Liban Abdullahi Jama*
| Ibrahim Hassan Mohamud
© 2025 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
This study aims to investigate the impact of online service delivery on the purchasing intention of food buyers using the technology acceptance model (TAM) and the theory of planned behaviour (TPB) to provide a more robust understanding of online food purchase intention. A total of 416 questionnaires were obtained from consumers who had experience with online food delivery services in Mogadishu, Somalia. A partial least square (PLS) path modelling approach was used to analyze the collected data. The study result revealed that Attitude, Subjective Norms, Perceived Control, and Perceived Ease of Purchase substantially impact the purchasing intention of food buyers in Mogadishu, Somalia. However, the findings did not support the hypotheses about Perceived Usefulness and Personal Awareness. This study contributes to the existing literature by examining the TPB and TAM theories in relation to the intention to purchase food online. The study also encourages further research to gain deeper insights and explore additional variables that might shape purchasing intention in this context, including political stability and technology infrastructure.
technology acceptance model, theory of planned behavior, purchase intention
Online shopping is a rapidly growing industry that has gained popularity as a method of shopping [1, 2]. Internet technology has attracted more consumers to purchase online by providing customers with more accessible, convenient, and affordable alternatives to find a wider variety of food products [3, 4]. Moreover, online meal delivery services became a new business model where businesses focus on delivery services. The leading online services provided to consumers consist of online ordering platforms, delivery systems, and online payment methods. Unlike traditional practices, online food delivery service providers offer door-to-door services. The order will be collected by the rider of the food delivery service and delivered to the consumer [5].
Shopping for food using the internet is mainly determined by the internet penetration rate, which indicates the general extent of internet usage among a given population. According to the study [2], more than 4.3 billion internet users exist. Most users are in North America, which has 93 percent of the world's internet penetration, followed by Europe with 89.2 percent and Latin America with 80.5 percent. The Asian region has 67 percent of Internet users, and Australian users account for 70.1 percent.
Despite the fact that Africa is home to approximately 1.46 billion, it has a 43.2% Internet penetration rate, the lowest of any region in the world. For example, Europe and North America's penetration rates are 93.4% and 89.2%, respectively. However, Africa has the highest rate of technology acceptance globally, and the number of internet users is dramatically increasing. The African internet usage growth rate is 13,233% compared to Europe and North America 611% and 2,858% respectively [2]. As a result, online purchasing is fast growing in African countries; many consumers shop for food products without physically being present.
In Somalia, the time consumers spend engaging in various digital activities has increased significantly. The penetration rate currently is 9% [6]. The growth of Internet usage in Somalia was the second greatest in all of Africa, behind only the growth seen in the Democratic Republic of the Congo [7].
Compared to traditional restaurants, the reach of the Internet as a shopping medium has given consumers substantial advantages in terms of time savings, cheaper goods, and product choices. In order to better formulate marketing strategies, it is necessary to comprehend better online buyers and their purchasing intentions [8]. Furthermore, the advancement in internet technology has changed customers' purchase intentions and consumption behaviours, so it is necessary to identify factors affecting customers' online buying behaviour and intention [9]. For this reason, numerous studies have been conducted on factors affecting consumers' online purchase intentions [10-12]. However, only a few studies focused on this topic in the context of developing countries, especially in Somalia, where it is hardly investigated the variables associated with online purchase intentions [7]. This highlights the need for research that addresses developing nations such as Somalia since they have distinct socio-economic, cultural, and infrastructure needs. Therefore, this research contributes to the literature by filling the existing gap.
The objective of this study is to investigate the effect of online food delivery services on consumer purchase intention among food shoppers in Mogadishu, Somalia. in order to improve and promote a strategy for the businesses engaged in online food delivery services by applying the theory of planned behaviour (TBP) and technology acceptance model (TAM). These theories better analyze the underlying motivations and influences driving consumer's purchase intention by examining factors like attitude, subjective norms, perceived control, personal awareness, perceived ease of purchase and perceived usefulness. They also provide a structured approach to studying consumer technology adoption and buying behaviour about purchasing decisions.
2.1 Purchase intention
Purchase intention is a measure of how likely it is that a person will buy a particular product. It is based on how the customer's needs, attitude, and perception of the product or company interact [13-15]. Purchase intention can be considered a consumer's desire to buy a particular product [16]. In other words, a consumer's desire to buy is based on how much they plan to buy [14]. Knowing what people want to buy can help businesses analyze the market and change their goods or services to increase sales and make more money [17]. Online reviews affect how consumers see the value of a brand [18, 19] and, in turn, how likely they are to buy that brand. The quality and name of a website affect a consumer's trust and sense of risk, affecting a consumer's decision to buy [20]. In the context of developing countries, consumers' purchase intentions are influenced by a range of factors, including cultural, economic, and social considerations. For instance, in countries with emerging e-commerce markets, consumers may have different levels of trust in online platforms, which can significantly impact their purchase intentions. Additionally, the availability of online reviews and customer feedback may play a different role in shaping consumers' perceptions of product value and, consequently, their purchase intentions [19, 21].
Based on the previous study, buying intentions must be discussed when discussing online food delivery platforms. This is the end goal that the platform manager wants the consumer to reach. We also know that many things can affect a customer, and this study will help explain some of them.
2.2 TPB theory
The Theory of Planned Behavior (TPB) was created by Ajzen [22]. It is a cognitive model of how people act, and its primary objective is to predict and explain how people will act. It says a person's behaviour is caused by their "behavioural intention." On the other hand, a person's "attitude" (AT), "subjective norms" (SN), and "perceived behavioural control" (PBC) affect how they plan to act. However, other things will also affect people using online sites to get services. In previous studies applying TPB to online service delivery platforms, researchers have emphasized the role of attitude in influencing consumers' intentions to use these platforms [23, 24]. A positive attitude toward online service delivery can significantly impact purchase intentions.
Moreover, the influence of subjective norms, which represent social pressures, including recommendations from friends and family, has been explored [25]. Positive subjective norms can enhance consumers' intentions to use online services. Even if they did not use it, the factors are essential for platform managers to know to improve the goods and services on the platform.
2.2.1 Attitude
According to planned behaviour, a consumer's attitude is how they feel about a given action, whether positive or negative. It is a reliable indicator of whether or not a person will follow through on a planned behaviour [23]. Additionally, the traits associated with certain behaviours are well known to influence individuals' pre-existing attitudes towards those behaviours. A good attitude towards online food shopping substantially impacts consumers' propensity to make those purchases [24]. It focuses on how utilitarian motives influence attitudes toward online purchasing intentions [25]. Investigated consumers' food-buying attitudes favourably impact their desire to purchase functional foods [26]. Previous study pointed out that the attitude towards online purchases strongly affects the intention to utilize online purchases [27]. In summary, we aim to explore whether consumers' attitudes toward online service delivery platforms significantly affect purchase intention. Therefore, hypotheses H1 are proposed:
H1: Attitudes toward online service delivery positively influence buying intention.
2.2.2 Subjective norms
Perceived social pressure to engage in or refrain from a particular behaviour is an example of a subjective norm [28]. Individuals are subject to the impact of social norms and networks as they expedite information dissemination and alleviate ambiguity while making decisions. As outlined in the study [24], subjective normative influences, such as those from individuals deemed essential by users (such as family and friends), might impact users' acceptance intentions. A research revealed that consumers’ subjective norms significantly influence their intent to continue using the service [29]. Customers' attitudes, emotion control skills, and subjective standards affect their propensity to make additional purchases [30]. As reported, subjective norms and perceived behavioural control substantially affect online purchase intent [31]. Previous study investigated consumers' intent to maintain their online shopping habits [32]. Social standards mainly influence individuals' purchasing decisions. It has been hypothesized that customers are more inclined to engage in online purchasing when they have a favourable subjective norm, given that social normative impact may be of great relevance to a consumer while contemplating an online purchase [33]. Thus, the following hypothesis can be empirically tested:
H2: Subjective norms of online service delivery positively influence buying intention.
2.2.3 Perceived control
Perceived behavioural control [24] refers to an individual's estimation of his or her practicable level of behaviour, in this case, consumption, in light of the resources and opportunities available. Individuals' perceptions of their competence (ability), crucial needs (resources), and convenience (opportunity) will all be influenced by their prior experiences and expectations of the external environment. In conclusion, customers' perception of their ability to manage their consuming behaviour will influence their risk perception and motivation to use online meal delivery services. Consumers' prior online shopping experiences substantially impact their propensity to make future online food purchases [34]. Perceived agency has a sizeable impact on consumers' propensity to purchase over the internet [35]. Perceived behavioural control and subjective norms have significant effects on e-commerce [36]. Therefore, the following hypothesis intends to conduct an empirical investigation of this relationship:
H3: Perceived control of online service delivery has a positive influence on buying intention.
2.3 TAM theory
The technology acceptance model (TAM), which is based on the theory of reasoned action (TRA), was the most popular way to explain the adoption of new technology [37]. Internet usage attitudes, behavioural intentions, and actual usage are all factors that TAM investigates. The focus is on how perceived utility and perceived ease of use affect these factors. Following the advent of e-commerce, numerous researchers modified and enlarged TAM by including additional variables to better explain various technology adoptions and usages, thereby giving rise to new research models. By applying the concepts of perceived usefulness and ease of use to online shopping and adding the concepts of personal awareness of security and personal inventiveness, previous study created four key determinants that explain consumers' attitudes and examined the impact of these determinants on online purchase intention [38]. With these updates, TAM shifted its study emphasis from broad technological acceptance to the propensity to purchase online.
2.3.1 Personal awareness
The concept of personal awareness of security pertains to the subjective evaluations made by consumers on the potential risks associated with transmitting sensitive information during online buying activities [39]. Security emerges as a significant apprehension that hinders customers from online shopping [39]. For instance, the vulnerability of transactions can lead to the unauthorized disclosure of confidential information to external entities or its theft by malicious hackers [40, 41]. The aspect of security is of utmost importance when considering the attitudes and intentions of consumers about online purchases [39, 42]. These arguments give rise to the formulation of the following hypothesis for investigation:
H4: Personal awareness of security of online service delivery has a positive influence on buying intention.
2.3.2 Perceived ease of purchase
The concept of perceived ease of purchasing refers to a consumer's anticipation that an online purchase will involve less work than an in-person purchase [43, 44]. Several studies have established the impact of perceived simplicity on customers' adoption and usage behaviour of information technology [45]. Nevertheless, some recent research employing the Technology Acceptance Model (TAM) has discovered that the perception of ease of use does not play a decisive role in shaping individuals' attitudes or behavioural intentions. Previous study demonstrated that the perceived ease of use of e-commerce did not significantly impact the attitude towards e-commerce or the desire to use it among prospective online customers [46]. Other researchers in the field have reported comparable results. As exemplified by the study conducted, which focused on online banking [47], and mobile business [48]. It is possible that a significant number of individuals who engage in online activities possess a certain level of proficiency in navigating the Internet and may not perceive online purchases as a challenging endeavour. Building upon the preceding discourse, the primary objective of this investigation is to scrutinize the subsequent hypotheses:
H5: Perceived ease of purchasing of online service delivery has a positive influence on buying intention.
2.3.3 Perceived usefulness
Perceived usefulness pertains to the consumer's view that the Internet enables more efficient purchasing than in-person shopping [43, 44]. Researchers have demonstrated that perceived usefulness impacts the intention to engage in online shopping [49, 50]. Furthermore, it has been found that perceived usefulness is positively correlated with online users' behaviours and attitudes [51]. The absence of perceived advantages in online buying may discourage individuals from embracing it [52] and create reluctance to transition from traditional offline shopping to online platforms [53]. Consequently, this might impact individuals' attitudes and intentions to purchase online. In order to ascertain the impact of perceived usefulness on online service delivery, the present study provided the following hypothesis for empirical examination:
H6: Perceived usefulness of online service delivery has a positive influence on buying intention.
2.4 Theoretical modal
The study's theoretical framework shows the relationship between ATT, SN, PC, PA, PEP, PU, and Purchase Intention (PI). PI is operationalized as the exogenous construct predicting ATT, SN, PC, PA, PEP, and PU as endogenous constructs. The TAM and the TPB theories support the relationships between the constructs. The theoretical framework tests positive relationships between the constructs. The model is shown in Figure 1 below.
Figure 1. Theoretical modal
This study aims to examine how online food delivery services impact the purchasing intentions of food shoppers in Mogadishu, Somalia, to enhance and advance strategies for businesses involved in providing online food delivery services.
The study employed quantitative research methods. Data was collected from consumers who had experience purchasing food from online food delivery providers in Mogadishu-Somalia, and the instrument used in this study to collect data from the respondents was a 5-point Likert scale questionnaire adopted from the literature. The questionnaire was designed on Google tools (Google Docs) and distributed online via Email, WhatsApp, and Telegram. Since this study was investigating online food purchase intentions, the literature supports the idea that using online surveys produces the most efficient and acceptable data collection method [54, 55]. The questionnaire contains closed-ended questions for which respondents must select an option from a list, and it is divided into two sections: A (respondent profile) and B (variables of the study). The elements of the TPB construct, namely attitude, subjective norms, and perceived control, were adapted from [56].
In contrast, the items of the TAM construct, personal awareness, perceived ease of purchase and perceived usefulness were adopted from a survey instrument built based on prior research [57]. Furthermore, five academic specialists assessed the questions and their suitability to ensure the study's content validity. The questionnaire's scale was subjected to a pilot study to establish reliability.
Several researchers suggested that a sample size exceeding 200 units is considered significant and suitable for the study, which uses Structural Equation Modeling [58]. The sample size was 416 consumers, and respondents were selected using purposive sampling. It is a non-probability sampling method in which a sample is selected based on the population's characteristics and the study's purpose. Nonprobability sampling involves the researcher's subjective selection of respondents [57]. Judging, selective, and subjective sampling are other names for purposive sampling. The respondents' participation was voluntary; they have the right to cancel or stop filling out the questionnaire at any time, and further information provided by respondents will be used only for research purposes. Partial least square (PLS) with a path analysis model was used to test the model. Using the PLS algorithm, indicators were evaluated for convergent validity, average variance extracted (AVE), Cronbach's alpha, and composite reliability.
4.1 Descriptive
Table 1 shows that most respondents were male, accounting for 68.5%. Concerning their education level, tertiary/University accounted for approximately 79.3% of the sample. Regarding age, 73.6% of the surveyed respondents were less than 30 years old. Such age categories are pertinent to studying online food purchases because they represent the most frequent online food buyers. Concerning internet usage and items purchased online, the results showed that 41.8% and 42.8% of the respondents have been using the internet for less than five years and 5-10 years, respectively. The remaining 15.4% have more than ten years of experience in internet usage. Most of the respondents (69%) were students. More than half of the respondents earned less than USD 100. Most respondents, 59.7%, buy food online for personal use.
Table 1. Profile of respondents
|
Distribution |
Frequency |
Percentage % |
|
|
Gender |
Male |
131 |
31.5 |
|
Female |
285 |
68.5 |
|
|
Education |
Primary or below |
3 |
.7 |
|
Secondary |
13 |
3.1 |
|
|
Tertiary/University |
330 |
79.3 |
|
|
Postgraduate |
70 |
16.8 |
|
|
Age |
Below 18 |
27 |
6.5 |
|
19-21 |
188 |
45.2 |
|
|
22-24 |
118 |
28.4 |
|
|
25-30 |
60 |
14.4 |
|
|
31 or above |
23 |
5.5 |
|
|
Experience |
Less than 5 year |
174 |
41.8 |
|
5-10 years |
178 |
42.8 |
|
|
above 10 years |
64 |
15.4 |
|
|
Occupation |
Students |
287 |
69.0 |
|
Professionals/officers |
40 |
9.6 |
|
|
Self-employed |
59 |
14.2 |
|
|
Others |
30 |
7.2 |
|
|
Monthly income |
Less than $100 |
212 |
51.0 |
|
$101-$300 |
107 |
25.7 |
|
|
$301-$500 |
46 |
11.1 |
|
|
$501 - $1,000 |
29 |
7.0 |
|
|
$1,001 or above |
22 |
5.3 |
|
|
Reason of buying |
Personal use |
241 |
57.9 |
|
Recommended by friends or family |
98 |
23.6 |
|
|
Entertain guests |
17 |
4.1 |
|
|
Try new flavour |
36 |
8.7 |
|
|
Gift |
24 |
5.8 |
|
4.2 Measurement model
4.2.1 Convergent validity
Convergent validity pertains to an internal reliability measure that evaluates the extent to which a scale's items demonstrate a satisfactory correlation to identify a common underlying construct [55].
The determination of several statistical measurements such as Average Variance extraction (AVE), factor loading, Cronbach's Alpha, Composite Reliability (CR), Dijkstra-rho Henseler's (A), and Jöreskog's rho (c) is employed in this context. Based on the findings of this study, the item loading exhibited a value exceeding 0.7. According to the findings presented in Table 2, the average variance extracted (AVE) is above the threshold of 0.5. The Dijkstra-(A) Henseler's and Jöreskog's (c) rho values were above 0.7. The affirmation of the fulfilment of all criteria is substantiated by the fact that all three criteria met the necessary threshold values. Consequently, two items were eliminated simultaneously due to their low factor loading.
Table 2. Convergent validity
|
Construct |
Items |
Loadings |
AVE |
CR |
|
ATT |
ATT1 |
0.787 |
0.553 |
0.832 |
|
ATT2 |
0.75 |
|||
|
ATT3 |
0.729 |
|||
|
ATT4 |
0.706 |
|||
|
P Intention |
PI1 |
0.866 |
0.626 |
0.833 |
|
PI2 |
0.758 |
|||
|
PI3 |
0.744 |
|||
|
PC |
PC1 |
0.727 |
0.534 |
0.775 |
|
PC2 |
0.751 |
|||
|
PC3 |
0.715 |
|||
|
PEP |
PEP1 |
0.904 |
0.503 |
0.744 |
|
PEP2 |
0.621 |
|||
|
PEP3 |
0.555 |
|||
|
PU |
PU1 |
0.664 |
0.587 |
0.809 |
|
PU2 |
0.82 |
|||
|
PU3 |
0.804 |
|||
|
PA |
PA1 |
0.782 |
0.598 |
0.817 |
|
PA2 |
0.766 |
|||
|
PA3 |
0.772 |
|||
|
SN |
SN1 |
0.714 |
0.61 |
0.824 |
|
SN2 |
0.833 |
|||
|
|
SN3 |
0.792 |
|
|
4.2.2 Discriminant validity
Following the verification of convergent validity, the subsequent step involves the examination of discriminant validity. The present study employs the widely utilized Fornell-Larcker criterion, a prevalent tool within the research community. As indicated in Table 3, the constructs exhibit satisfactory discriminant validity [56] when the average variance extracted (AVE) square root exceeds the correlation between all reflective constructs.
Table 3. Fornell–Larcker criterion
|
|
ATT |
P Intention |
PC |
PEP |
PU |
PA |
SN |
|
ATT |
0.744 |
||||||
|
P Intention |
0.478 |
0.791 |
|||||
|
PC |
0.473 |
0.472 |
0.731 |
||||
|
PEP |
0.458 |
0.819 |
0.481 |
0.709 |
|||
|
PU |
0.355 |
0.374 |
0.594 |
0.453 |
0.766 |
||
|
PA |
0.312 |
0.378 |
0.515 |
0.46 |
0.447 |
0.774 |
|
|
SN |
0.389 |
0.359 |
0.431 |
0.66 |
0.423 |
0.387 |
0.781 |
4.3 Structural model
The present study employed Partial Least Squares (PLS) regression, a modified version of the multiple linear regression model. Previous study proposed that evaluating the structural model should involve utilizing various statistical measures, such as the standard beta, R-squared, and t-values [55]. They suggest employing a bootstrapping approach with a resample size of 5000 to obtain reliable estimates. Additionally, it emphasized the need to consider effect size (f2) and predictive relevance (Q2) when examining the structural model. The results of the examination of each matrix and parameter in this study are presented in Table 4 and Figure 2.
The study's findings revealed the following results: ATT favourably influenced purchasing intention, as evidenced by a significant beta coefficient of 0.136 (p<0.001). Therefore, the hypothesis H1 is supported. Moreover, it was determined that PC significantly influenced the purchase intention of online service delivery (β = 0.128, p < 0.002), hence supporting H3. In a similar vein, it can be observed that the Perceived Enjoyment and Perceived Ease of Use (PEP) construct has exerted a favourable impact on the inclination to engage in online purchasing (β=0.949, p < 0). Consequently, H5 is substantiated. Similarly, it was shown that SN significantly influenced the purchase intention of online service delivery (β = -0.355, p < 0), thus providing support for H2.
In contrast, the results presented that both perceived usefulness (PU) and perceived ease of use (PEOU) do not significantly influence individuals' intentions to engage in online purchasing, as evidenced by the non-significant beta coefficients of -0.018 (p > 0.589) for PU and -0.017 (p > 0.568) for PEOU. Consequently, the hypotheses H4 and H6 were excluded from consideration. As evidenced in Table 4, the R-squared coefficient stands at 0.760, indicating that the collective inclusion of all six variables accounts for approximately 76% of the variability observed in the purchase intention of online service delivery.
Figure 2. Structural model
Table 4. Structural model-hypothesis testing
|
Hs |
Path Relationship |
Sample Mean (M) |
Standard Deviation (STDEV) |
T-Value |
P-Values |
Decision |
|
1 |
ATT -> P Intention |
0.136 |
0.039 |
3.424 |
0.001 |
Supported |
|
2 |
SN -> P Intention |
-0.355 |
0.056 |
6.471 |
0 |
Supported |
|
3 |
PC -> P Intention |
0.128 |
0.041 |
3.136 |
0.002 |
Supported |
|
4 |
PEP -> P Intention |
0.949 |
0.052 |
18.459 |
0 |
Supported |
|
5 |
PU -> P Intention |
-0.018 |
0.038 |
0.54 |
0.589 |
Not Supported |
|
6 |
PA -> P Intention |
-0.017 |
0.035 |
0.571 |
0.568 |
Not Supported |
4.4 Discussion
The primary aim of this study is to investigate how access to online food delivery services influences consumers' propensity to make purchases in Mogadishu, Somalia, using the theory of planned behaviour (TBP) and the technology acceptance model (TAM). Regarding the first hypothesis, H1, attitude towards online shopping significantly and positively impacts purchase intentions for food products. Previous research has established the favourable influence of attitude on individuals' intentions to make online purchases [57-60]. As a result of this study exhibited a positive attitude toward online food shopping boosts consumer's intent to use the internet for purchasing. The more positive attitude a consumer has toward online food service delivery, the more likely they are to buy.
Marketing efforts should concentrate on understanding consumers' sentiments to effectively take advantage of the favourable consumer attitude towards buying food from the Internet and boost profitability and market share. This can be accomplished by enhancing consumers' trust and confidence by providing high-quality products and a secure and convenient online shopping experience.
Similarly, the study results showed that subjective norms substantially and positively affect customer purchase intentions [29-31]. Subjective normative pressures from people deemed to be significant to the consumer, if essential persons, such as family and friends, use a new technology, a person may be influenced by their social relations and develop a favourable perception toward that technology, which in turn would affect the intention to buy food online. This study emphasized the influence of social circles on online consumers' purchase decisions. Consequently, marketing strategies should aim to cultivate favourable subjective norms by offering platforms that enable customers to showcase their contentment with online food purchases, thereby shaping customers' perceptions.
Furthermore, the findings revealed that perceived control significantly and positively impacts buyer's intentions to purchase food online [24, 35, 61]; this study suggested that consumer's willingness to buy food online is enhanced when individuals have the ability and opportunity and believe that they are more self-competent with the use of the internet, so they can easily purchase food using the internet.
The study's outcomes also revealed a strong positive relationship between perceived ease of purchase (PEP) and the consumer's intention to purchase online food [62-67]. Perceived ease in purchasing (PEP) predicts purchase intentions; if the consumers believe that using the internet to purchase food is easy and will require minimum effort, then it would enhance their intent to buy food. However, if consumers perceive that ordering food online is hard, they will dislike purchasing it, even if it is helpful to them.
In contrast, the findings of this study show that perceived usefulness has no significant effect on purchase intentions among online food shoppers [68, 69]. The unsupported six hypothesis (H6) may be because respondents in the study found it difficult to use the online purchase due to the inadequate internet network. Similarly, the study results showed that personal awareness has no significant effect on the purchase intentions of online food buyers [64-67].
The primary objective of this study was to examine the impact of online service delivery on the purchasing intention of food buyers in Mogadishu, Somalia. In order to accomplish this goal, two well-known theories, specifically the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM), were utilized. The hypotheses were tested by employing partial least square structural equation modelling (PLS-SEM) in the investigation.
The study results indicate that several factors substantially influence the purchasing intention of food shoppers in Mogadishu, Somalia. Attitude, Subjective Norms, Perceived Control, and Perceived Ease of Purchase were significant determinants of consumers' intentions to engage in online food shopping. These findings underscore the importance of customer attitudes, the influence of social norms, perceived control over the online shopping process, and the convenience of online purchases in shaping the willingness of consumers to participate in online food shopping in this context.
However, it is noteworthy that the hypotheses related to Perceived Usefulness and Personal Awareness did not receive support in this setting. The non-significant findings suggest that the perceived utility of online service delivery and increasing consumer awareness regarding online buying may not substantially influence purchase intentions within the unique context of Mogadishu, Somalia.
The theoretical implications of this study highlight the continued relevance of TPB and TAM models in understanding consumer behaviour, even in developing country settings with distinct socio-economic and cultural factors. These models provide a robust framework for comprehending the determinants of consumer purchasing intention.
Businesses and policymakers must acknowledge the distinct socio-economic and cultural variables that impact consumer behaviour in Mogadishu, Somalia, to develop efficacious and customized approaches for enhancing online service provision and capitalizing on its potential within the food retail industry. There is a need for further investigation in this field to acquire a more profound understanding and examine supplementary factors that may influence the formation of purchasing intention within this particular setting. Future research endeavours could delve more profoundly into the ramifications of external factors, including but not limited to political stability and technology infrastructure, and their impact on the adoption of online food delivery services. In its entirety, this study provides a significant contribution to the realm of consumer behaviour and e-commerce within the distinct context of Mogadishu, Somalia.
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