Does Online Ratings Matter? An Integrated Framework to Explain Gratifications Needed for Continuance Shopping Intention in Pakistan

Abstract

Due to the phenomenal growth of e-commerce, online shopping has recently become a worldwide trend. This fosters many online shopping platforms to enter into Asian emerging markets, which evolves a need to understand online decision-making processes in this particular context. Addressing this gap, our study initialized an integrated framework based on Uses and Gratification theory and the Cognitive–Affect–Behavior paradigm to examine the impact of gratification elements on customer satisfaction and convenience enforcing continuance shopping intention. Moreover, we also conceptualize the moderating role of online ratings in our study. In total, 317 valid questionnaires from Pakistani online shoppers were incorporated to statistically test our model using the Structural Equation Modeling (SEM) approach in Amos. Besides, the results confirm the positive impact of layout and functionality on customer satisfaction and convenience, while the impact of PEEIM has been found insignificant. Furthermore, customer satisfaction and convenience are found to be the imperative predictors of continuance shopping intention. Our findings exhibit that a high level of online rating strengthens the direct effect of satisfaction and convenience on continuance intention. Theoretical and practical implications for future scholars and e-commerce shopping platforms are discussed.

1. Introduction

With the drastic development of the e-commerce industry, online shopping has become the most preferred choice among individuals and is considered an essential mode of online transactions. As a feasible alternative to traditional shopping, online shopping gain tremendous popularity among consumers. Some viable reasons behind this dynamic growth are the myriad advantages of online shopping for both customers and online platforms [1,2]. Various principle promoters behind customer’s concerns to adopt online shopping includes getting information about product or service [3], convenience [4], time and cost saving [3], and online transaction facility [5]. Similarly, numerous businesses have expanded their operations through this worldwide effective channel of distribution and considered this mode of shopping as a sizeable opportunity to grow [6,7]. Consequently, online shopping has become a notable scenario for both practitioners and researchers [8,9,10].

Specifically, customers require some intact drivers to shop online, which are primarily satisfaction and convenience. Moreover, these drivers have an imperative effect on continuance intention, which is considered to be an essential source in increasing habitual online shopping. Consequently, the sustainability of the e-commerce platform crucially depends on customer’s continuance intention [10].

The increased popularity of online shopping has made e-commerce platforms a significant online transactional spot that attracts both buyers and sellers [11]. Moreover, this injects several suspicious concerns in consumers’ minds regarding online purchases. Some identifiable concerns in consumers that cause hindrance in online purchasing includes product or service concerns, privacy concerns, and security concerns [12]. To alleviate these concerns, perceived effectiveness of institutional mechanism (PEEIM) plays a vital role, which causes trust among consumers and increase online transactions [13]. PEEIM is considered a modern concern in making online transactions without any hindrances and can subsequently be an antecedent of customer satisfaction and convenience.

A conducive element in online shopping is the layout and functionality of the e-commerce platform, i.e., website or app. It plays a vital role in attracting customers and producing a favorable environment for boosting satisfaction and convenience level of consumers. Discrepancies while using a shopping platform, i.e., website or apps, creates dissatisfaction, which even tends to make online shoppers drop out from their current shopping carts, leaving transactions incomplete [14]. A friendly layout and favorable functionality of the e-commerce platform can motivate consumers and elucidate their decisions to make a purchase [15].

According to UNCTAD B2C E-commerce index 2020 [16], enormous growth in index scores has been noted from some developing countries and the top ten developing economies recorded in the index belong to Asian nations. The report shows the latest trends of e-commerce in Asian markets, due to which online shopping is experiencing gigantic growth in many Asian and developing countries. Numerous new and existing e-commerce shopping platforms have emphasized their attention towards dynamic consumer behavior, particularly in Asian emerging markets. Moreover, it has been observed that various frameworks or models particularly focused on western countries [17]. Palvia [18] encountered that the models or frameworks executed in the US or western countries are particularly valid in developed economies. So, there is a viable scope to test such developed theories and models in Asian countries consisting of diverse culture and emerging e-commerce markets. Although immense growth of online shopping has been observed in Asian emerging markets, it still lacks the empirical evidences as compared to the studies conducted in the western context [19]. In light of the above discussion, we intend to choose an emerging Asian country with diverse cultural characteristics to extend the previous literature in our study.

Prior studies indulged plenty of different theories like expectation confirmation theory [20], IS success model [21], dual factor model [22,23], uses and gratification theory [24,25,26], S-O-R Model [25], and social identity theory [27,28] to determine consumer behavioral and usage characteristics. Among all these theories, many recent scholars have incorporated uses and gratification theory (UGT) in their studies to investigate the significant impact of gratifications on consumer’s adoption and continuance intention to use online shopping [24,25]. However, we aim to explore online informative gratifications under the shadow of UGT that can derive customer satisfaction and convenience and investigate their causal link with continuance intention in the presence of online ratings as potential moderator.

Our study aims to bridge the highlighted gaps mentioned above by providing a theoretical model integrating UGT with the CAB paradigm. We chose Pakistan as an emerging Asian country because of its diverse cultural characteristic, and we targeted its e-commerce market that is more specifically involved in the online shopping context. According to a report published by GSMA in the year 2020 [29], Pakistan is progressing towards a fully-fledged digital economy. With a vast population that is expected to pass 220 million in 2020 and more than 100 million young population under the age of 25, Pakistan is a well-positioned country to empower the global economy in the coming decades. The number of Internet users in Pakistan gradually increased by 11 million (+21%) between 2020 and 2021, and internet penetration in Pakistan stood at 27.5% in January 2021 [30]. Pakistan contains the 46th largest e-commerce market with a revenue of $4 billion in the year 2020 [31]. Consequently, with an immense increase of 84% in the e-commerce industry, Pakistan contributed a 26% worldwide growth rate in the year 2020 and still the revenues through e-commerce penetration are expected to increase further. UNCTAD B2C E-Commerce Index measures different countries’ economies’ preparedness to support online shopping, which ranked Pakistan 116 out of 152 in 2020 index [16]. Pakistan’s e-commerce market recently experienced a conducive growth of over 35 percent for the first quarter of fiscal year 2021, which turns out to be Rs96 billion as compared to Rs71billion recorded over last year as per a report shared in the fourth meeting of National e-Commerce Council (NeCC), chaired by commerce advisor in Pakistan [32]. This clarifies the potential growth of e-commerce in Pakistan and makes it an emerging market thriving toward e-commerce success. Our study accentuated that by deploying the cognitive path based on informative gratification, i.e., layout and functionality, and PEEIM, which generates affective responses as customer satisfaction and convenience and in turn develops behavioral responses as continuance shopping intention. Following UGT, we also integrated online ratings as a moderator between customer satisfaction, convenience, and continuance intention to initialize its equivocal role. Thus, our study symbolizes the role of informative gratification integrated with the CAB model to develop continuance intention in Pakistani online consumers.

2. Theoretical Background

2.1. Uses and Gratification Theory (UGT)

UGT has been widely accepted and used to build a comprehensive framework for understanding the motivations and reasons behind the use of a particular media and its types [33]. Katz et al. [34] explains that people are very aware of their needs and they particularly seek motivations from certain media or technology to gratify those needs. Consequently, this conceptualizes a new concept after diminishing a traditional thought that “what media do to people” to “what people do with media”.

Prior studies incorporated UGT in studying different perspectives varying from traditional media (radio, newspaper, television) to Internet use and recent social media types (photo tagging, photo sharing, microblogging) [24]. A large body of literature invoked UGT in determining the motivations and reasons for Internet use [35,36,37,38], which significantly affects consumer continuance intention [39,40], buying intention [41], and actual buying behavior [33].

The enormous use of the Internet has pushed consumers to adopt and use emerging media frequently, which has accelerated a trend of online shopping in many societies. Consequently, most of the recent research used UGT to identify the specific motivational factors that are used in the customer’s adoption of new technology while affecting their buying behavior [39,42]. Hence, UGT is considered a preferable choice when it comes to studying behavioral intentions and decision-making processes using the Internet.

One of the kinds of people using the Internet also lie under the category of online shoppers. With this view, several researchers employed UGT to study the Internet as a shopping platform [39,43], and to find out the possible gratification elements determining continuance intention towards online shopping [44]. The UGT also suggests that consumers consciously choose media such as social networking sites or apps based on gratifications related to security assurance [45] and web interface [46], which are the core components behind their motivation and behavioral intentions.

It has also been supported by Ducoffe [47] that informational content plays an important role as a satisfaction factor for consumers according to the extended UGT. Thus, continuing using online transactional platforms need substantial informative motivations and the use of UGT is most suitable to conceptualize those needed gratifications [44]. Further, it can help us to better understand e-consumers [48]. It has been found that UGT plays an important role in understanding consumers’ experiences linked with online websites that can affect their future behavioral intentions and motivations [10,43,49,50]. Following UGT, the extant literature has put light on different constructs that affect the continuance usage intention of consumers toward transactional platforms, but the most significant and vigorous dimension amongst all is informative gratifications [45].

2.2. Cognition-Affect-Behavior Model (CAB)

We integrated the Holbrook CAB model in our study, which consists of three sequential components, i.e., cognition, affect, and behavior [51]. These fundamental elements of CAB explain that cognition comes through a personal belief, perceptions, or attitude gained after accumulating knowledge about or experiencing a particular object, which creates effective responses, i.e., the kind of feeling or emotions that are generated from the facts and beliefs about that particular object, and finally lead towards the behavioral response, which can be either intention or resistance to adopt the particular object [52,53,54].

A large body of literature used CAB to understand enormous Internet-related fields, such as e-banking [55], mobile apps [56], social networking sites [55], and online buying and selling [57,58,59], which proves the differential effects coming after consumer’s cognition leading towards a particular behavior. Following the findings of Martinez et al. [59], the classical CAB paradigm is most appropriate when the particular object concerned is related to the Internet. As per the recommendations of Holbrook, CAB is considered a standard learning hierarchy suitable for these kinds of high-involvement behaviors [51]. While engaging in online shopping, consumers show their high involvement to form a behavior [60]. Therefore, CAB (high-involvement hierarchy) can be convenient to explain the behavioral intentions of online shoppers.

The CAB paradigm is also found suitable for understanding the underlying concepts of a customer’s loyalty or a customer’s continuous intention to use [61,62,63]. In summary, the CAB model has been found suitable for identifying an individual’s behavioral intentions in multiple contexts, and it seems helpful in determining the consumer’s continuance intention to do online shopping.

2.3. UGT and CAB

According to the UGT, an individual’s behavior toward any kind of media is influenced by multiple gratification elements. Consequently, UGT has been incorporated in extant literature to study online purchase continuance intention [25,26]. The CAB paradigm itself is vastly used to study behavioral responses arising from a user’s cognition with stimuli like product, service, or shopping environment, which generate affective responses and, thus, form a specific behavior like purchase intention. As discussed earlier, many recent studies employed UGT to study behavioral responses influenced by multiple gratification elements. However, these gratifications can also relate to the user’s cognition, which can generate multiple effects and can be more conducive in examining the behavioral responses. For instance, a satisfied customer will be more willing to continue using the same product or service [64,65], or a feeling of convenience can also help to retain customer intention to shop in the future [66]. Past studies insufficiently employed UGT in multiple studies to examine a user’s buying behavior generated through gratifications directly. We integrated UGT and the CAB paradigm to illustrate a multiple cognitive path design that elaborates the gratifications explored through user cognition, which form affective and behavioral responses simultaneously. This can lead us to better understand the whole picture behind the online purchase continuance intention generated through gratifications and behavioral responses.

3. Research Model and Hypotheses Development

3.1. Research Model

Prior literature suggests that using UGT, several gratification elements can be identified as a predictor to determine online purchase continuance intentions. According to several UGT scholars, if online shopping platforms can concentrate on a consumer’s needed gratifications, then they can successfully generate a user’s adoption and continuance intention to use the online shopping platforms. However, the increasing trend of these online platforms in society is encouraging consumers to do online shopping, which is evolving a need to study online informative gratifications that influence purchase continuance intention.

Therefore, these online informative gratifications can play a significant role in the sustainable use of online shopping platforms. After the careful perusal of extant literature, we devised our theoretical model (Figure 1) while integrating both UGT and the CAB paradigm to carry out our investigation. Based on our model, we posited that there are certain informative gratifications (i.e., layout and functionality, PEEIM), that are developed through cognitive ability, which produce multiple affective responses in consumers (i.e., customer satisfaction, convenience) leading toward a specific behavior (i.e., continuance intention). Moreover, we have incorporated online ratings, which indicate popularity opinion and act as a moderator between the affect and behavioral response.

3.2. Hypotheses Development

3.2.1. Layout and Functionality

Layout and functionality refer to the particular characteristics of an online shopping platform that can provide a sense of enjoyable interactions, ease to use, and fruitful experiences for consumers [67]. Subsequently, the author has considered the layout and functionality aspect as a part of the online physical environment, which is comprised of four dimensions, i.e., usability, the relevance of information, interactivity, and customization. The importance of website functionality and drivers toward customer satisfaction have been discussed considerably [15]. Consumers will prefer online shopping if they perceive the web platform is easy to use and provides sufficient information. In fact, consumers will experience a higher level of satisfaction if the layout of the online platforms particularly focuses on user-based design principles [68,69,70]. Through a conducive layout and functionality of the shopping platforms, the web effectiveness can be stimulated, and consumers can easily access a sufficient pool of information resulting in customer satisfaction. Recently, many theorists have highlighted the importance of the layout and functionality of web interfaces in the context of online shopping platforms [67,71,72]. Numerous authors have supported the fact that website quality or website layout and functionality of an online store have a huge impact on customer satisfaction [72,73,74,75]. Thus, we include layout and functionality as an informative gratification element that can be perceived by an individual’s cognition of the shopping platform. Moreover, this gratification can also motivate consumers and increase their satisfaction level regarding the shopping platform. Therefore, we find it appropriate to hypothesize that

Hypotheses 1a (H1a).

Layout and Functionality will have a positive impact on customer’s satisfaction.

Numerous studies have explored the positive association between online shopping and convenience [4,5,66,76]. Indeed, the consumers rely on convenience while initiating any behavior. However, one of the foremost reasons to adopt online shopping is convenience, i.e., shop from home or anywhere in the world. In particular, several elements in online shopping can enhance its convenience and need to be addressed. Luna et al. [77] emphasized the importance of the layout and functionality of a website because these are the fundamental items to determine the level to which a consumer feels comfortable or convenient. Piccoli et al. [78] posited convenience and interactivity as a critical factor of website effectiveness. A lesser cognitive effort needed to shop online is also related to convenience [79]. In this regard, the effective layout and functionality of online shopping platforms can make it convenient for consumers to gather needed information and perform transactions by saving their time and efforts simultaneously. Thus, layout and functionality act as informative gratification, which consumers can gain after their personal cognition, to stimulate their level of convenience. Therefore, we hypothesize that

Hypotheses 1b (H1b).

Layout and Functionality will have a positive impact on convenience.

3.2.2. Perceived Effectiveness of E-Commerce Institutional Mechanism (PEEIM)

PEEIM is a crucial construct related to a consumer’s financial security while conducting an online transaction on any e-commerce platform [13]. PEEIM connotes a buyer’s financial security perceptions regarding online transactional platforms, which assumes that an intermediary or third-party safeguarding mechanism is available to protect them from any risk or fraud while performing an online transaction [80]. Consequently, the author also emphasizes conducting future research to explore the influence of PEEIM in the e-commerce environment. Many willing buyers are reluctant to perform online transactions while doing online shopping because of the unavailability of PEEIM, which arises security concerns. Moreover, security concern is primarily an important factor in conducting customer satisfaction [81,82,83]. Transactional security can build up trust in consumers that can lead toward customer satisfaction with the online platforms [84]. A cognitive consistency has also been observed in the presence of PEEIM, which most likely results in the favorable perception of the e-commerce environment [85]. Consumers visiting online platforms are unable to proceed with their transactions due to the absence of PEEIM, which increases their financial security concerns. Perceived security is suggested as one of the most powerful drivers of customer satisfaction [81]. Thus, through personal cognition, PEEIM can provide informative gratification to customers pertaining transactional security, which drives customer satisfaction. Therefore, we hypothesize the following:

Hypotheses 2a (H2a).

PEEIM will have a positive impact on satisfaction.

Specifically, we focused on the feeling of convenience while performing online transactions without any security concerns. Given that, performing online transactions is considered to be a distinguishing feature of e-commerce platforms for consumers to shop conveniently by saving their time. Moreover, perceiving inconvenience and insecurity while performing online transactions are classified as important online shopping concerns [12]. Javadi et al. [86] proved that security concerns related to leaking of financial details or losing money can have a negative influence on a consumer’s adoptability of e-commerce platforms. An e-commerce institutional mechanism can ensure secure transactions for online buyers, generating transaction convenience. Most of the online consumers are conscious and reluctant to provide their financial or personal information because of security concerns. Thus, the effectiveness of e-commerce institutional mechanism can act as a surrogate indicator forming a positive perception about security. In this sense, convenience can be evaluated through PEEIM. Thus, we propose that PEEIM may provide informative motivation for performing online transaction conveniently and can be included in informative gratification. Hence, we hypothesize that

Hypotheses 2b (H2b).

PEEIM will have a positive impact on convenience.

3.2.3. Customer Satisfaction and Continuance Intention

A range of past and recent studies argue that customer satisfaction is a strong antecedent to predict a user’s continuance intention [20,87,88,89]. Customer satisfaction is a primary objective in consumer marketing, which develops affective responses in the consumer to make a purchase. Consumers decide whether to retain or discontinue a given product or service based on satisfaction or dissatisfaction with the product or service [90]. It has also been observed that satisfaction is the primary component that tends to form loyalty in customers toward a given product or service while resisting them to choose any other alternative [91,92]. Customer satisfaction is a core component in generating positive connections between buyer and seller, i.e., loyalty to use, and has been widely studied by several scholars [93,94]. A range of commentators has discussed the strong bonding between satisfaction and continuance intention across multiple e-environments, which particularly includes e-governance [95,96], online education [97], e-payment services [98,99], mobile apps [100,101], e-retailing [102], and e-books [103]. E-commerce platforms should focus on customer satisfaction because previous studies have validated its importance in an e-commerce context that generates diverse behavioral outcomes, i.e., customer loyalty or e-loyalty [64,88,91,92,104,105] and repurchase intention [106]. Thus, we assume that customer satisfaction is conducive to the occurrence of continuance intention. Consequently, if the gratification needs of consumers are fulfilled, then as a result, an affective response occurs, i.e., satisfaction, which can lead towards a positive behavioral outcome, i.e., continuance intention. Therefore, we put forward the following assumptions

Hypotheses 3 (H3).

Satisfaction will positively impact Continuance Intention.

3.2.4. Convenience and Continuance Intention

Extensive research on online shopping recognizes the imperative role of convenience in generating purchase intentions [66,107] and repurchase intentions [4,66,108]. Convenience is elaborated as consumers experiencing lesser effort while doing online shopping. The efforts vary in forms like physical [109], cognitive [79], or psychological [76]. Some existing studies argue that one of the primary motivations for e-consumers to shop online includes convenience, which is also considered a common incentive for online shopping [110,111,112]. Existing literature on convenience supports that it is the core element that generates motivation to shop online. Moreover, without convenience, it is impossible to experience online purchase [76,107,113]. Prior scholars also posit that convenience is a crucial factor strengthening the relationship between buyer and seller [114], which motivates consumers’ repurchase intention. Higher online convenience fosters consumers to seek as much information as they need efficiently, which also increases their online purchasing propensity [115]. Similarly, some recent evidence also highlights the significance of convenience in generating different purchasing trends [114]. Building on prior findings, we argue that convenience is indeed a powerful motivational factor that can boost continuance purchase intention in a favorable way. Thus, we incorporated convenience as an affective response generated through the consumer’s informative gratifications, which can lead towards continuance shopping intention. Therefore, the following assumption is put forward.

Hypotheses 4 (H4).

Convenience will positively impact Continuance Intention.

3.2.5. Moderating Role of Online Ratings

Extant prior literature has acknowledged the importance of online ratings that strongly influence consumers’ purchase decisions and repurchase intentions [116,117,118,119,120]. According to Filieri [116], online rating is elaborated as a type of online user opinion indicating an overall evaluation of a particular product or service based on gained experience. Moreover, consumers evaluate their given ratings generally based on their experience and perceived satisfaction level with the service used [121]. Online ratings influence purchase decisions, which can vary through rating quality and authenticity. Consumer general satisfaction with online ratings can drive purchase intention but the quality and reliability of online ratings can increase the motivation to purchase online [120]. Senecal and Nantel [122] and Filieri [116] posit that, online ratings have emerged as a modern source of e-word of mouth. Trong et al. [45], after taking into account the importance of online ratings in online shopping, move one step forward to refine this concept in the context of levels of online rating, i.e., high online ratings or low online ratings. Moreover, online ratings are suggested as an indicator of popularity opinion exerting a strong moderating influence between customer satisfaction and continuance intention.

Online ratings show conducive support to online consumers in making their decisions to purchase online and maintain their long-term bonding with the shopping platforms. Referring to UGT, ratings given by customers act as an informational cue throughout the decision process, which enforces purchasing behavior [121,123]. As per Neilson report, online ratings are found to be the second most trustworthy source after friends or family that provides information about a product or service [124]. Moreover, customers get throughout signals and support from online ratings while making up their decisions to purchase, which subsequently save their time, lessen their effort to search information, raise convenience level, and remove uncertainties. Despite the strong influence of online ratings on consumer behavior, very few researchers emphasize studying its influence on continuance purchase intention. Similarly, online ratings can provide substantial insights to shopping platforms generating satisfaction and convenience for online consumers because it can help in reducing the uncertainties and effort in making an online purchase. Thus, we incorporate online ratings as a reliable informative gratification source for making decisions and encouraging consumers to perform online purchasing frequently. Therefore, we propose the following hypotheses:

Hypotheses 5a (H5a).

Online Ratings positively moderate the relationship between satisfaction and continuance intention, and that satisfaction positively influences continuance intention more strongly when online ratings are higher.

Hypotheses 5b (H5b).

Online Ratings positively moderate the relationship between convenience and continuance intention, and that convenience positively influences continuance intention more strongly when online ratings are higher.

The overall theoretical model is shown in Figure 1.

4. Methodology

4.1. Sample and Data Collection

We used a two-part questionnaire to test our proposed model. The first part was composed of demographics and general information about the respondents, which includes area, gender, age, education, occupation, online shopping experience, and online shopping frequency. Consistent with our research model, the second part was based on the information about the impact of the constructs on continuance intention. The questionnaire was designed in English, as it is considered to be the official language in Pakistan. Our questionnaire’s target population includes students, employees, business owners, and also unemployed or retired people having experience of doing purchasing from any online platform or store working in Pakistan. Only the respondents from Punjab province and capital territory (i.e., Islamabad) were selected because these are the most advanced areas with the highest contribution to e-commerce order sharers, i.e., Punjab with 55% and Islamabad alone with 10% [125]. A pilot study was also conducted before questionnaire distribution to evaluate the format, design, wording, questions sequence, and other potential issues. The pilot test was distributed amongst 20 participants and after gathering their responses they were asked to comment for any observable discrepancies. The pretest, thus, confirmed the wording and ensured that the participants easily understood every item on the questionnaire.

A convenience sampling technique was employed, and data collection was done through a hybrid distribution method. Firstly, an online questionnaire was distributed on the most common social networking sites in Pakistan like Facebook and Instagram. Other popular social networks like WhatsApp and Snapchat were also incorporated to distribute questionnaire personally via hyperlink with a brief description of the study. Secondly, a paper-pencil questionnaire was also distributed among different group of respondents. The participation of respondents was strictly anonymous and voluntary. A week was given to every respondent to complete the questionnaire and the responses were recorded instantly upon the completion of the questionnaire. A gentle reminder was also given to some of the respondents after three days of the first request. One hundred and fifty hard copies were distributed and collected while 271 respondents were recorded though online survey. The survey ran for almost three months in post-pandemic time during October 2020–December 2020 in which a total of 421 responses were received. The post-pandemic time starts after the beginning of the pandemic in Pakistan, which eventually changed consumers’ mindset towards online shopping because of different restrictions like lockdown or quarantine. The responses that met one or more of the following conditions were dropped: (1) same respondent appeared twice or more in survey; (2) incomplete response; (3) subjects without experience of online shopping; and (4) uniform answers to all questions. Finally, 317 valid responses (a response rate of 75.3%) were used for the subsequent analysis. We followed Hair et al. [126] for estimating the minimum sample size criteria for maximum likelihood interpretation, i.e., 100 to 150. Considering the sample size of 317 in our study, it meets the minimum sample size criteria for a structural equation model with maximum likelihood estimation.

The detailed demographics of the response sample are exhibited in

Table 1. Demographics of Respondents (N = 317).

	Items	Percentage (%)
Age	0–15	6
	16–30	49.2
	31–45	33.1
	45+	11.7
Gender	Male	59.3
	Female	40.7
Education Level	High School	18
	Bachelor’s Degree	30.6
	Master’s Degree	36.9
	PhD or above	14.5
Occupation	Student	43.5
	Employee	36.6
	Business Owner	12.6
	Unemployed/Retired	7.3
Online Shopping Experience	Several Weeks	10.1
	Several Months	14.5
	1 year	12.3
	2 years	35.3
	5 years	20.2
	<5 years	7.6
Online Shopping Frequency	1–10	86.1
(times in a month)	11–20	9.5
	21–30	1.6
	<30	2.8

. As accumulated, a majority (59.3%) of the respondents were male and 82.3% were amongst the age group of 16–45. Furthermore, 82% of the study samples were at least graduates. Around 43.5% of the respondents were students, and 36.6% were employees, respectively. In particular, 86.1% reported shopping online 1 to 10 times within a month and 67.8% of the respondents had acquired online shopping experience for years. According to a report and analytics published by Picodi.com on online shopping in Pakistan, there are more online purchases made by men than women in Pakistan, i.e., 59% vs. 41% and more than half of the online shoppers, i.e., 56%, belongs to the age group between 25 and 34 [127]. Our demographics for gender and education level also resembles the statistics of the above report, which helps us to generalize these demographics on the whole population of Pakistan.

4.2. Measurement Instrument

To measure constructs of our CAB model, formerly validated measurement scales were adapted. All measures were assessed through a six-point Likert-type scale (from 1 = strongly disagree to 6 = strongly agree) in the survey, except for the demographic variables.

Specifically, the items of layout and functionality were adapted from Harris and Goode [71]. In particular, layout and functionality (thirteen items) were measured through three sub-dimensions: interactivity (two items), usability (seven items), and customization (four items). PEEIM was measured through a four-item scale adopted from Fang et al. [80]. Satisfaction was measured through a four-item adapted scale of Maxham and Netemeyer [128]. For convenience, we adapted a five-item scale of Burner and Hensel [129]. We measured the dependent variable, continuance intention, with a three-item scale adapted from Kim et al. [130]. Finally, the moderating variable online rating was measured through an adapted three-item scale of Filieri [116]. The measurement used in this study are shown in

Table 2. Measurement Items Standardized Loadings.

Constructs and Measurement Items	Loading	Cronbach’s Alpha
Layout and Functionality		0.971
1. Online shopping websites or apps are not easily navigated	0.850
2. Navigation through online shopping websites or apps is intuitively logical	0.862
3. There are convenient ways to move among related pages and between different sections on online shopping websites or apps	0.861
4. This web site is difficult to use	0.853
5. Online shopping websites or apps are user-friendly	0.883
6. If I wanted to, I could customize online shopping websites or apps to what I like (e.g., changing colors, layout, fonts, etc.)	0.852
7. Online shopping websites or apps are tailored to me	0.859
8. When communicating with online shopping websites or apps I am rarely addressed using my correct name	0.820
9. Online shopping websites or apps make purchase recommendations that match my needs	0.864
10. Online shopping websites or apps help me to compare products and prices	0.808
11. I feel that online shopping websites or apps are not very engaging	0.857
12. There is a great deal of irrelevant information on online shopping websites or apps	0.829
13. Technical details about products can be easily accessed on online shopping websites or apps	0.875
Perceived Effectiveness of E-Commerce Institutional Mechanisms		0.946
1. When buying online, I am confident that there are mechanisms in place to protect me against any potential risks (e.g., leaking of personal information, credit card fraud, goods not received, etc.) of online shopping if something goes wrong with my online purchase.	0.884
2. I am sure that I cannot be taken advantage of (e.g., leaking of personal information, credit card fraud, goods not received, etc.) as a result of conducting purchases online.	0.895
3. I believe that there are other parties (e.g., your credit card company) who have an obligation to protect me against any potential risks (leaking of personal information, credit card fraud, goods not received, etc.) of online shopping if something goes wrong with my online purchase.	0.921
4. I have confidence in third parties (e.g., SafeTrader, TRUSTe) to protect me against any potential risks (e.g., leaking of personal information, credit card fraud, goods not received, etc.) of online shopping if something goes wrong with my online purchase.	0.910
Satisfaction		0.950
1. I think purchasing products from the online store is a good idea	0.906
2. I am pleased with the experience of purchasing products from the online store	0.915
3. I like purchasing products from the online store	0.913
Convenience		0.946
1. Online shopping would be convenient for me	0.894
2. Online shopping would allow me to save time when shopping	0.893
3. Online shopping would make my shopping less time consuming	0.879
4. Online shopping would be a convenient way to shop	0.872
5. Online shopping would allow me to shop whenever I choose	0.871
Continuance Intention		0.867
1. I would consider using online websites or apps for shopping in the long term	0.844
2. If I could, I would like to continue my use of online websites or apps for shopping	0.832
3. All things considered, I will expect to continue to use online websites or apps for shopping into the future	0.808
Online Ratings		0.901
1. Customer ratings have helped me to learn about the product	0.890
2. Have improved my understanding of the quality of the product’s features	0.881
3. Were useful in order to evaluate the quality of product specifications/features	0.834

. To capture other online consumers’ characteristics that might be related to satisfaction, convenience, and continuance intention, we included some demographic control variables (e.g., gender, age, and education) in our research model to ensure that the empirical results were not covariant with other variables [45].

4.3. Data Analysis Technique

SPSS Statistics v. 21 and Amos v. 22 were employed to examine the proposed theoretical model. Structural equation modeling (SEM) was incorporated to estimate the loadings, construct, validity weights, and reliability among the construct relationships at multiple stages. Confirmatory factor analysis (CFA) was also conducted to find out the loadings, discriminant validity, and internal consistency of the internal model. Finally, we also tested the moderation to find out the effect of interaction variables on our dependent variable.

5. Results

5.1. Reliability and Validity

To assess the psychometric properties of our research model, we started with the reliability test of the constructs and measure the standardized loading of each element of the corresponding constructs. The results are listed in Table 2. All items were found with substantial loading on their corresponding constructs and Cronbach’s alpha value of every construct was found to be above 0.85. For this particular research, each recorded value was found good and over the threshold of 0.7 [131].

Moreover, we tested the convergent and discriminant validity through CFA. For evaluating convergent validity of the model, we follow the two standards suggested by Hair et al. [132] and Henseler et al. [133], according to which average variance extracted (AVE) of each latent construct should exceed 0.5 and secondly, the latent variable factor loading should exceed 0.5 (AVE > 0.5). Values of AVE were found in the range from 0.686 to 0.829, and the value of variance extracted of our scale items measuring the constructs exceed the shared variances of the corresponding constructs satisfying the recommended conditions. Discriminant validity follows Fornell–Larker standard according to which the AVE of each latent item must be greater than the maximum squared correlations among other maximum shared variance (MSV) [134]. MSV was also found lesser than AVE and the correlation values between each pair of constructs do not exceed the corresponding square root of the AVE for the measure, respectively. Hence, we found that every instrument in our study possesses sufficient psychometric quality to further continue with other phases of analysis.

5.2. Model Measurement

We deployed multiple fit criteria using Amos to compute inclusive model fit. An overall goodness-of-fit index (GFI) depicts whether the statistical findings are supported in our model or not. Following the suggestions of Bentler [135], a threshold value closer to 0.90 or higher is considered as a good fit for the model while the threshold value 0.8 or greater is recommended for the adjusted goodness-of-fit index (AGFI). The value of GFI and AGFI was found to be 0.835 and 0.806, respectively, which were considered as a good fit for our model. Moreover, the comparative fit index (CFI) used to examine the internal model fitting was also calculated. As recommended by Bentler [135], the accepted threshold limit for CFI ranges from 0 to 1. Thus, the deliberated CFI value was found to be 0.951 in our study confirming a good fit. Root mean square error of approximation (RMSEA) index was also investigated to evaluate the average of residuals not accounted for by our model. RMSEA accounted for in our study was 0.052 as recommended by Bentler and Yuan [136].

Table 3. Inclusive Statistics and Validity [Convergent and Discriminant] Matrix.

Constructs	AVE	MSV	1	2	3	4	5	6
			LF	CN	ST	IM	OR	CI
1. Layout and Functionality (LF)	0.726	0.130	0.852
2. Convenience (CN)	0.778	0.130	0.360 ***	0.882
3. Satisfaction (ST)	0.829	0.177	0.327 ***	0.243 ***	0.911
4. PEEIM (IM)	0.815	0.034	−0.184 **	−0.127 *	−0.031	0.903
5. Online Ratings (OR)	0.754	0.166	0.132 *	0.156 *	0.281 ***	0.005	0.869
6. Continuance Intention (CI)	0.686	0.177	0.186 **	0.267 ***	0.421 ***	−0.070	0.408 **	0.828

Notes: The number of respondents = 317. Along diagonal are square roots of AVE (Average variance extracted), Off-diagonal are inter-construct correlations. MSV (Maximum shared variance), Significance of Correlations: * p < 0.050, ** p < 0.010, *** p < 0.001.

exhibits the complete model fit summary reconfirming the model fit results of our study.

5.3. Hypotheses Testing

To conduct structural model analysis, AMOS was used, and SEM was incorporated to empirically test the formulated hypotheses. Computed standardized path coefficients are exhibited in

Table 4. Path Results.

Path	Regression Weights
	Estimates	S.E	C.R	p
Hypothesis 1a Satisfaction <--- Layout and Functionality	0.355	0.068	5.260	***
Hypothesis 1b Convenience <--- Layout and Functionality	0.344	0.060	5.700	***
Hypothesis 2a Satisfaction <--- PEEIM	−0.086	0.054	−1.592	0.111
Hypothesis 2b Convenience <--- PEEIM	−0.067	0.048	−1.398	0.162
Hypothesis 3 Continuance Intention <--- Satisfaction	0.331	0.050	6.617	***
Hypothesis 4 Continuance Intention <--- Convenience	0.128	0.056	2.293	0.022

Notes: The number of respondents = 317. Significance of Correlations: *** p < 0.001, C.R (Critical Ratios) represents t-values, S.E represents standard error).

. As predicted, our results indicate layout and functionality have the positive and sturdiest influence on satisfaction (β = 0.355, p < 0.001) and convenience (β = 0.344, p < 0.001), which support our H1a and H1b. However, contradicting our assumptions, the positive influence of PEEIM on satisfaction and convenience was found to be insignificant. Thus, our hypotheses H2a and H2b are not supported. As anticipated, our findings revealed that both satisfaction (β = 0.331, p < 0.001) and convenience (β = 0.128, p < 0.05) exert a positive and significant influence on continuance intention, consequently confirming H3 and H4.

5.4. Moderation Analysis

Table 5. Moderation Test Results.

Variables	DV---Continuance Intention				DV---Continuance Intention
	Model 1				Model 2
	Model 1a		Model 1b		Model 2a		Model 2b
	Coeff	S.E	Coeff	S.E	Coeff	S.E	Coeff	S.E
Control Variables
Age	−0.119	0.088	−0.116	0.087	−0.143	0.091	−0.132	0.090
Gender	0.043	0.139	0.062	0.138	−0.066	0.144	−0.088	0.143
Education Level	0.119	0.072	0.124	0.071	0.173 *	0.075	0.168	0.074
Main Effects
Satisfaction	0.403 ***	0.072	0.406 ***	0.071
Convenience					0.202 **	0.072	0.246 ***	0.074
Online Ratings	0.342 ***	0.072	0.393 ***	0.074	0.427 ***	0.072	0.454 ***	0.072
Moderation Effects
Satisfaction X Online Ratings			0.175 *	0.070
Convenience X Online Ratings							0.153 *	0.064

Notes: The number of respondents = 317. Significance of Correlations: * p < 0.050, ** p < 0.010, *** p < 0.001.

illustrates the models to check the moderation effects, and the results accounted for in the table confirmed the moderating effects of online ratings. Regarding the effect of interaction variables, online ratings positively influence the relationship between satisfaction and continuance intention (β = 0.175, p < 0.05). Consequently, online ratings also positively moderate the relationship between convenience and continuance intention (β = 0.153, p < 0.05) as predicted.

To further elucidate our interpretations, we estimated simple slope and plotted the interaction at one standard deviation above or below the mean of our moderator. Figure 2 represents that the slope regression line for the effect of satisfaction on continuance intention was positive and statistically significant for the high online rating (β = 0.65, p < 0.050), but not significant for the low online rating (β = 0.16, ns). However, we also found that at the high level of online ratings, continuance intention increased more promptly than at the low level of online ratings when satisfaction increased. Consequently, Figure 3 portrays that the sloped regression line for the effect of convenience on continuance intention was also positive and statistically significant for the high online rating (β = 0.46, p < 0.05), but not significant for low online ratings (β = 0.03, ns). Therefore, our results showed statistical support for H5 and H6, respectively. The general summary of our hypotheses testing is demonstrated in

Table 6. Hypotheses Test Results.

Hypotheses	Result
Hypotheses 1a (H1a).Layout and functionality positively affects Satisfaction.	Supported
Hypotheses 1b (H1b).Layout and functionality positively affects Convenience.	Supported
Hypotheses 2a (H2a).PEEIM positively affects Satisfaction.	Not Supported
Hypotheses 2b (H2b).PEEIM positively affects Convenience.	Not Supported
Hypotheses 3 (H3).Satisfaction positively affects Continuance intention.	Supported
Hypotheses 4 (H4).Convenience positively affects Continuance intention.	Supported
Hypotheses 5 (H5).Online Ratings positively moderate the relationship between satisfaction and continuance intention, and that satisfaction positively influences continuance intention more strongly when online ratings are higher.	Supported
Hypotheses 6 (H6).Online Ratings positively moderate the relationship between convenience and continuance intention, and that convenience positively influences continuance intention more strongly when online ratings are higher.	Supported

.

6. Discussion

Our study aims to investigate the influence of informative gratifications, i.e., layout and functionality, and PEEIM, on customer satisfaction and convenience. In addition, we also explored the meaningful linkages of customer satisfaction and convenience with continuance intention to shop online while keeping online rating as a moderator. Our empirical results confirm that most of the hypotheses were found significant (Table 6).

Firstly, our findings demonstrated the imperative role of layout and functionality of a shopping platform as the sturdiest indicator of customer satisfaction and convenience [15,77]. Moreover, it is found as an important informative gratification element that evolves through consumer cognition, which influences online shoppers [71]. This implies that a well-designed layout and effective functionality could enhance customer satisfaction and convenience, which will increase online shopping competence, integrity, and benevolence [15]. Thus, enforcing consumer’s continuous usage of online shopping. The strong layout and functionality of a shopping platform will ease consumers during the whole process of online purchasing from finding a product to deciding to buy and performing transaction [14]. Another most valid concern of consumers while shopping online is to satisfy their needs, when they found it convenient to use online shopping can result in greater satisfaction level [72]. Moreover, when consumers will find online shopping platforms convenient to use, it will automatically motivate them to save their time and make a safe online purchase effectively [15]. Most consumers get irritated while doing online shopping when they feel difficulty in using the website or app, experience plenty of irrelevant information, are unable to customize their search, and when there is an absence of interactivity with the supplier or platform causing dissatisfaction and inconvenience to consumers [45]. To the best of our knowledge, few studies have emphasized generalizing the role of layout and functionality as an informative gratification and its sturdiest impact on customer satisfaction and convenience in the online shopping context. Moreover, rare studies incorporated these informative gratifications as a cognitive path towards consumer continuance intention. Thus, it opens the window for future researchers to emphasize their research deeply on informative gratifications correlating with consumer cognition.

Unfortunately, contradicting our assumptions, PEEIM was found insignificant in developing its positive impact on customer satisfaction and convenience in the Pakistan e-commerce market. We intend to explain the possible reasons for this insignificant relationship through a recent study [137], which posits the preference of cash on delivery (COD) over e-payment in Pakistan. Due to the weak and insecure infrastructure of e-payments in Pakistan, COD has become a primary mode of payment while doing online shopping, which plays a dominant role in e-commerce adoption among Pakistani consumers [137]. The increase in online scams and unavailability of effective e-commerce institutional mechanisms tend to make consumers lose their control over the entire buying process while doing e-payments. COD mode particularly increases consumer perceived control over the purchasing process [137]. PEEIM plays a crucial role in building a safe, trustworthy, and legal environment in the online market [138], which is absent in Pakistan’s online context. This creates a sense of consumer distrust on e-commerce platforms causing dissatisfaction and inconvenience. We found this scenario as a valid reason behind the rejection of our hypotheses.

Moreover, as expected, customer satisfaction and convenience are the dominant antecedents of continuance intention in Pakistani online shoppers. These results are found consistent with the previous studies’ findings as well [66,88,89,108]. Furthermore, we explored that customer satisfaction and convenience are suitable affective responses in CAB, which bear a tendency to form particular behaviors [63]. Finally, our study demonstrates a valid role of online ratings as a moderator strengthening the effect of customer satisfaction and convenience on continuance intention. Our findings posit that, online ratings can enhance customer satisfaction and convenience level while making an online purchase, thus, enforcing and generating stronger continuance intention [45,120]. Moreover, online ratings also act as informative gratification that allows consumers to make up their purchasing decision while analyzing other consumers’ opinions regarding a product or service [121,123]. Our study particularly highlights the critical role of online ratings as a moderator in online shopping in Pakistan. Consequently, we recommend other researchers to explore the dynamic role of online ratings in developing consumer behavior and continuance intention concerning other constructs of online shopping.

6.1. Theoretical Contribution

Our study holds several insightful contributions to the literature that are worth mentioning:

• First, numerous studies have employed UGT to conduct consumer behavior [10,24,139]. However, our study empirically investigates the theoretical importance of UGT in carefully examining the distinctive relationship among informative gratification elements, customer satisfaction, convenience, online ratings, and continuance intention.
• Second, our study moves one step forward to examine the influence of informative gratifications on customer satisfaction and convenience simultaneously.
• Third, our study extends the literature by integrating UGT and the CAB model for the first time to investigate the dominant role of informative gratifications on customer satisfaction and convenience and examining these gratifications as a consumer’s cognitive path according to the CAB model. Moreover, we introduced a CAB model that adds in UGT to show an amalgamation of PEEIM and layout and functionality. However, our findings prove the sturdiest impact of layout and functionality on both customer satisfaction and convenience [15,77] but contrary to other studies, PEEIM did not show valid support to our assumptions in Pakistan. This is due to the absence of an effective e-commerce institutional mechanism in Pakistan, which is causing distrust and increasing security concerns in online shopping. Furthermore, it increases consumer’s positive concern with COD and accepting it as a primary mode of payment while shopping online [137]. Therefore, our findings reveal a major drawback in Pakistan’s e-commerce industry, which makes the online environment suspicious and shows a need for an effective e-commerce institutional mechanism that favors customers’ high propensity to consume online shopping. This also opens a way for future researchers to elaborate on the role and importance of PEEIM in Asian countries like Pakistan and its significance in e-commerce development.
• Fourth, the dominating role of PEEIM has been discussed widely as a moderator in many studies [140,141]. However, fewer studies explored the PEEIM role as an independent variable. Besides, our findings also revealed that PEEIM did not have a significant impact on satisfaction and convenience. Moreover, our sample shows that around 50% of people have two to five years’ experience in online shopping but still around 85% of the people shop only 1 to 10 times in a month, which is very low in comparison to a western context. We believe that the absence of PEEIM creates dissatisfaction and inconvenience, which lower the frequency of online shopping in Pakistan and also lower the continuance intention to shop online.
• Fifth, our findings determined that customer satisfaction and convenience could strongly predict continuance intention to shop online in Pakistan [87,88,89,142]. Sixth, our study contributes immensely to the extant literature by suggesting online rating is a robust indicator that positively moderates the relationship of customer satisfaction and convenience with continuance intention [45,120]. Following prior investigations by Trong et al. [45], our results illustrate that online ratings strengthen the relationship between satisfaction, convenience, and continuance intention. Therefore, our empirical findings move one step further by demonstrating the critical role of online ratings in developing stronger continuance intention to shop online and provide guidelines for future researchers to deeply analyze its crucial role in the online shopping context.
• Finally, our post-pandemic data of Pakistani consumers also add novelty to our research, since the pandemic act as a catalyst to e-commerce industries worldwide including Pakistan [143]. According to a report published by Statista [144] in the year 2020, 40% of the respondents from the Middle East, the North African region, and Pakistan encountered the pandemic as the reason behind online shopping. Moreover, 45% of the respondents reported an increase in their online shopping frequency as compared to the start of the pandemic. Therefore, our findings provide useful insights to practitioners to measure the change in online consumer behavior after the pandemic, as most previous studies rely on pre-pandemic data.

6.2. Practical Implications

The findings of this study provide useful insights to practitioners on how to develop and design a purposeful and safe shopping platform that may lead towards consumer retention. Furthermore, our findings develop an understanding that consumers seek satisfaction and convenience simultaneously to make online transactions. In this regard, online shopping platforms should regularly monitor and evaluate customer satisfaction and convenience as a noteworthy predictor of continuance intention. Notably, the online shopping platforms should focus on the satisfaction and convenience of consumers at the early stages of their online purchase decisions. E-commerce’s recent and new entrants should focus on layout and functionality, and PEEIM, because consumer perception about the product or service is replicated here. We can also say that the product or services shown on shopping platforms are virtual unless we buy or use them. Therefore, shopping platforms should focus on initial gratifications and the consumer’s cognitive processes that lead toward customer satisfaction and convenience. However, our findings reveal the layout and functionality of online shopping platforms, i.e., websites or apps, is a proven predictor of satisfaction and convenience. To increase layout and functionality, shopping platforms should concentrate on usability, the relevance of information, interactivity, and customization as demonstrated by Harris and Goode [67]. They can also work on identifying some more informative gratifications elements as our result shows a significant effect of informative gratifications in developing customer satisfaction and convenience.

To attract online shoppers in Pakistan, shopping platforms should continuously try to configure novel approaches, like options that ease online shopping, assure security, and removes ambiguity, e.g., Alibaba in China consists of a user-friendly layout and functionality with an effective e-commerce institutional mechanism ensured by Alipay, which helps a lot in removing uncertainties and creating trust and an easy to use platform for shopping. This plays an important role in developing relational benefits with consumers and tends to engage customers in a long-term relationship with online shopping platforms.

Furthermore, our findings raise another valid point of concern for the online shopping platforms in Pakistan, which is that although COD is favoring most consumers to shop online it should not be neglected that COD is an alternative mode of payment that arises due to high distrust and insecurity in an online environment that considerably affects consumers continuance intention to shop online. Therefore, online platforms should take the necessary steps to validate effective e-commerce institutional mechanisms in Pakistan to create a legal, trustworthy, and secure online environment leading towards strong continuance intention.

Moreover, our findings indicate the crucial role of online ratings as a moderator affecting the relationship of customer satisfaction and convenience with continuance intention [45,120]. Moreover, we also identify that such an effect will be stronger in the presence of high online ratings [45]. Online shopping platforms should make strategies to enhance customer satisfaction and convenience, and meanwhile build up stronger online ratings to ensure a stronger continuance intention in consumers to shop online. Consequently, online platforms should mitigate the security concerns, assure safe transactions, and confirm the quality of product or service through authentic and strong online ratings to create customer satisfaction and convenience, which are integral antecedents of continuance intention.

Subsequently, our target was to examine online shopping consumer’s continuance intention in Asian countries with diverse cultural characteristics and focusing an emerging e-commerce market, specifically Pakistan, which highlights crucial insights for early marketing practitioners. Marketing strategies on strengthening continuance intention can initially be formulated based on informative gratifications, which drives through consumer’s cognitive path to conduce favorable affective responses, i.e., customer satisfaction and convenience, facilitating continuance intention. Finally, the online ratings strategy promotes online interactivity, which helps in diminishing the ambiguities in the online shopping process and moderates the relationship of customer satisfaction and convenience with continuance intention.

6.3. Limitations and Future Scope

The present research contains several limitations that need to be addressed. Firstly, the present study particularly validated the results from online shoppers in Pakistan. The characteristics of Pakistani consumers may differ from those located in other Asian countries. Therefore, we recommend that the present model should be tested and cross-validated in the wider context in other emerging Asian e-commerce markets to provide additional insightful findings. Moreover, we selected online shoppers in Islamabad and Punjab province based on convenient sampling and generalized our results on Pakistan, which is a limitation to our results. Therefore, future scholars are encouraged to involve more areas in Pakistan like Sindh or KPK to enrich this study. Secondly, we integrated UGT and the CAB paradigm to analyze a single perspective, specifically online shopping, which itself is a broader concept. However, online shopping can be categorized as related to some particular products or services like clothes, food, electronics, automobiles, etc. So, future researchers can focus on different attributes of online shopping to validate this integrated model. Thirdly, only one control variable out of three, i.e., education level was found statistically significant in our model. Therefore, future research could consider other control variables that can show a positive association. Fourth, our respondents were general consumers of online shopping or online shoppers having their viewpoint, which can oppose the perspective of online shopping platform managers. So, this evolves a need to generalize the behavior of online shopping platform managers in this context, which can expose some valuable insights. Fifth, we found informative gratifications as a significant predictor of customer satisfaction and convenience facilitating continuance intention. Therefore, some more gratifications should be explored specifically in an online shopping context. Lastly, our present research is comprised of a relatively small sample size, i.e., 317 respondents, so future researchers should consider choosing a larger sample size in this context to elaborate empirical findings.

7. Conclusions

This study integrates UGT and the CAB paradigm to scrutinize the sturdiest impact of gratifications on customer satisfaction and convenience, which are drivers for continuance intention to shop online. Our findings provide empirical evidence and thoughtful insights related to online shopping literature by exploring the strong positive impact of layout and functionality on customer satisfaction and convenience, which facilitate continuance intention. Moreover, our findings also indicate that the absence of PEEIM in the Pakistani e-market would induce distrust and security concerns lowering continuance intention. This is also the foremost reason for the adoption of COD in Pakistan. Building continuance intention and having loyal customers is an imperative concern in online shopping or e-businesses, which drive e-commerce platforms to sustain a competitive advantage in the e-market. Customer satisfaction and convenience should be measured simultaneously to predict continuance intention. Online ratings bear a critical moderating role as an informational cue for consumers, which enhances continuance intention. Thus, our empirical findings can help practitioners in validating their marketing strategies and enhancing their sustainability in the e-market.