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Abstract

People with Disabilities (PwD) is discussed in the literature as the largest minority in the world. This group generally prefers online shopping instead of store shopping due to the physical difficulties they experience. However, no online shopping model has been developed for this group. Therefore, the aim of this study is to reveal an online purchasing model for PwDs in line with the theory of planned behavior. In this regard, the effects of the variables perceived ease of use, perceived usefulness, peer communication, security concern, privacy concern and physical disabilities on consumers’ purchasing intention and subsequent purchasing behavior through subjective norms, attitude and behavioral control were investigated with pre- and post-disability data. In the study, data was collected from participants before (322) and after (546) disability. As a result of this study, it was revealed that online behavior of consumers before and after the disability differed. Especially peer communication made a significant difference in purchasing behavior after the disability. Consumers became more sensitive about security and privacy in their online shopping after the obstacle. In addition, consumers’ perceived usefulness had a significant effect on their attitudes after the disability. Therefore, as a result of the study, an online shopping model for PwD consumers was created.

Plain language summary

Pre and post disability behaviors of PwD consumers

This study reveals the change in PwD consumers’ behavior before and after disability. Thus, it enables measures to be taken against changes in consumers’ behavior.

Keywords

PwDs TPB physical obstacles privacy concern online purchase intention

Introduction

Physical disabilities are generally defined as diseases that affect the integrity of the body (Edwards et al., 2018). The World Health Organization (WHO, 2015) defines individuals who cannot perform their daily physical activities as sick. While mental disorders deal with diseases that affect the mind, physical disabilities deal with diseases that affect the body in a concrete way (Carty et al., 2021). These diseases include diseases (vision, hearing, touch) that cause sensory disabilities (cataract, glaucoma, retinal degeneration, otosclerosis, cholesteatoma, vertigo etc.), diseases that cause movement disabilities (loss or impairment of upper or lower extremities, poor dexterity, back/waist pain, and damage to one or more organs of the body esc.), cardiovascular diseases (heart attack, heart disease, hypertension esc), digestive diseases (gastritis, ulcer, reflux etc.), respiratory diseases (asthma or chronic obstructive pulmonary disease, allergies, etc.), chronic diseases (Multiple sclerosis, cerebral palsy, cancer, diabetes, psoriasis, migraine, Parkinson’s disease and epilepsy, scoliosis, rheumatism, COPD, asthma etc.; Anderson & Durstine, 2019; Carty et al., 2021; Edwards et al., 2018; Fuchs & Whelton, 2020). Consequently, it is known that many individuals are affected and have to live with these diseases. It has been stated that one in every four Americans has a physical disability that limits their daily movements, and a total of 42.5 million Americans have these disabilities (Houtenville et al., 2021). It is estimated that one in every six people in the world has a disability, corresponding to a total of 1.3 billion people (16% of the world’s population; WHO, 2021). While the number of disabled individuals between the ages of 15 to 64 in the European Union who have basic activity problems is 44vmillion, the number of disabled individuals who have limited working opportunities due to a lifelong health problem reaches 35 million. It is thought that there are approximately 2.5 million orthopedically disabled people in Türkey (12% of the population). Those who have difficulty seeing are 1.4%, those who have difficulty hearing are 1.1%, those who have difficulty speaking are 0.7%, those who have difficulty walking or climbing/descending stairs are 3.3%, those who have difficulty carrying/holding things are 4.1%, and those who have difficulty remembering are 2% (Ministry of Family, 2022). When other physical diseases are added to these, it can be seen that the figures can reach very high levels. Therefore, many people around the world try to cope with physical diseases, and a significant majority of them live with these diseases. For this reason, they are described as the ‘largest minority’ in the world (Mogaji et al., 2023).

There are many studies in the literature about PwD consumers. However, few of these are about online purchasing behavior. Among the studies on this subject, Elms and Tinson (2012) examined the online grocery shopping behaviors of 10 million disabled individuals in the UK. As a result of the study, it was revealed that disabled people are prone to online shopping behavior, but they think that they cannot benefit enough from the product discounts in the store when shopping online. Annett-Hitchcock and Xu (2015) investigated the use of online communities for clothing shopping by physically disabled consumers. It was proved that in order to help their peers, physically disabled individuals shared their product photos on social media and in groups and shared their product experiences along with their personal information. Maciaszczyk (2015) stated in his study that there are new preference options for physically disabled consumers that have emerged with globalization and digitalization. Accordingly, disabled individuals can be a part of online communities. Dias de Faria and Moreira Casotti (2019) investigated the behavior of consumers with down syndrome. As a result of the study, the obstacles faced by consumers with down syndrome were revealed. It becomes difficult for individuals with down syndrome to be consumers due to obstacles in education, working life, social behavior, digital world. Mogaji et al. (2023) examined PwD’s mobility decisions in their study. The study revealed that PwDs make mobility decisions based on accessibility, suitability, affordability and reliability, according to their capacities. Qayyum et al. (2023) investigated the impact of physical disabilities on the influencer market. The study revealed that hedonic and eudaimonic well-being become more important and have a greater impact on purchase intention when individuals encounter an inclusive advertisement featuring disabled people. Studies in the literature (Annett-Hitchcock & Xu, 2015; Driediger & Bhatiasevi, 2019; Maciaszczyk, 2015; Qayyum et al., 2023) have revealed that consumers with physical disabilities turn to online purchasing to overcome the difficulties they face while shopping. However, there are many variables that can affect their decisions when purchasing online. Therefore, this study will create an online purchasing model for PwD consumers to fill this gap. Thus, the factors that positively/negatively affect consumers with physical disabilities, who prefer to purchase online at a high rate, can be revealed in the light of the theory of planned behavior (TPB).

This study will make three important contributions to the literature and practitioners. First, the model created in this study will be the first online purchasing model for disabled people in the literature. Thus, the purchasing behaviors of disabled people can be better understood and purchasing practices can be developed for them. Secondly, the study will also investigate consumers’ perspectives on online consumption before they have a physical disability. Thus, the effects of physical disabilities on the model on the basis of variables can be examined. The impact of consumers’ physical disabilities on consumer behavior will also be more clearly understood. On a variable basis, practitioners will be able to adapt their websites/applications to consumers with disabilities. Thirdly, considering that the likelihood of individuals having physical ailments increases as they age, it is thought that the elderly can also benefit from the disabled online purchasing model. Therefore, companies will be able to update their applications not only for the disabled group but also for the potentially disabled group. In this way, digital strategies for consumers with physical disabilities, the ‘largest minority’, can be effectively implemented by companies.

Literature

Technology Acceptance Model and Theory of Planned Behavior

In many studies in the literature, the effect of the Technology Acceptance Model and Theory of Planned Behavior on consumers’ decision-making mechanism has been confirmed (Table 1). However, there is no research conducted with these two models on consumers with physical disabilities. The effects of the components in these two models on physically disabled people may also produce meaningful outcomes. It is thought that PwD’s may be more prone to the theory of planned behavior and the technology acceptance model because they are physically challenged. Therefore, the data obtained here will enable meaningful changes to be made in the lives of PwD consumers.

Table 1.

Literature with TAM and TPB.

Source	Model used	Variables^a
Driediger and Bhatiasevi (2019)	TAM	SN, VS, PR, EN, PU, PEU, BI, B
Cho and Lee (2020)	TAM	CNF, PEU, PU, SAT, CI
Lee et al. (2020)	TAM	PEU, PU, SN, PA, PL
Das et al. (2021)	TPB	ATT, SN, PBC, BI, B
Wu and Song (2021)	TAM & TPB	PEU, PU, SI, CI, BC, SN
Troise et al. (2021)	TAM & TPB	PU, PEU, SN, PBC, TR, ATT, BI
Tahat et al. (2021)	TAM	PU, LA
Wang et al. (2022)	TPB	ATT, SN, MN, BI, PBC, B
Rossetto et al. (2023)	TAM	PEU, PU, BI
Rejali et al. (2023)	TAM & TPB	PEU, PU, ATT, SN, PBC, BI
Liu and Park (2024)	TAM & TPB	PEU, PU, ATT, PBC, SN, BI
Bauer et al. (2024)	TPB	ATT, PBC, SN, BI, B

Variables: PEU = perceived ease of use; PU = perceived usefulness; CNF = confirmation; SAT = satisfaction; CI = continuance intention, SN = subjective norms; VS = visibility; PR = perceived risk, EN = enjoyment; PA = perceived anxiety; PL = perceived likability; SI = social isolation; TR = trust; ATT = attitude; PBC = perceived behavioral control; LA = learning acceptance; BI = behavioral intention; B = behavior.

When the research in this field is examined, many studies have demonstrated the impact of ease of use and perceived usefulness (TAM variables) on consumers’ attitudes, intentions, and behaviors. For example Driediger and Bhatiasevi (2019) found that perceived ease of use and perceived usefulness positively affected consumers’ online grocery purchasing intention. In addition, purchase intention also positively affects actual purchase. Also Cho and Lee (2020) found that perceived usefulness and perceived ease of use variables within the technology acceptance model positively affect the intention of disabled consumers to continue using smart devices through satisfaction. Lee et al. (2020) similarly found that perceived ease of use, perceived usefulness, and subjective norms positively influenced older adults’ intentions to adopt and use service robots. Das et al. (2021) revealed the effect of attitude, subjective norms and perceived behavioral control on behavioral intention in their study. They also stated that behavioral intention also shapes behavior. Wu and Song (2021) investigated the online shopping continuance intentions of older adults. The study found that the perceived usefulness of online shopping was positively associated with consumers’ attitudes and intentions to continue shopping online. It was also found that perceived behavioral control was positively associated with online shopping continuance intentions, but unline other studies subjective norms were not. Troise et al. (2021) investigated the impact of the theory of planned behavior and technology acceptance model on online food distribution companies. According to the research results, perceived ease of use and perceived benefits positively affect consumers’ attitudes. In addition, consumers’ attitudes positively affect behavioral intention. In addition, the influence of subjective norms and behavioral control on behavioral intention has been confirmed. However, unlike other studies, no effect of perceived ease of use on behavioral intention was found. Finally, the influence of subjective norms on attitude has also been proven. Tahat et al. (2021) researched the impact of using social media as an educational tool on the learning processes of individuals with disabilities during the COVID-19 pandemic. As a result of the study, it was seen that the quality, ease of use and texts in the video also contributed to improving the learning experiences of individuals with disabilities. Therefore, the impact of the technology acceptance model on individuals with disabilities was also revealed. Wang et al. (2022) revealed the effect of attitude and subjective norm on intention in their study. In addition, intention and perceived behavioral control affected the behavior of consumers. Rossetto et al. (2023) investigated the telerehabilitation process of disabled individuals. As a result of the study, it was proven that the participants had high scores in terms of behavioral intention, perceived usefulness and perceived ease of use. Therefore, significant effects were revealed in terms of technological acceptability. Rejali et al. (2023) examined the purchasing behavior of consumers by comparing three popular user acceptance models Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB) and Unified Theory of Acceptance and Use of Technology (UTAUT). As a result of the study, it was stated that all three models successfully explained behavioral intention. Liu and Park (2024) investigated tourists’ metaverse experience with these two theories (TAM & TPB). The study results show that perceived ease of use is positively related to perceived usefulness and attitude. In addition, the relationship between attitude, perceived behavioral control and subjective norm and behavioral intention has also been proven. Bauer et al. (2024) established a link with TPB in their research on traumas experienced by men. This study also revealed that the theory of planned behavior had a significant effect on patients.

Subjective norms, attitude and perceived behavioral control are three important components (La Barbera & Ajzen, 2021) that affect purchasing intention in line with the theory of planned behavior. Moreover, in theory, purchasing behavior is directly supported by purchase intention (Hasan & Suciarto, 2020). Subjective norms refer to the social pressure perceived by consumers (Ajzen, 1991). In other words, it involves being influenced by the environment/friends/family reference group. In the literature (Harrigan et al., 2021; Jain, 2020), it is seen that a high percentage of subjective norms affect purchase intention significantly and positively. However, there are also studies (Hasan & Suciarto, 2020; Wu & Song, 2021) that argue that subjective norms are not effective in online purchasing. Attitude refers to the attitude a person has toward an event, behavior or item (Ajzen, 1991). Individuals’ attitudes are also very effective on purchasing intention. Many studies (Ha et al., 2019; Trivedi & Yadav, 2020) have revealed the effect of attitude on online purchasing intention. Perceived behavioral control indicates whether an individual has the necessary competence to perform a behavior (Ajzen, 1991). In online shopping, perception behavioral control refers to whether consumers’ shopping abilities are formed along with their digital skills. Consumers are thought to have behavioral control if they have sufficient resources, information and opportunities for online shopping. There are many studies (Hasan & Suciarto, 2020; Peña-García et al., 2020) that perceived behavioral control affects purchase intention in online shopping. According to the literature review, although TAM and TPB are used together in different sectors, they have not been considered together in online shopping. In the light of this information, a model for the online grocery purchasing behavior of individuals with physical disabilities will be created in the research, together with the variables in the theory of planned behavior and the technology acceptance model.

Conceptual Model

For the factors underlying the online shopping behavior of individuals with physical disabilities, in addition to the perceived ease of use and perceived usefulness variables used in the technology acceptance model and subjective norms, attitude and behavioral control in the theory of planned behavior; peer communication, security concern, privacy concern and physical obstacles variables were evaluated. Perceived ease of use, refers to the degree to which a potential user of a particular system believes it is free from effort (Davis, 1989). Perceived ease of use in online shopping is often a component of user-friendly websites. In this way, consumers can easily find what they are looking for, complete their shopping, and make their payment comfortably. As e-grocery websites improve themselves in this sense, the rate of consumers making their purchases through these sites is increasing (Ha et al., 2019). Therefore, it is predicted that consumers with physical disabilities frequently use online shopping in order to avoid social pressure. In addition, its effect on subjective norm, attitude and behavioral control has been demonstrated in many studies (Ha, 2020; Sun et al., 2020; Trivedi & Yadav, 2020). For this reason, the first premise component is considered as perceived ease of use. The hypotheses are as follows:

H1: Perceived ease of use has effect on subjective norms of disabled consumers

H2: Perceived ease of use has effect on attitude of disabled consumers

H3: Perceived ease of use has effect on perceived behavioral control of disabled consumers

Perceived usefulness is the degree to which a person believes that using a particular system would enhance his or her performance (Davis, 1989). Within the technology acceptance model, perceived usefulness directly affects consumers’ attitudes in online shopping and indirectly affects their purchasing intentions (La Barbera & Ajzen, 2021). There are also studies (Ho et al., 2020; Sun et al., 2020) that have a significant impact on consumers’ subjective norms, attitude and behavioral control. Therefore, it is predicted to be an important component for consumers with physical disabilities, as for other customers. Hypotheses were prepared accordingly.

H4: Perceived usefulness has effect on subjective norms of disabled consumers

H5: Perceived usefulness has effect on attitude of disabled consumers

H6: Perceived usefulness has effect on perceived behavioral control of disabled consumers

Consumers learn consumption-related knowledge, skills, and attitudes from their parents, peers and TV advertising based on consumer socialization (Rita et al., 2019). Peer communication is an important element in online shopping, especially through social media (Annett-Hitchcock & Xu, 2015). Individuals can observe the behavior of their peers on social media and act accordingly. He can also communicate directly. It is also known that consumers with physical disabilities are more affected than their peers (Harrigan et al., 2021). Therefore, peer communication can have an impact on consumers’ subjective norms, attitudes and behavioral controls. In this regard, another primary component is considered as peer communication.

H7: Peer communication has effect on subjective norms of disabled consumers

H8: Peer communication has effect on attitude of disabled consumers

H9: Peer communication has effect on perceived behavioral control of disabled consumers

There are many factors that negatively affect consumers behaviors in online shopping. In this direction, security and privacy concerns are seen as the most important variables (Greenacre & Akbar, 2019; Rita et al., 2019). Security and privacy concerns appear as factors that increase the risks perceived by consumers. While security concerns generally reveal the insecurity in elements related to payment systems in online shopping, privacy concerns are associated with the theft of information by unknown persons (Greenacre & Akbar, 2019). In addition, many studies (Acikgoz et al., 2023; Anic et al., 2019) shows that this concerns effect consumers’ attitude. Therefore, these concerns of consumers need to be reduced. It is predicted that the level of skepticism of consumers with physical impairments also increases (Rita et al., 2019) and it is thought that security and privacy concerns in online shopping may also affect their behavior. In this regard, it is expected that security and privacy concerns will have a significant and negative impact on subjective norms, attitudes and behavioral control.

H10: Security concern has effect on subjective norms of disabled consumers

H11: Security concern has effect on attitude of disabled consumers

H12: Security concern has effect on perceived behavioral control of disabled consumers

H13: Privacy concern has effect on subjective norms of disabled consumers

H14: Privacy concern has effect on attitude of disabled consumers

H15: Privacy concern has effect on perceived behavioral control of disabled consumers

Physical obstacles are one of the main elements that can affect individuals’ purchasing behavior (Grewal & Levy, 2007; Pantano et al., 2022). Any disease/element that physically disrupts the normal form of the body can be evaluated in this variable. The daily behavior of an individual with a physical difficulty will also be affected by this difficulty. People with disabilities are known to shop online to abstain the ‘inconveniences’ of physical retail stores atmosphere (Rosenbaum et al., 2020). Among the studies conducted on this subject, Muangmee et al. (2021) revealed that confidence and physical difficulty variables have a mediating effect between the UTAUT2 model and behavioral intention. Ramadan (2021) show in his studies that a relationship is established between Alexa and consumers with special needs as it helps them regain their independence and freedom. Driediger and Bhatiasevi (2019) stated that online grocery shopping can help overcome obstacles for consumers. Therefore, it is seen that consumers’ behaviors change depending on the obstacles they face before and after the physical challenge. In this regard, the effect of physical obstacles on subjective norms, attitude and behavioral control will be investigated in the study

H16: Physical obstacles has effect on subjective norms of disabled consumers

H17: Physical obstacles has effect on attitude of disabled consumers

H18: Physical obstacles has effect on attitude of disabled consumers

Subjective norms, attitude and perceived behavioral control have been considered as variables affecting consumers’ intentions (Das et al., 2021; Rejali et al., 2023; Troise et al., 2021; Wang et al., 2022) and behaviors (Bauer et al., 2024; Das et al., 2021; Driediger & Bhatiasevi, 2019) in many areas within the scope of the theory of planned behavior and these effects have been proven in the past. Therefore, the final hypotheses were prepared for the effect of these three variables on consumers’ intentions and behaviors.

H19: Subjective norms has effect on disabled consumers purchase intentions

H20: Attitude has effect on disabled consumers purchase intentions

H21: Perceived behavioral control has effect on disabled consumers purchase intentions

H22: Purchase intention has effect on disabled consumers purchase behavior

Methodology

Research Design

In the study, the effect of the model was measured with survey based experimental design on customers with physical disabilities (Figure 1). Two studies were conducted in this direction. In the first study, the effect of the model was measured by considering the thoughts of consumers with disability before this physical disability occurred. In the second one, it was measured with the consumption thoughts after the physical disability occurred. Thus, the difference between the thoughts of the participants before and after the occurrence of a physical disability was analyzed with structural equation modeling on the same model. With structural equation modeling, differences on variable basis can be revealed. Therefore, a model in which perceived ease of use, perceived benefit and peer communication variables created in line with the literature will positively affect consumers’ online purchasing behaviors, while security concerns, privacy concerns and physical disabilities variables may affect consumers negatively was evaluated for both cases (pre and post disability). In addition, this model predicts that physical difficulties and peer communication variables may become more important in physically disabled consumers. Therefore, pre- and post-disability data will be obtained from the same participants to test whether there is a significant difference between them. Thus, the effect of having a physical illness on online shopping will be revealed.

Figure 1.

Online purchasing model for physically disabled consumers.

Data Collection and Sampling

Survey based experimental research was carried out in the study. Data were collected from the participants for two situations. In the first study (pre-disability), participants were asked to think about their lives before they had a physical difficulty. In the second study (post-disability), the participants were asked to answer by thinking about their current living conditions. The respondents were selected using a purposeful sampling method (Suri, 2011). Consumers with physical disabilities in the target group were included in the research. Information about this disabilities was given before filling out the survey form, and consumers without any physical disabilities were not included in the study. There is also a preliminary question regarding whether the participants shop online or not. Consumers who did not grocery shopping online were also not included in the study. Only online grocery consumers with physical disabilities were considered as participants.

In the research, face-to-face survey method was used to provide a faster response from consumers with physical difficulties. A total of 42 survey questions consisting of three sections were directed to the participants in our sample. In total, at least 386 answers are required according to the formula 8.42 + 50 = 386 (Tabachnick & Fidell, 2012). Face-to-face surveys were collected by students attending the research methods course. A total of 546 surveys were obtained from consumers with physical disabilities by paying a fee (50 cents) per survey to students. In order to investigate the behavior of consumers with physical difficulties before they had this physical disability, a survey form containing their thoughts before the physical disability was also implemented to the participants who agreed. Some participants did not fill out the first (pre disability) questionnaire because they did not shop online before disability, did not remember, etc. Consequently, data could be collected from 322 (out of 546 disabled consumers) consumers regarding the pre-physical disability. A total of 868 data were included in the analysis. The Ethics Committee form for the study was obtained from the Ethics Committee of the researchers’ university. Thus, a research was conducted in accordance with the Helsinki ethical rules.

Instrument Development

We developed a structured survey instrument based on items from the literature. Items from existing validated scales were adapted (Table 2). For the operationalization of the constructs, with 7-point Likert scale, the continuous distribution assumption, which provides the basic requirement of structural equation modeling, was fulfilled. For behavioral control, subjective norms and attitude, Troise et al. (2021), Driediger and Bhatiasevi (2019) for online shopping intention, online shopping behavior and physical obstacles; For physical obstacles, Sumarliah et al. (2022); For peer communication and perceived usefulness, Harrigan et al. (2021), Kim (2020) research was used for security concern, privacy concern and perceived ease of use. A back translation was performed to ensure the quality and accuracy of measures.

Table 2.

The Items.

Constructs	Code	Items
Perceived Ease of Use	PEU1	Purchasing in the online grocery market is efficient in many ways
	PEU2	Purchasing in the online grocery market is not a hassle
	PEU3	I can easily buy anything I want in the online grocery markets
Perceived Usefulness	PU1	Using online grocery stores’ websites can improve my shopping performance
	PU2	Using online grocery stores’ websites can increase my shopping productivity
	PU3	Using online grocery stores’ websites can increase my shopping effectiveness
Peer Communication	PC1	I talked with my peers about online grocery shopping
	PC2	I talked to my peers about the products that can be purchased in online grocery shopping
	PC3	I asked advice from my peers about online grocery shopping
	PC4	I obtained the product information from my peers about online grocery shopping
	PC5	My peers encourage me to buy in online grocery shopping
Security Concern	SC1	I am concerned that online grocery market companies will not implement appropriate security measures to protect their consumers.
	SC2	I am concerned that online grocery market companies will not ensure that my transactional information is protected from being altered or destroyed accidentally during an e-commerce transmission.
	SC3	I do not feel secure about the electronic payment system of online grocery market companies
	SC4	In general, I hesitate to make e-transactions because I am concerned about the security of my credit card information.
Privacy Concern	PRC1	I am concerned that online grocery market companies are collecting too much personal information from me.
	PRC2	I am concerned that online grocery market companies will use my personal information for other purposes without my authorization.
	PRC3	I am concerned that online grocery market companies will share my personal information with other entities without my authorization.
	PRC4	I am concerned that unauthorized persons (e.g., hackers) may have access to my personal information collected by online grocery market companies.
	PRC5	I am concerned about the privacy of my personal information during e-transactions.
Physical Obstacles	PO1	I have to staying at home because of my physical illness
	PO2	Due to my physical illness, I avoid going to shopping
	PO3	Due to my physical illness, I cannot walk to the market.
	PO4	Using online grocery shopping due to illness may overcome physical challenges
Subjective Norms	SN1	People who are important to me would think that I should use online grocery shopping
	SN2	People who influence me would think that I should use online grocery shopping
	SN3	People whose opinions are valued to me would prefer that I should use online grocery shopping
Attitude	ATT1	I think that using online grocery shopping would be a wise idea
	ATT2	I think that using online grocery shopping is a good idea
	ATT3	I think that using online grocery shopping is pleasant
	ATT4	In my opinion, it is desirable to use online grocery shopping
Perceived Behavioral Control	PBC1	I think that I would be able to use online grocery shopping website/apps well
	PBC2	I think that using online grocery shopping would be entirely within my control
	PBC3	I think that I have the resources, knowledge and ability to use online grocery shopping website/apps
Intention to Purchase	IP1	I intend to use online grocery shopping when the service becomes widely available.
	IP2	Whenever possible, I intend to use online grocery shopping to purchase groceries.
	IP3	I intend to use online grocery shopping when there is free home delivery.
Purchase Behavior	PB1	I shop grocery online many times in a month
	PB2	I spend a lot of time for online grocery shopping
	PB3	I frequently use online grocery shopping

Common Method Bias

In the study, two basic techniques used for common method bias control, Herman’s one-factor analysis in SPSS and one latent factor analysis in AMOS, were used. According to Herman’s one-factor analysis, shared variance below 50% may be a problem (Herman & Mack, 1975). The total variance shared in the study was determined as 26.58% for the data before the physical disability and 27.72% for the data after the physical disability. Therefore, there is no problem. Additionally, one latent factor analysis was performed in the AMOS program. For the data obtained before the physical disability, values of difference in degree of freedom 2 < 5 and Chi-square value is 0.01 < 3.84 were obtained (Afthanorhan et al., 2021). The standardized values of variables related to the common latent factor are less than 0.01. Since this is smaller than 0.2, common method bias was not observed. In the data collected after the physical disability, the difference in degree of freedom was calculated as 2 < 5 and Chi-square value is 0.79 < 3.84. In addition, the change in the standardized regression coefficient for variables related to the common latent factor is less than 0.018. Therefore, there is a difference of less than 0.2 (Al Halbusi, 2021) for all values. This reveals that common method bias was not observed in the study. In addition, the study tried to reduce common method bias by collecting pre and post disability data from participants at different times. In addition, in order to reduce the systematic error between variances, the explanations on the survey were read to the participants and explained clearly (MacKenzie & Podsakoff, 2012).

Preliminary Analysis

In the research, some preliminary analyzes were carried out to perform path analysis using structural equation modeling. Firstly, a pilot study was conducted. The pilot study included 50 participants. The data obtained were evaluated by exploratory factor analysis. It was observed that the participants in the pilot study were able to correctly distinguish the variables in the study. Afterward, the main data were collected and preliminary analyses were conducted. Missing data, normal distribution and reliability coefficients were examined in the main data. There is no missing data in the main data. Normal distribution coefficients are within ±1.5 (Tabachnick & Fidell, 2012). In addition, Cronbach alpha and composite reliability (Hair et al., 2017) values for all variables are above .7 (Table 3). Therefore, all resulting scales are unidimensional and sufficiently reliable. In addition, the content validity of the survey, which is the data collection tool, was checked. The results for convergent validity analysis demonstrate the significance of all the indicators related to their factors. The fact that the average variance extracted (AVE) is above 0.50 indicates that the scale provides convergent validity. (Hair et al., 2017). The results indicate that there is acceptable convergent validity. The discriminant validity could be assessed by cross-loadings, the Fornell-Larcker criterion, and the Heterotrait-Montrait ratio (HTMT). A HTMT value below 0.85 shows that discriminant validity has been established between two reflective constructs (Kline, 2023). In addition, it is seen that discriminant validity is achieved according to the Fornell Larcker criterion. It is important to obtain shared variance values between each pair of constructs that are lower than the corresponding AVEs for discriminant validity. It can be seen that this criterion is met in the study. Additionally, the cross loadings between dimensions show that each item loads higher in its own dimension than in others. In addition, there should be no multicollinearity problem in order to test the structural equation model. For this, the variance inflation factor (VIF) between the variables was examined and it was found that this value was below 5. As a result, reliability and validity were also established for pre- and post-physical disability data. In addition, manipulations checks for pre and post disability data were performed following Hauser et al. (2018). Since physical disabilities were considered as the main theme in the study for manipulation check, t-test was conducted for the key independent variable physical obstacles. Results demonstrated that a significant difference appeared between both groups (Mpre-disability = 3.49 vs. Mpost-disability = 5.94; t = −58,19, df = 866, p < .01), Thus, it was demonstrated that pre and post disability data were suitable for analysis.

Table 3.

Reliability and Convergent Validity.

Variables	PEU	PU	PC	SC	PRC	PO	SN	ATT	BC	IU	UB
C.A^a	0.91/0.84	0.90/0.91	0.94/0.93	0.93/0.92	0.94/0.93	0.95/0.91	0.90/0.89	0.91/0.88	0.89/0.87	0.89/0.89	0.90/0.85
C.R.^a	0.89/0.77	0.88/0.89	0.89/0.89	0.89/0.89	0.91/0.90	0.95/0.88	0.88/0.86	0.88/0.84	0.86/0.83	0.86/0.85	0.86/0.80
AVE^a	0.77/0.63	0.76/0.77	0.74/0.73	0.77/0.74	0.78/0.74	0.82/0.67	0.76/0.73	0.71/0.66	0.74/0.70	0.68/0.67	0.74/0.66
PEU^b	0.87/79	0.233	0.227	0.371	0.350	0.027	0.371	0.340	0.265	0.384	0.212
PU^b	0.298	0.87/0.87	0.067	0391	0.282	0.129	0.278	0.258	0.202	0.259	0.192
PC^b	0.210	0.164	0.86/0.85	0.166	0.304	0.081	0.128	0.198	0.282	0.185	0.192
SC^b	0.290	0.194	0.135	0.87/0.86	0.165	0.107	0.299	0.335	0.195	0.359	0.293
PRC^b	0.413	0.318	0.311	0.122	0.88/0.86	0.19	0.239	0.363	0.296	0.308	0.309
PO^b	0.278	0.289	0.372	0.307	0.178	0.90/0.81	0.070	0.031	0.077	0.018	0.054
SN^b	0.296	0.176	0.262	0.244	0.327	0.103	0.87/0.85	0.382	0.301	0.458	0.259
ATT^b	0.421	0.459	0.353	0.177	0.344	0.369	0.211	0.84/0.81	0.329	0.587	0.381
PBC^b	0.252	0.160	0.218	0.242	0.195	0.312	0.445	0.183	0.86/0.83	0.290	0.295
IP^b	0.274	0.224	0.289	0.195	0.332	0.318	0.498	0.453	0.323	0.82/0.81	0.382
PB^b	0.286	0.153	0.198	0.297	0.252	0.287	0.277	0.326	0.285	0.269	0.86/0.81

Note. Bold characters indicate the square root values of AVE.

The first values were calculated for before the physical disability (Study1), the second values were calculated for after the physical disability (Study2).

The section above bold characters is prepared for the values before the physical disability (Study1), the section below bold characters is prepared for the values after the physical disability (Study2).

Findings

Preliminary analysis shows that, the model could be tested with structural equation modeling. Consequently, confirmatory factor analysis was applied to the relevant model in the AMOS program. Confirmatory factor analysis revealed that the factors could be distinguished meaningfully by the participants. Then, path analysis was applied to the proposed model.

Confirmatory Factor Analysis (CFA)

In the study, data were collected from the participants before (from participants who accepted) and after the physical disability. Accordingly, confirmatory factor analysis was applied to the proposed model for both groups. The data obtained as a result of confirmatory factor analysis are presented in Table 4. The first data obtained can be seen in the before modification section of the table. When the data before the physical disability were evaluated, the fit index values recommended by Byrne (2001) could not be reached. Therefore, the data in the modification index was examined. In accordance with the recommendation suggested by Asuero et al. (2006) to remove items that have a high correlation coefficient with more than one variable and will not reduce the number of observed items below three, the first item of perceived ease of use, the second item of privacy concern and the fourth item of security concern were removed from the study. Afterward, sufficient coefficients for fit index values were reached. Although the data after the physical disability were close, the desired fit values were not reached before the modification. In line with the modification suggestions, the third item, peer communication, was removed from the study. In the subsequent analysis, the expected fit values were reached. Thus, path analysis could be performed for both data (before disability and after disability).

Table 4.

Confirmatory Factor Analysis (Before Disability and After Disability).

Indexes		X²/df	RMSEA	CFI	GFI	TLI	IFI
Before modification	Before disability	2.040	0.057	0.93	0.82	0.92	0.93
Before modification	After disability	1.912	0.041	0.96	0.89	0.95	0.96
After modification	Before disability	1.836	0.051	0.95	0.85	0.95	0.94
After modification	After disability	1.814	0.039	0.96	0.90	0.95	0.96

Path Analysis

After confirmatory factor analysis, latent variables were transformed into observed variables by taking averages (taking into account the removed items) and path analysis was performed. The fit index values obtained as a result of the path analysis are presented in Table 5. It has been demonstrated that fit index values (Byrne, 2001) are sufficient for both pre- and post-physical disability data. Only for after disability data, the X²/df value is above 3. Here too, since the RMSEA value was close to 0.080, it was accepted without making any changes to the model. The effects between variables can be seen in Table 6.

Table 5.

Path Analysis Fit Indexes.

Indexes	X²/df	RMSEA	CFI	GFI	AGFI	IFI
Before disability (S1)	3.2	0.083	0.96	0.97	0.89	0.96
After disability (S2)	4.5	0.081	0.96	0.98	0.91	0.96

Table 6.

Path Analysis Results.

Models	Before disability (Study1)			After disability (Study2)
Paths	Estimate	p-Value	Decision	Estimate	p-Value	Decision
PEU → SN	0.261	0.00	Supported	0.162	0.00	Supported
PEU → ATT	0.136	0.01	Supported	0.226	0.00	Supported
PEU → PBC	0.110	0.05	Supported	0.140	0.00	Supported
PU → SN	0.140	0.01	Supported	0.041	0.31	Not supported
PU → ATT	0.077	0.15	Not supported	0.269	0.00	Supported
PU → PBC	0.109	0.06	Not supported	0.022	0.58	Not supported
PC → SN	0.007	0.91	Not supported	0.157	0.00	Supported
PC → ATT	0.054	0.30	Not supported	0.145	0.00	Supported
PC → PBC	0.213	0.00	Supported	0.080	0.02	Supported
SC → SN	−0.144	0.01	Supported	−0.174	0.00	Supported
SC → ATT	−0.207	0.00	Supported	−0.024	0.48	Not supported
SC → PBC	−0.076	0.20	Not supported	−0.120	0.00	Supported
PRC → SN	−0.082	0.14	Not supported	−0.165	0.00	Supported
PRC → ATT	−0.220	0.00	Supported	−0.070	0.05	Supported
PRC → PBC	−0.155	0.00	Supported	−0.068	0.14	Not supported
PO → SN	0.047	0.40	Not supported	0.109	0.01	Supported
PO → ATT	−0.072	0.16	Not supported	0.135	0.00	Supported
PO → PBC	−0.125	0.02	Supported	0.195	0.00	Supported
SN → IP	0.223	0.00	Supported	0.332	0.00	Supported
ATT → IP	0.459	0.00	Supported	0.375	0.00	Supported
PBC → IP	0.089	0.02	Supported	0.128	0.00	Supported
IP → PB	0.708	0.00	Supported	0.669	0.00	Supported

PEU = perceived ease of use; PU = perceived usefullness; PC = peer communication; SC = security concern; PRC = privacy concern; PO = physical obstacles; SN = subjective norms; ATT = attitude; PBC = behavioral control; IP = intention to purchase; PB = purchase behavior.

When pre-physical disability data were evaluated, it was found that consumers’ perceived ease of use had an impact on their subjective norms (β = .26), attitudes (β = .14) and behavioral controls (β = .11). Although perceived usefulness had an impact on consumers’ subjective norms (β = .14), it did not affect their behavioral controls and attitudes (p > .05). Although peer communication did not have an effect on consumers’ subjective norms and attitudes (p > .05), it was found to have an effect on their behavioral controls (β = .21). Although security concern affected consumers’ subjective norms (β = −.14) and attitudes (β = −.21), it had no significant effect on their behavioral controls (p > .05). Although privacy concern affected consumers’ attitudes (β = −.22) and behavioral controls (β = −.15), it did not have a significant effect on their subjective norms (p > .05). Although physical obstacles did not affect consumers’ subjective norms and attitudes (p > .05), a significant effect was found on behavioral controls (β = −.12). In addition, subjective norm (β = .22), attitude (β = .46) and behavioral control (β = .09) variables were found to have a significant effect on intention to purchase. Finally, consumers’ intention to purchase behavior (β = .71) affects purchasing behavior positively and significantly.

In the post-physical disability data, perceived ease of use had a significant effect on consumers’ subjective norms (β = .16), attitudes (β = .22) and behavioral controls (β = .14). Perceived usefulness affects consumers’ attitudes (β = .27), but has no effect on their subjective norms and behavioral controls (p > .05). It has been demonstrated that peer communication is effective on consumers’ subjective norms (β = .16), attitudes (β = .14) and behavioral controls (β = .08). Although security concern affected consumers’ subjective norms (β = −.17) and behavioral controls (β = −.12), it had no effect on their attitudes (p > .05). Although privacy concern has a significant effect on consumers’ subjective norms (β = −.16) and attitudes (β = −.07), it does not have a significant effect on behavioral controls (p > .05). As expected, physical obstacles were found to have a significant impact on consumers’ subjective norms (β = .11), attitudes (β = .13) and behavioral controls (β = .19) after the disability. Additionally, subjective norms (β = .33), attitude (β = .37) and behavioral control (β = .13) showed a significant effect on consumers’ purchasing intention. In addition, consumers’ online purchasing intention (β = .67) affects purchasing behavior positively and significantly.

In the findings related to Pre and Post Disability, while 14 paths are supported in the first data, 18 paths are supported in the second data. Therefore, the model produced more significant results in pre-disability data. In addition, the support status of 10 paths has changed. The noteworthy paths are; the effect of perceived usefulness on subjective norms, security concern on attitude, privacy concern on attitude in the first data, while no effect was found in the second data. The paths that were not supported in the first data but supported in the second data are as follows; the effect of perceived usefulness on attitude, peer communication on subjective norms and attitude, security concern on behavioral control, privacy concern on subjective norms, physical obstacles on subjective norms and attitude became significant. Therefore, peer communication, security concern, privacy concern and physical obstacles variables produced more significant results for the post-disability model.

Discussion

Theorical Implications

When the online purchasing model for people with disabilities is evaluated compared to the pre-disease situation, it has been observed that the disclosure rate is high. Therefore, it can be stated in the literature that it is a successful model and can be applied to consumers who have physical disabilities. As a result of the study, three important contributions were made to the literature. First, a comprehensive online purchasing model has been put forward with the TAM and TPB theory for consumers experiencing physical disabilities. Perceived ease of use, which is considered in line with the technology acceptance model, was determined as a variable that directly and significantly affects the participants before and after the obstacle. Therefore, it supports the studies in the literature on online purchasing (Ha, 2020; Sun et al., 2020; Trivedi & Yadav, 2020). However perceived usefulness, another variable considered in line with the technology acceptance model, caused differences in pre- and post-disable decisions. While in many studies (Ho et al., 2020; Sun et al., 2020) perceived usefulness affected consumers’ attitudes, here it did not affect consumers’ attitudes before the disability, but it affected consumers’ behavior after the disability. In other words, consumers with physical disabilities have become more important to the perceived ease of online shopping after the disabilities. In the model developed for PwDs, the ‘largest minority in the world’, the theory of planned behavior effect was realized similarly in both pre-disability and post-disability data. Subjective norms, behavioral control and attitude significantly affect intention as expected. This is in line with other results in the literature (Ha et al., 2019; La Barbera & Ajzen, 2021; Troise et al., 2021).

Secondly, by testing the model before and after the disability, it was seen that the model worked better after the disability. Thus, it was revealed that consumers think differently after the disability. Since many studies only consider post-disability data, examining pre- and post-disability data together will also make a significant contribution to the literature. Thirdly, many relationships (Ha et al., 2019; Jain, 2020; La Barbera & Ajzen, 2021; Peña-García et al., 2020) in the literature were also confirmed in this study. However, different relationships that can make significant contributions to the literature have also been revealed. While peer communication did not have a significant effect before the disability, it became significant after the disability. In other words, consumers gave more importance to peer communication after having a physical disability. In addition, the effect of physical obstacles on consumers’ online purchasing behavior has been revealed. Security and privacy concerns negatively affect consumers, similar to past studies (Acikgoz et al., 2023; Anic et al., 2019). However, this study revealed that consumers were more affected by these factors after the disability.

Managerial Implications

In line with the outputs obtained in the study, digital marketing strategies can be developed for individuals with disabilities. It has been observed that disabled individuals are more prone to online purchasing behavior after disability. Therefore, considering them as a separate group during the segmentation stage by marketers will increase the efficiency level of the promotion strategies to be developed. For example, by identifying consumers who have physical difficulties in online grocery purchasing, it will be possible to turn these consumers into loyal customers through online communities. Another important finding in the study is that consumers attach more importance to peer communication after the disability. Therefore, the companies can remind itself of itself when these consumers are with their peers. For example, ‘let’s overcome physical difficulties together’ days can be organized and sponsored. Additionally, the study found that the basis of online purchasing is perceived ease of use. For this purpose, companies need to create user-friendly websites. If consumers with physical difficulties are taken into consideration when designing the website, these consumers can be made to feel valuable. This is a very important element in turning consumers into loyal customers. For example, a company that pays attention to color harmony by taking into account consumers with color blindness can win those customers for the long term. Moreover, it should be ensured that the personnel who will work in the customer service of disabled consumers are selected and employed in accordance with the disabilities. For example, in call centers, companies can help disabled consumers solve their problems with video calls by employing employees who know sign language for consumers with vocal problems.

Another important finding in the study is that consumers become more sensitive to security and privacy concerns after the disability. For this reason, online grocery companies need to strengthen their infrastructure in order to address consumers’ concerns. It is important to convey the studies carried out on this subject to the consumer. For example, consumers can be reassured with a campaign that says ‘We apply GDPR principles in our organization to protect your data and serve you better’. In addition, physical obstacles directly affect consumers’ online shopping behavior. Consumers with physical disabilities prefer online shopping rather than store shopping. For this purpose, the sensitivity of the group should be taken into consideration in the digital strategies to be created by the companies. Consumers without physical difficulties consider store shopping as a means of happiness, but consumers with physical difficulties are deprived of this happiness. For this reason, consumers with physical disabilities can increase their shopping happiness through applications that can entertain them while shopping on the online website. In this way, companies can convey that they care about every customer through the ‘largest minority’. Therefore, the study clearly reveals that the perspectives of disabled consumers on online shopping before and after the disability have changed (Figures 2 and 3). Therefore, the online shopping needs of disabled consumers should be urgently addressed by companies and an action plan should be prepared accordingly.

Figure 2.

Pre-disability online purchasing model.

Figure 3.

Post-disability online purchasing model.

Limitations and Further Research

As in many studies, this study has some limitations in terms of time and cost. The first limitation of this study is the use of purposive convenience sampling for consumers with physical disabilities. Preferable diverse sampling strategies could enhance the broader applicability of the results. Second, the potential for longitudinal change over time as individuals adapt to their physical disabilities has not been addressed, which could provide valuable insights into the dynamic nature of purchasing behavior. The third limitation is that the sample included participants from one country. The applicability of the purchasing model for PwDs can be increased with data obtained from other countries and results from other cultures.

Future studies could further enrich the understanding of the online purchasing behavior of people with disabilities, such as social support, self-efficacy or accessibility features that could be added for people with disabilities. Furthermore, in future studies, classifying individuals’ physical disabilities into specific groups may reveal important nuances and differences in the online purchasing behavior of individuals with various types of physical disabilities (e.g., mobility, sensory, cognitive). In addition, exploring the role of potential moderating variables such as age, gender, or socioeconomic status, which may provide additional insights into heterogeneity among people with disabilities, would also enrich the literature on this topic. Lastly, it is thought that significant differences may emerge between groups with low and high digital literacy among PwD consumers. Further research on this subject will increase the knowledge in the literature.

Conclusion

The aim of the study is to reveal the online behavior of consumers with physical disabilities and to create a purchasing model accordingly. The model created in this direction was analyzed and it was revealed that the model works better after physical disability (Figures 2 and 3). It has been observed that the effect of variables such as peer communication and physical obstacles on purchasing increases more after physical disability. Peer communication, which they did not consider important before the physical disability, became important for the consumers after the physical disability. As expected, while physical obstacles were an element that consumers did not care about before the physical disability, they became a significant element after the disability for consumers. In addition, study revealed that perceived ease of use is very important for consumers both before and after physical disability in online shopping. While perceived usefulness did not affect consumers’ attitudes before the disability, it began to affect their attitudes after the disability. Consumers have become more sensitive to security concerns and privacy concerns after physical disability. In addition, it has been observed that subjective norms, attitude and behavioral control have an impact on consumers’ purchasing intention in both pre- and post-physical disability situations. Additionally, in both models, purchase intention positively affects purchasing behavior.

Footnotes

Author Note

As corresponding author,I confirm that the manuscript has been read and approved for submission by all the named authors.

ORCID iD

Sefa Emre Yilmazel

Funding

The author received no financial support for the research,authorship,and/or publication of this article.

Declaration of Conflicting Interests

The author declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Data Availability Statement

10.6084/m9.figshare.24415414

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Online Purchasing Model for PwD (People with Disabilities) Consumers: Pre and Post Disability Behaviors

Abstract

Plain language summary

Keywords

Introduction

Literature

Technology Acceptance Model and Theory of Planned Behavior

Conceptual Model

Methodology

Research Design

Data Collection and Sampling

Instrument Development

Common Method Bias

Preliminary Analysis

Findings

Confirmatory Factor Analysis (CFA)

Path Analysis

Discussion

Theorical Implications

Managerial Implications

Limitations and Further Research

Conclusion

Footnotes

Author Note

ORCID iD

Funding

Declaration of Conflicting Interests

Data Availability Statement

References