**2. Theoretical Foundation: Technology Acceptance Model**

Since TAM was introduced in academia, the theory has become very popular, supported by data, and being adaptable to predict the use of new technology [17]. The model focuses on how the characteristics of new technology affect consumers' perceptions and how the customers ultimately use that technology [16,18]. The main point of TAM is that usefulness and the ease of use perceived by consumers are linked to consumers' attitudes toward using new technology. Furthermore, the consumers' attitudes toward using new technology are critical to the use of new technology [19,20]. Past studies have proposed several modifications that were considered essential to improve the predictive power of the technology acceptance model [21,22]. Several studies attempted to develop extended TAM to predict individual intention to adopt technology [16,23]. Most of the past studies have been done in the context of IT-related technologies. However, some studies have been conducted on the use of non-IT technologies such as apparel shopping [4,24], bottled water usage [25], acceptance of electric vehicles [23], intention to use YouBike system [26], outsourcing in organizational decision making [27], and acceptance of sustainability labels [28]. Therefore, TAM is the most appropriate model to predict customers' intention to use drone delivery. The extended technology acceptance model is presented in Figure 1.

**Figure 1.** An extended technology acceptance model.

#### *2.1. Perceived Ease of Use*

Perceived ease of use–also known as 'complexity' in innovation diffusion theory [29]—has been described as a significant predictor of technology adoption. For example, one study found that poor interface systems led to poor user performance, resulting in the rejection of many technologies [30]. In the context of electronic commerce, the success was depending upon the customer service features, products, site designs, and navigation and entertainment features [31]. Prior studies have shown that sites designs include updated information, simple checkout procedures, good layout, transparent navigational structures, effective search engines, and user-friendly interfaces were important aspects of online shopping [32–34]. In line with this, researchers found that perceived ease of use has a positive influence on teachers' attitudes towards mobile learning at higher institutions [35]. In the context of drone delivery services, perceived ease of use positively influenced attitudes towards drone delivery services [4].

#### *2.2. Perceived Usefulness*

Perceived usefulness refers to an individual's belief that using a specific system will accelerate his or her performance [36]. Prior researchers argued that perceived usefulness is a primary construct in TAM that predicts consumer attitude towards the virtual store, and a crucial factor that determines the behavioral intention [37]. Similarly, another study revealed the positive influence of perceived usefulness on attitude and behavioral intention to use online retail stores [32]. In the context of online retail stores, researchers argued that perceived usefulness significantly enhanced consumers' attitudes and intention to use online retailers [38]. In line with this, researchers found that the perceived usefulness of mobile apps has a positive influence toward the adoption of the app in the medical education system [39]. Extant literature depicts that perceived usefulness is a significant factor in technology adoption. For example, studies showed that technology usefulness has positive a influence on the adoption of the Google Applications platform [40] and customers' online purchases [41].

Prior studies depict the significance of technology-related constructs in the adoption of technological products. Hence, we assume that perceived ease of use and perceived usefulness are significant predictors of drone-based delivery services. Thus, we propose the following hypotheses:

**Hypothesis 1 (H1).** *Perceived ease of using drone food delivery service has a positive influence on attitude towards drone-based delivery services.*

**Hypothesis 2 (H2).** *Perceived ease of using drone food delivery services has a positive influence on the perceived usefulness of drone-based delivery services*.

**Hypothesis 3 (H3).** *Perceived usefulness of using drone food delivery services has a positive influence on attitude towards drone-based delivery services*.

#### *2.3. Subjective Norms*

Subjective norms are an important antecedent influencing people's behavior. It is the perceived pressure of a person towards behaving in a certain manner. Researchers found that important referents such as family and friends affect consumers' belief in the use of technology [42]. Researchers found that the influence of subjective norms on an individual is due to internalization, which refers to incorporating a referent's belief about the usefulness of a system [16]. Past studies revealed that subjective norms have a positive influence on users' perceived usefulness of technology [43,44]. For example, a study conducted on the acceptance of mobile commerce (m-commerce) revealed that subjective norms positively influenced the usefulness and attitude towards the acceptance of m-commerce [45]. Another study on US consumers' use of mobile technology for shopping fashion goods revealed that subjective norms positively influenced the perceived usefulness of mobile technology for shopping [46]. Similarly, researchers revealed that

subjective norms positively influenced the attitude towards mobile payment-based hotel reservations [47]. Extant literature revealed the significant effect of subjective norms on attitudes towards using technology via perceived usefulness [48,49]. Based on prior studies results related to the significant role of subjective norms in the adoption of innovative products, we propose the following hypotheses:

#### **Hypothesis 4 (H4).** *Subjective norms positively influence the usefulness of drone food delivery services.*

**Hypothesis 5 (H5).** *Subjective norms positively influence attitudes towards drone food delivery services*.

#### *2.4. Domain-Specific Innovativeness*

Domain-specific innovativeness (DSI) is related to individual inclination towards the adoption of a product class and refers to the tendency of a person to learn about the products within the particular domain [50]. The concept of domain-specific innovativeness is first presented by Robertson [51]. He suggested that consumers can innovate in the particular product class or related product classes. Consumers who have a propensity in the specific domain would react more towards the innovation in that category [52]. For example, people who have expertise in the domain of automobiles would better evaluate the performance of the high-power engine. Experts in the cosmetic industry would better evaluate the positive and negative aspects of beauty cream. This perception is due to the individual innovativeness in the domain of a specific product class [50]. Further, DSI is a better predictor of consumer behavior than global innovativeness [50,53]. In the context of electronic commerce, domain-specific innovativeness positively influenced consumers' acquisition and adoption of new products [54].

Prior research showed that consumers at any time can be innovative in a specific category, and at the same time, they can be a laggard in other product categories [55], and the measurement is only possible through a domain-specific environment [50]. The usefulness of domain-specific innovativeness can be seen in the number of consumer behavior researches [56–58]. Past studies have applied domain-specific innovativeness (DSI) in different domains such as rock music [59], wine consumption [60], online shopping [61], tourism management [62], and information technology usage [63]. Although domainspecific innovation was proved to be an efficient predictor of consumers' product adoption, researchers found a weak relationship between domain-specific innovativeness and new products adoption [64]. Researchers indicated that the current scale for adaptive behavior is biased as it does not cover other aspects of innovativeness [65]. That is, past researchers measured the adoptive dimension of domain-specific innovativeness such as purchase experience and time of adoption. Thus, to overcome this issue, the current study has conceptualized domain-specific innovativeness into two dimensions: product processing innovativeness and information processing innovativeness. Product processing innovativeness focuses on the specification of the product class [53], and information processing innovativeness relates to the knowledge and novelty-seeking aspect of domain-specific innovation [56]. Recently, researchers found that consumer novelty seeking has a positive impact on attitudes towards drone food delivery services [66].

The extant literature on innovativeness reveals the significance of both dimensions of domain-specific innovativeness, that is, product processing innovativeness and information processing innovativeness in the adoption of technology. Therefore, we assume that product processing innovativeness and information processing will positively influence the attitude towards the adoption of drone-based delivery services. Hence, we propose the following hypotheses:

**Hypothesis 6 (H6).** *Product processing innovativeness will positively influence customers' attitudes towards drone food delivery services.*

**Hypothesis 7 (H7).** *Information processing innovativeness will positively influence customers' attitudes towards drone food delivery services.*

#### *2.5. Impact of Attitude on Behavioral Intentions*

This study proposes that attitudes towards drone delivery service have a positive influence on three dimensions, including word of mouth, willingness to pay more, and intention to use [4,67,68]. First, the intention is the individual degree of willingness to perform or not a particular behavior in the near future [10,69]. Researchers found that the intention to use products or services is based on a positive evaluation of using the product or services [67,70,71]. Second, word of mouth represents consumers' informal communication directed to other people about the characteristics of the consumed products or services [68,72]. The impact of word of mouth is greater than an advertisement as it is considered more reliable and imparts greater confidence to purchase the products and services [73,74]. The third dimension of behavioral intention is a willingness to pay more. It is defined as the customers' willingness to pay high prices for the purchase of products and services [75]. Extant literature found that attitude has a positive impact on behavioral intentions [4,66,71].

Researchers argued that the TAM supports the effect of attitude on behavioral intentions [16,76]. Several studies have found a positive influence of attitude on behavioral intention. For example, attitude positively affects behavioral intentions for the purchase of green products [77], and the intention to use drone food delivery services [1]. Similarly, in the context of using drone food delivery during COVID-19, scholars found that attitude has a positive influence on behavioral intention [2]. Previous researchers merged TPB and TAM and predicted that attitude has a positive influence on customer behavioral intention to use drone food delivery services [4]. Similarly, other researchers found that attitude positively influences intention to use technology. For example, a study on using robotic technology in restaurants confirmed the positive influence of consumers' attitudes towards robotics on three dimensions of behavioral intentions—intention to use, word of mouth, and willingness to pay more [67]. In the context of using drone food delivery, researchers found that attitude has a positive influence on intention to use, word of mouth, and willingness to pay more [68]. Prior studies empirical and theoretical backgrounds provide evidence that attitude has a significant impact on the behavioral intention of customers. Hence we propose the following hypotheses:

**Hypothesis 8 (H8).** *Attitude towards drone food delivery service has a positive influence on intention to use drone food delivery service.*

**Hypothesis 9 (H9).** *Attitude towards drone food delivery service has a positive influence on word of mouth.*

**Hypothesis 10 (H10).** *Attitude towards drone food delivery service has a positive influence on willingness to pay more.*
