparedness and promoting saving behaviours among academic employees in Ethiopia.

Theoretical Framework

The study incorporates three theoretical frameworks, namely Social Learning Theory, Behavioural Economics, and the Financial Capability Framework, to comprehend the saving habits and financial preparedness of academic employees. Social Learning Theory posits that individuals acquire new behaviours through observation and imitation of others. In the context of this study, it will be utilized to explore how the saving habits and financial preparedness of academic employees are influenced by the behaviours and financial practices of their peers or colleagues. Behavioural Economics integrates insights from the field of behavioural economics, incorporating concepts such as present bias or loss aversion. By incorporating these concepts into the theoretical framework, the study seeks to understand the cognitive biases and psychological factors that may impact the saving habits and financial preparedness of academic employees. The Financial Capability Framework focuses on assessing individuals' financial knowledge, skills, attitudes, and access to financial resources. This framework will be employed to evaluate the financial capability of academic employees and examine how these factors contribute to their saving practices and financial preparedness. By considering these theoretical frameworks, the study aims to provide a comprehensive understanding of the factors that influence the saving practices and financial preparedness of academic employees.

2. Methods

This study was conducted in the North Wollo zone, which is situated in the Amhara region of Ethiopia. The primary urban centre in this zone is Woldia, located approximately 521 kilometers away from the capital city, Addis Ababa. The target population for this study comprised all academic staff members currently employed at colleges and universities operating within the North Wollo zone.

To collect data for this study, a structured questionnaire was employed as the main method of data collection. The research design adopted for this study was cross-sectional in nature, enabling data to be collected at a single point in time. Stratified random sampling was utilized to select participants from the target population. Specifically, academic staff members from Woldia University, Woldia Teachers College, North East College, Enkodo College, Yeju College, and Woldia TVT were identified as the primary sampling units. The sample size for each selected institution was determined using the chance related to size sampling technique without replacement. Within each chosen stratum, an individual employee was randomly selected using simple random sampling. The sample size for this study was determined based on stratified sampling, ensuring a 95% confidence level. The sample size for this study was determined using stratified sampling with a 95% confidence level. The formula used for sample size calculation was n =

\frac{n_{0}}{1 + \frac{n_{0}}{N}}

since

\frac{n_{0}}{N}

> 0.05, where

n_{0}

is calculated as

\frac{({z_{α / 2})}^{2} pq}{d^{2}}

, with

z_{α / 2}

= 1.96, p = 0.3 (based on a pilot survey), and d = 0.04 (relative error). This yielded an initial sample size of

n_{0}

= 504. Based on the criterion of

n_{0}

/N > 0.05, the definitive sample size for this study was established to be 312 academic employees residing in Woldia City. Proportional allocation was utilized to distribute the sample sizes among the various strata. The distribution of sampled academic staff members from different institutions in Woldia City was as follows: Woldia University (81), Woldia Teachers College (57), Northeast College (31), Enkodo College (47), Adago College (26), and Woldia TVT College (70).

2.1. Variables in the Study

This research focuses on investigating the saving practices of individuals, which are categorized into two distinct groups: 1) "save out of income" and 2) "no save out of income." The variable of interest is binary or dichotomous in nature. The study examines several factors as potential influences on saving habits, including age, gender, educational level, marital status, monthly salary, monthly expenditure, housing status, extra income, association with saving methods, addiction, and involvement in academic affairs. These variables are considered independent variables as they are hypothesized to have an impact on the dependent variable, which is the status of saving habits.

2.2. Method of Data Analysis

The collected data underwent statistical analysis using SPSS software version 26. Descriptive statistics, such as tables, frequency distributions, and percentages, were employed to provide a concise summary of the data. Chi-square statistics were used to explore the associations between the variables being studied. Additionally, binary logistic regression analysis was conducted to assess the impact of different dimensions of the independent variables on the outcome variable.

Binary logistic regression is a statistical technique suitable for analyzing the likelihood of an event when the response variable has two categorical outcomes. In this study, logistic regression was chosen as the appropriate method because it allows for the investigation of how various independent variables influence the probability of the dependent variable occurring. The logistic regression equation employed the logit transformation of 𝑝𝑖, which offers an alternative representation of the model and facilitates the examination of the relationship between the independent and dependent variables. Logistic regression is commonly used when the response variable is dichotomous. In this study, the response variable was denoted as Y, with y=1 indicating the presence of a specific characteristic of interest and y=0 indicating the absence of that characteristic

[11]

. As a result, the logit transformation of 𝑝𝑖 is an alternative form of the logistic regression equation, which is given as:

Logit (

P_{i}

) = log

(\frac{P_{i}}{1 - P_{i}})

B_{0}

B_{1} X_{11}

B_{2} X_{12}

+...+

B_{k} X_{1 k}

Model Fit

In logistic regression, evaluating the goodness of fit entails examining the agreement between the predicted values and the observed values. To assess the adequacy of the model, various tests are conducted in logistic regression by employing the likelihood function and the deviance statistic to measure the disparity between predicted and observed values. These tests include the likelihood-ratio test and the Hosmer and Lemeshow test statistic, which help determine the suitability of predictors in the model. Specifically, the Hosmer and Lemeshow goodness-of-fit statistic examines the concordance between observed and predicted values for the dependent variable. It provides valuable insights into response patterns across different combinations of covariates and the average estimated probability. This statistic serves as a conclusive assessment of the model's fit to the observed data. Furthermore, the odds ratio is a measure used to compare the likelihood of an outcome occurring when a specific treatment is administered versus when it is not. Calculated by dividing the probability of the event occurring by the probability of the event not occurring, the odds ratio offers valuable insights into the relationship between the treatment and the outcome.

3. Results

The study findings reveal that among the participants, 16.7% (52 individuals) reported saving a portion of their total income, while the majority, 83.3% (260 respondents), did not save any money. In terms of gender distribution, 12.2% (38 respondents) were female, while 87.8% (274 respondents) were male. Regarding age distribution, 20.5% (64 respondents) were below 30 years old, 48.1% (150 respondents) were aged between 30-35, 20.5% (64 respondents) were aged between 35-40, and 10.9% (34 respondents) were above 40. In relation to educational level, 2.9% (9 respondents) held a degree, 93.6% (292 respondents) held a master's degree, and 3.5% (11 respondents) held a PhD. The distribution of marital status indicated that 61.5% (192 respondents) were single, 33.3% (104 respondents) were married, 4.5% (14 respondents) were separated, and 0.6% (2 respondents) were widowed. These findings provide insights into the saving habits and demographic characteristics of the study participants.

Regarding monthly net income, 2.9% (9 respondents) had a monthly net income below 5000, while the majority, 93.6% (292 respondents), had a monthly net income ranging from 5000-9000. Only a small proportion, 3.5% (11 respondents), reported a monthly net income above 9000.

In terms of monthly expenditures, 0.6% (2 individuals) reported expenses below 3000, indicating relatively low monthly expenses. A significant portion, 35.3% (110 respondents), reported expenditures between 3000-7500, while 44.6% (139 respondents) reported expenditures between 7500-9000. Additionally, 19.6% (61 respondents) reported expenditures above 9000, suggesting higher monthly expenses for some respondents.

Regarding involvement in academic affairs, approximately 15.7% (49 respondents) were engaged in educational activities or pursuing academic goals, while the majority, 84.3% (263 respondents), were not currently involved in academic affairs.

In terms of housing status, 6.1% (19 respondents) owned their houses, while the majority, 93.9% (293 respondents), rented their houses, indicating a higher prevalence of renting among the participants.

Regarding extra income, 18.9% (59 respondents) reported having additional sources of income beyond their primary earnings, while the majority, 81.1% (253 respondents), did not have any extra income.

When it came to saving methods, 10.3% (32 respondents) reported utilizing modern saving methods, while the majority, 89.7% (280 respondents), used traditional saving methods such as savings accounts, cash, or physical assets.

In terms of the number of family members in their homes, 46.5% (145 respondents) had 1-2 family members, 43.3% (135 respondents) had 3-4 family members, 3.5% (11 respondents) had 4-5 family members, and 6.7% (21 respondents) had more than 5 family members, indicating varying household sizes among the participants.

Regarding addiction, 3.2% (10 respondents) reported having an addiction, while the vast majority, 96.8% (302 respondents), reported not having an addiction, indicating a relatively low prevalence of self-reported addiction among the participants.

Table 1. Descriptive statistics summary.

Variables	Category	Frequency	Percentage
save some money out of your total income	'save out of income	52	16.7%
save some money out of your total income	'No, save from income'	260	83.3%
Gender	Female	38	12.2%
Gender	Male	274	87.8%
Age	<30	64	20.5%
	30-35	150	48.1%
	35-40	64	20.5%
	>40	34	10.9%
Educational level	Degree	9	2.9%
	Masters	292	93.6%
	PhD	11	3.5%
Marital status	Single	192	61.5%
	Married	104	33.3%
	Separated	14	4.5%
	Widowed	2	0.6%
monthly net income	<5000	9	2.9%
	5000-9000	292	93.6%
	>9000	11	3.5%
cost of expenditures per month	<3000	2	0.6%
	Affairs	110	35.3%
	7500-9000	139	44.6%
	>9000	61	19.6%
Academic Affairs	Yes	49	15.7%
Academic Affairs	No	263	84.3%
housing status	Owned	19	6.1%
housing status	Rented	293	93.9%
have an extra income	Yes	59	18.9%
have an extra income	No	253	81.1%
a member of any savings association	Yes	32	10.3%
a member of any savings association	No	280	89.7%
saving methods	Modern	32	10.3%
saving methods	Traditional	280	89.7%
Number of families in the home	1-2	145	46.5%
	3-4	135	43.3%
	4-5	11	3.5%
	More than 5	21	6.7%
Addiction	Yes	10	3.2%
Addiction	No	302	96.8%

Based on the data presented in Table 2, the analysis of the association between gender and saving habits reveals that 52.6% of female employees did not save any portion of their income, while the remaining 47.4% of female employees did save. In contrast, the majority of male employees (87.6%) did not save from their income, with only 12.6% of male employees engaging in saving behaviours.

When examining the relationship between age and saving habits, the results indicate that the majority of employees across different age categories tended not to save. Specifically, 87.5% of employees below the age of 30, 84.7% of employees aged between 30-35, 85.9% of employees aged between 35-40, and 64.7% of employees above the age of 40 did not save from their income.

Furthermore, the analysis reveals a significant association between marital status and saving habits. Among the different marital status categories, the majority of single employees (88%), married employees (76%), divorced employees (78.6%), and widowed employees (50%) did not save from their income.

Regarding the relationship between monthly expenditures and saving habits, the majority of employees (89.9%) with monthly expenditures ranging from 7500-9000 Ethiopian Birr did not engage in saving behaviours.

When examining the relationship between housing status and saving habits, it becomes evident that employees residing in rented housing were less likely to save from their earnings compared to other housing arrangements.

Overall, the results indicate that gender, age, marital status, monthly expenditures, and housing status display statistically significant relationships with employee saving habits, as indicated by p-values below 0.05 (the chosen level of significance). Among these significant variables, gender demonstrates a strong positive relationship with saving habits (Phi = 0.307 and Cramér's V = 0.307), while housing status exhibits a weaker positive relationship (Phi = 0.138 and Cramér's V = 0.138).

Table 2. Association between variables.

Variable	Categories	Saving Habit		Chi-square	p-value	Phi and Cramer’s v
Variable	Categories	'save out of income	'No, save from income'	Chi-square	p-value	Phi and Cramer’s v
Gender	Female	18 (47.4%)	20 (52.6%)	29.366	0.000	0.307 0307
Gender	Male	34 (12.4%)	240 (87.6)	29.366	0.000	0.307 0307
Age	<30	8 (12.5%)	56 (87.5%)	9.799	0.020	0.177 0.177
	30-35	23 (15.3%)	127 (84.7%)
	35-40	9 (14.1%)	55 (85.9%)
	>40	12 (35.3%)	22 (64.7%)
Educational level	Degree	0 (0%)	9 (100%)	4.884	0.087	0.125 0.125
	Masters	48 (16.4%)	244 (83.6%)
	PhD	4 (36.4%)	7 (63.6%)
Marital status	Single	23 (12%)	169 (88%)	8.935	0.030	0.169 0.169
	Married	25 (24%)	79 (76%)
	Separated	3 (21.4%)	11 (78.6%)
	Widowed	1 (50%)	1 (50%)
monthly net income	<5000	0 (0%)	9 (100%)	4.884	0.087	0.125 0.125
	5000-9000	48 (16.4%)	244 (83.6%)
	>9000	4 (36.4%)	7 (63.6%)
cost of expenditures per month	<3000	2 (100%)	0 (0%)	22.983	0.000	0.271 0.271
	3000-7500	29 (26.4%)	81 (73.6%)
	7500-9000	14 (10.1%)	125 (89.9%)
	>9000	7 (11.5%)	54 (88.5%)
Academic Affairs	Yes	11 (22.4%)	38 (77.6%)	1.399	0.237	0.067 0.067
Academic Affairs	No	41 (15.6%)	222 (84.4%)	1.399	0.237	0.067 0.067
housing status	Owned	7 (36.8%)	12 (63.2%)	5.930	0.015	0.138 0.138
housing status	Rented	45 (15.4%)	248 (84.6%)	5.930	0.015	0.138 0.138
have an extra income	Yes	6 (10.2%)	53 (89.8%)	2.211	0.137	-0.84 0.84
have an extra income	No	46 (18.2%)	207 (81.8%)	2.211	0.137	-0.84 0.84
a member of any savings association	Yes	3 (9.4%)	29 (90.6%)	1.365	0.243	-0.066 0.066
a member of any savings association	No	49 (17.5%)	231 (82.5%)	1.365	0.243	-0.066 0.066
saving methods	Modern	3 (9.4%)	29 (90.6%)	1.365	0.243	-0.066 0.066
saving methods	Traditional	49 (17.5%)	231 (82.5%)	1.365	0.243	-0.066 0.066
Number of families in the home	1-2	21 (14.5%)	124 (85.5%)	3.337	0.342	0.103 0.103
	3-4	28 (20.7%)	107 (79.3%)
	4-5	1 (9.1%)	10 (90.9%)
	More than 5	2 (9.5%)	19 (90.5%)
Addiction	Yes	1 (10%)	9 (90%)	0.331	0.565	-0.033 0.033
Addiction	No	51 (16.9%)	251 (83.1%)	0.331	0.565	-0.033 0.033

Table 3 presents the values of the Cox and Snell R square (0.257) and the Nagelkerke R square (0.432). These statistics indicate that the model explains approximately 43.2% of the variance, suggesting a substantial impact of the model.

Table 3. Model Summary.

Step	-2 Loglikelihood	Cox & Snell R Square	Nagelkerke R Square
1	188.640^a	.257	.432

Table 4 depicts that Hosmer and Lemeshow test goodness of fittest has a p-value = 0.061, which is greater than 𝛼_value= 0.05, and it indicates that the model estimates fit the data and acceptable level. As a result, there is enough evidence that the model fits the data well.

Table 4. Hosmer-Lemeshow Test.

Step	Chi-square	Df		Sig.
1	14.995		8	.061

Binary Logistic Regression Results

Table 5 presents the results of a binary logistic regression analysis investigating the relationship between several independent variables and a binary dependent variable, specifically the saving practice. The following is a concise interpretation of the findings.

Female employees who have a saving habit are 0.033 times as likely as male employees without a saving habit, as indicated by an odds ratio of 0.033. In other words, the odds of female employees with a saving habit are significantly lower compared to their male counterparts without a saving habit.

Age also plays a significant role in employees' saving habits (p < 0.001). Employees below the age of 30 are 32.423 times more likely to save compared to employees aged 40 and above. Similarly, employees in the age range of 30-35 are 7.451 times more likely to save than employees aged 40 and above.

The educational level of employees also influences their saving habits. Employees with a master's degree who save are 28.590 times more likely to save than employees with a doctorate who do not save.

Therefore, other predictor variables that demonstrate a significant relationship with the dependent variable can be interpreted in a similar manner. Overall, gender, age, educational level, monthly expenditure, housing status, extra income, and membership in a savings institution all have p-values below the predetermined significance level (α-value = 0.05). This indicates that there is sufficient evidence to conclude that these variables significantly influence the saving habits of employees.

On the other hand, the study did not find a statistically significant effect of marital status, family size, and addiction on the saving habits of employees, as indicated by p-values greater than the α-value of 0.05.

Table 5. The variables in the equation.

Variables	B	S.E.	Wald	df	Sig.	Exp(B)
Gender (1)	-3.404	.644	27.933	1	.000	.033
Age			20.006	3	.000
Age (1)	3.479	.824	17.810	1	.000	32.423
Age (2)	2.008	.594	11.436	1	.001	7.451
Age (3)	2.545	.727	12.271	1	.000	12.744
Educational_level			8.483	2	.014
Educational_level (1)	2.571	0.651	.000	1	.999	13.08
Educational_level (2)	3.353	1.151	8.483	1	.004	28.590
Marital_Satus			4.413	3	.220
Marital_Satus (1)	.081	2.253	.001	1	.971	1.084
Marital_Satus (2)	-.457	2.231	.042	1	.838	.633
Marital_Satus (3)	-2.643	2.616	1.021	1	.312	.071
Expenditure			26.320	3	.000
Expenditure (1)	-23.731	26502.634	.000	1	.999	.000
Expenditure (2)	-2.719	.697	15.199	1	.000	.066
Expenditure (3)	-.146	.666	Addiction	1	.826	.864
Acadamic_afairs (1)	-.424	.503	.711	1	.399	.655
Housing_status (1)	-2.048	.674	9.240	1	.002	.129
Extra_income (1)	2.879	.667	18.626	1	.000	17.798
Member (1)	2.623	.901	8.465	1	.004	13.772
Family_Size			5.303	3	.151
Family_Size (1)	-1.127	1.130	.995	1	.319	.324
Family_Size (2)	-1.622	1.035	2.455	1	.117	.198
Family_Size (3)	1.836	2.021	.825	1	.364	6.272
Addiction (1)	-.990	1.212	.667	1	.414	.372
Constant	-.540	2.597	.043	1	.835	.583

4. Discussion

The negative coefficient for Gender (1) indicates that being Male is linked to a lower likelihood of having a saving practice. This finding is consistent with

[12]

showing gender differences in saving behavior, where males tend to save less compared to females. Various factors such as cultural norms, financial responsibilities, and individual attitudes towards saving can influence saving habits. Women are more likely to save and engage in more conservative financial behaviours than men. This difference may be attributed to factors like risk preferences, income disparities, and societal expectations.

The presence of significant coefficients for various age groups indicates that age is related to saving habits. The positive coefficients for Age (1), Age(2), and Age(3) indicate that as age increases, the likelihood of having a saving habit also increases. This finding is in line with

[13-15]

consistently showing a positive correlation between age and saving behaviour. Older people are more likely to have financial stability, long-term goals, and a greater understanding of the value of saving for retirement or emergencies.

The coefficients for different educational levels indicate that higher educational attainment is associated with a higher likelihood of having a saving habit. This finding is consistent with

[16]

which has shown a positive relationship between education and saving behaviour. Higher education can equip individuals with better financial literacy, higher income potential, and a better understanding of the advantages of saving. It provides individuals with financial knowledge, critical thinking skills, and career opportunities that positively influence their financial habits, including saving.

The coefficients for marital status categories do not demonstrate consistent or statistically significant relationships with saving habits. This finding may contrast with

[17-19]

that has identified marital status as a potential factor influencing saving behaviour. For example, married individuals may have more financial stability and shared financial goals, which could lead to higher saving rates. However, the lack of significance in this study suggests that the relationship between marital status and saving habits may vary depending on the specific context and characteristics of the sample. It is important to consider that the findings of this study may not generalize to all populations or contexts, and further research is needed to examine the relationship between marital status and saving behaviour in different settings.

This finding implies that employees who rent private homes have poorer savings practices than homeowners. This result is consistent with the findings of the

[15, 20]

. This study confirms Employee education status has also been found to influence their saving habits. Similarly,

[21]

discovered that highly educated people have higher average saving habits. According to

[22]

, membership in a savings association improves employees' saving habits, and this research backs up the claim.

It is crucial to remember that the results presented present only a portion of the story; a thorough understanding necessitates taking into account the larger body of research on saving behaviour. Various other factors, such as income levels, financial literacy, cultural norms, and economic conditions, can influence saving habits. Moreover, the specific measures and definitions used in this study may differ from those in other research, making direct comparisons challenging. Accessing the complete study and exploring additional research in the field of saving behaviour would help gain a more comprehensive understanding of the results and their relation to other studies.

5. Conclusions

The statistical analysis using Chi-square statistics revealed a statistically significant correlation between gender, age, marital status, monthly expenditure, and housing status with respect to the saving habits of employees. In addition, the results of the binary logistic regression analysis showed that the most important variables affecting the saving behaviours of academic staff members were gender, age, educational attainment, monthly expenses, housing status, additional income, and membership in a savings institution. Specifically, having saving habits and lower salaries were indicative of lower saving habits among employees. However, the results of this study showed that addiction, family size, and marital status did not significantly predict employees' saving habits.

These findings contribute valuable insights to the existing body of literature on personal finance and savings behaviour in Ethiopia. This study sheds light on potential areas for financial literacy and education improvement while offering a deeper understanding of the factors influencing financial decision-making by comparing the saving practices and financial readiness of academic staff members across various institutions.

The implications of this study can inform policymakers, employers, and financial institutions about the specific needs and challenges faced by employees about their saving habits. This knowledge can guide the development of targeted interventions and support mechanisms to enhance financial well-being and promote better-saving practices among employees.

Abbreviations

SE: Standard Error

Df: Degree of Freedom

EtB: Ethiopian Birr

Sig: Significant

Exp: Exponent

Author Contributions

BA participated in the process of organizing, brainstorming, analyzing, and interpreting the findings. AK contributed to the initial drafting, subsequent revisions, and critical review of the article. BG was responsible for designing the research, collecting and analyzing the data for the study. All authors made equal contributions to the final version of the manuscript. Furthermore, all authors read and gave their approval to the final manuscript.

Data Availability of Statement

The data that support the results have been included in the study and will be available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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APA Style

Taye, B. A., Belete, A. K., Yirsaw, B. G. (2024). Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia. International Journal of Business and Economics Research, 13(2), 36-45. https://doi.org/10.11648/j.ijber.20241302.12

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ACS Style

Taye, B. A.; Belete, A. K.; Yirsaw, B. G. Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia. Int. J. Bus. Econ. Res. 2024, 13(2), 36-45. doi: 10.11648/j.ijber.20241302.12

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AMA Style

Taye BA, Belete AK, Yirsaw BG. Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia. Int J Bus Econ Res. 2024;13(2):36-45. doi: 10.11648/j.ijber.20241302.12

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@article{10.11648/j.ijber.20241302.12,
  author = {Birhan Ambachew Taye and Aychew Kassa Belete and Bantie Getnet Yirsaw},
  title = {Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia
},
  journal = {International Journal of Business and Economics Research},
  volume = {13},
  number = {2},
  pages = {36-45},
  doi = {10.11648/j.ijber.20241302.12},
  url = {https://doi.org/10.11648/j.ijber.20241302.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20241302.12},
  abstract = {Introduction: Saving behaviour is a critical aspect of financial planning, where individuals defer present consumption to enhance their quality of life and meet future needs. The study aims to gain a comprehensive understanding of their financial behaviours, identify the factors that influence their financial decision-making, and compare the financial behaviours among different groups of academic employees. Methods: Employing a quantitative research approach, this study utilizes a structured questionnaire to gather data from academic employees. The questionnaire evaluates variables such as income level, education, job security, and financial goals to examine their impact on saving behaviours and financial readiness. Binary logistic regression analysis is employed to assess the influence of each factor on the dependent variable. Results: The findings indicate that a majority (83.3%) of academic employees have not previously saved, while a minority (16.7%) have managed to accumulate some savings. Statistical analyses, including chi-square tests, demonstrate significant associations between saving habits and variables such as gender, age, marital status, monthly expenses, and housing. The binary logistic regression analysis further highlights the significance of factors such as gender, age, education level, expenses, housing, additional income, and participation in savings groups in shaping employees' saving behaviours. Conclusion: This study contributes to the understanding of Ethiopian savings practices and personal finance by examining and comparing saving behaviours and financial preparedness across different academic institutions. It provides insights into the factors influencing financial decision-making and proposes strategies for enhancing financial literacy.
},
 year = {2024}
}

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TY  - JOUR
T1  - Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia

AU  - Birhan Ambachew Taye
AU  - Aychew Kassa Belete
AU  - Bantie Getnet Yirsaw
Y1  - 2024/05/17
PY  - 2024
N1  - https://doi.org/10.11648/j.ijber.20241302.12
DO  - 10.11648/j.ijber.20241302.12
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 36
EP  - 45
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20241302.12
AB  - Introduction: Saving behaviour is a critical aspect of financial planning, where individuals defer present consumption to enhance their quality of life and meet future needs. The study aims to gain a comprehensive understanding of their financial behaviours, identify the factors that influence their financial decision-making, and compare the financial behaviours among different groups of academic employees. Methods: Employing a quantitative research approach, this study utilizes a structured questionnaire to gather data from academic employees. The questionnaire evaluates variables such as income level, education, job security, and financial goals to examine their impact on saving behaviours and financial readiness. Binary logistic regression analysis is employed to assess the influence of each factor on the dependent variable. Results: The findings indicate that a majority (83.3%) of academic employees have not previously saved, while a minority (16.7%) have managed to accumulate some savings. Statistical analyses, including chi-square tests, demonstrate significant associations between saving habits and variables such as gender, age, marital status, monthly expenses, and housing. The binary logistic regression analysis further highlights the significance of factors such as gender, age, education level, expenses, housing, additional income, and participation in savings groups in shaping employees' saving behaviours. Conclusion: This study contributes to the understanding of Ethiopian savings practices and personal finance by examining and comparing saving behaviours and financial preparedness across different academic institutions. It provides insights into the factors influencing financial decision-making and proposes strategies for enhancing financial literacy.

VL  - 13
IS  - 2
ER  -

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Author Information

Birhan Ambachew Taye

Department of Statistics, Woldia University, Woldia, Ethiopia

Contact Email

http://orcid.org/0000-0002-2789-9963
Aychew Kassa Belete

Department of Sports Science, Woldia University, Woldia, Ethiopia

http://orcid.org/0009-0006-5195-5255
Bantie Getnet Yirsaw

Department of Epidemiology and Biostatistics, University of Gondar, Gondar, Ethiopia

http://orcid.org/0000-0002-0685-2218

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APA Style

Taye, B. A., Belete, A. K., Yirsaw, B. G. (2024). Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia. International Journal of Business and Economics Research, 13(2), 36-45. https://doi.org/10.11648/j.ijber.20241302.12

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ACS Style

Taye, B. A.; Belete, A. K.; Yirsaw, B. G. Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia. Int. J. Bus. Econ. Res. 2024, 13(2), 36-45. doi: 10.11648/j.ijber.20241302.12

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AMA Style

Taye BA, Belete AK, Yirsaw BG. Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia. Int J Bus Econ Res. 2024;13(2):36-45. doi: 10.11648/j.ijber.20241302.12

Copy | Download

@article{10.11648/j.ijber.20241302.12,
  author = {Birhan Ambachew Taye and Aychew Kassa Belete and Bantie Getnet Yirsaw},
  title = {Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia
},
  journal = {International Journal of Business and Economics Research},
  volume = {13},
  number = {2},
  pages = {36-45},
  doi = {10.11648/j.ijber.20241302.12},
  url = {https://doi.org/10.11648/j.ijber.20241302.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijber.20241302.12},
  abstract = {Introduction: Saving behaviour is a critical aspect of financial planning, where individuals defer present consumption to enhance their quality of life and meet future needs. The study aims to gain a comprehensive understanding of their financial behaviours, identify the factors that influence their financial decision-making, and compare the financial behaviours among different groups of academic employees. Methods: Employing a quantitative research approach, this study utilizes a structured questionnaire to gather data from academic employees. The questionnaire evaluates variables such as income level, education, job security, and financial goals to examine their impact on saving behaviours and financial readiness. Binary logistic regression analysis is employed to assess the influence of each factor on the dependent variable. Results: The findings indicate that a majority (83.3%) of academic employees have not previously saved, while a minority (16.7%) have managed to accumulate some savings. Statistical analyses, including chi-square tests, demonstrate significant associations between saving habits and variables such as gender, age, marital status, monthly expenses, and housing. The binary logistic regression analysis further highlights the significance of factors such as gender, age, education level, expenses, housing, additional income, and participation in savings groups in shaping employees' saving behaviours. Conclusion: This study contributes to the understanding of Ethiopian savings practices and personal finance by examining and comparing saving behaviours and financial preparedness across different academic institutions. It provides insights into the factors influencing financial decision-making and proposes strategies for enhancing financial literacy.
},
 year = {2024}
}

Copy | Download

TY  - JOUR
T1  - Examining the Impact of Socioeconomic Factors on Academic Staff Saving Behaviors and Financial Readiness in North Wollo Zone, Amhara, Ethiopia

AU  - Birhan Ambachew Taye
AU  - Aychew Kassa Belete
AU  - Bantie Getnet Yirsaw
Y1  - 2024/05/17
PY  - 2024
N1  - https://doi.org/10.11648/j.ijber.20241302.12
DO  - 10.11648/j.ijber.20241302.12
T2  - International Journal of Business and Economics Research
JF  - International Journal of Business and Economics Research
JO  - International Journal of Business and Economics Research
SP  - 36
EP  - 45
PB  - Science Publishing Group
SN  - 2328-756X
UR  - https://doi.org/10.11648/j.ijber.20241302.12
AB  - Introduction: Saving behaviour is a critical aspect of financial planning, where individuals defer present consumption to enhance their quality of life and meet future needs. The study aims to gain a comprehensive understanding of their financial behaviours, identify the factors that influence their financial decision-making, and compare the financial behaviours among different groups of academic employees. Methods: Employing a quantitative research approach, this study utilizes a structured questionnaire to gather data from academic employees. The questionnaire evaluates variables such as income level, education, job security, and financial goals to examine their impact on saving behaviours and financial readiness. Binary logistic regression analysis is employed to assess the influence of each factor on the dependent variable. Results: The findings indicate that a majority (83.3%) of academic employees have not previously saved, while a minority (16.7%) have managed to accumulate some savings. Statistical analyses, including chi-square tests, demonstrate significant associations between saving habits and variables such as gender, age, marital status, monthly expenses, and housing. The binary logistic regression analysis further highlights the significance of factors such as gender, age, education level, expenses, housing, additional income, and participation in savings groups in shaping employees' saving behaviours. Conclusion: This study contributes to the understanding of Ethiopian savings practices and personal finance by examining and comparing saving behaviours and financial preparedness across different academic institutions. It provides insights into the factors influencing financial decision-making and proposes strategies for enhancing financial literacy.

VL  - 13
IS  - 2
ER  -

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