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Review

The Role of Virtual Environment in Online Retailing: State of the Art and Research Challenges

by
Sara Poggesi
,
Michela Mari
*,
Arash Kamangar
and
Pinalba Schilleci
Department of Management and Law, Faculty of Economics, Tor Vergata University of Rome, 00133 Roma, Italy
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(7), 4131; https://doi.org/10.3390/su14074131
Submission received: 15 January 2022 / Revised: 9 March 2022 / Accepted: 22 March 2022 / Published: 30 March 2022
(This article belongs to the Special Issue Online Retailing and Sustainable Marketing)
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Abstract

:
The aim of the paper is to systematically analyse the effects of the online environment on customers’ behaviour in order to offer a first, comprehensive state-of-the-art of the research on this topic. By analyzing a final sample of 105 papers, 4 themes have been identified, according to the theoretical lenses adopted by scholars. Results show that the traditional stimuli–organism–responses approach (also known as S–O–R) is the most frequently applicable conceptual framework for the analysis of the effects of the online setting, and worth mentioning are the modifications to the original S–O–R model proposed by scholars, which allow considering the specificities of the online environment.

1. Introduction

Over recent years, e-commerce has become a critical aspect for companies across the globe, to the point that, in 2025, global B2C e-commerce sales are forecasted to reach 7.391 billion U.S. dollars, a significant increase when compared to the 1.336 billion of 2014 [1]. These data confirm that B2C e-commerce is one of the fastest growing sectors within the world economy, and researchers agree in predicting that Internet shopping will continue to grow at a tremendous rate, despite its statistics not being easily accessible.
In the investigation of B2C e-commerce peculiarities, scholars are increasingly pointing out the relevance of firms’ adopted electronic retailing format (i.e., the website) in affecting customers’ behaviour in terms, as an example, of purchase and repurchase intentions, repatronage behaviours, loyalty, and word of mouth (WOM). These reactions seem to be very similar to those associated with customers’ interactions to physical retail settings [2,3], the goal both in the physical and online setting being the same, i.e., to enhance customers’ experience by means of the proper management of the environment in which the products are sold or in which the services are provided [4,5].
Specifically focusing attention on the online setting, the conscious designing of web environments in order to develop positive effects in customers and to increase positive responses is generally labelled “online atmosphere/online servicescape” and just as physical retailers provide relevant information through the “atmospherics” [6] or the “servicescape” [7] of their physical stores, online retailers (also known as e-tailers) also provide important information through the atmospherics of their websites (the e-servicescape). Over the years, different terms have been used by scholars to describe the online setting, i.e., “cybermarketscapes”, “e-scapes”, “online atmos-pherics”, “cyberscape”, “bricks-and-clicks” setting (in contrast to “bricks-and-mortar”) or the “clicks-only” setting a clear consensus on the dif-ferences among such labels has not yet emerged. Following [8], in this paper, web/online/e-atmospherics, web/online/e-servicescape and web/online/e-environment are used synonymously.
Research clearly points out that, to date, the online environment has a strategic relevance for firms; notwithstanding, no clear systematization of how the online retail context does affect customers’ behaviour and, in turn, firms’ outcomes is available yet.
Thus, this paper aims at answering the following research question: which are the effects of the online environment on customer’s behaviour? In order to answer to such a research question, a systematic literature review (SLR) on 105 papers has been conducted.
In particular, this paper aims to fill the above highlighted gap by systematically reviewing the academic literature on the effects of the online environment on customer’s behaviour, which has been published over the years in management journals, in order to give readers a still-missing structured, solid, and updated analysis of the existing results on the topic. In doing so, by applying a strict reading guide, a final sample of 105 papers has been analyzed; then, papers have been categorized according to (a) the paper’s keywords, (b) the paper’s research question(s), and (c) the employed theoretical framework. In doing so, we have identified the following four themes, “S–O–R (stimuli–organism–responses) application”; “TAM (technology acceptance model) application”; “Flow-theory application”; “Convergences”. Results show that the S–O–R approach is the most frequently applicable conceptual framework to the analysis of the online setting and worth mentioning are the modifications to the original S–O–R model proposed by the scholars, which allow taking into account the specificities of the online environment.
The paper is organized as follows. Firstly, the theoretical underpinnings are presented. Secondly, the methods for the analysis are defined. Thirdly, an overall analysis of the selected papers is provided. Fourthly, the literature trends for each of for identified themes are discussed. Finally, the most significant conclusions and managerial implications are presented.

2. Theoretical Underpinnings

Traditionally, to analyse the impact of the environment on customer’s behaviours, three different theories have been elaborated over the years.
The first one is here labelled S–O–R approach and is grounded on three studies. First, the ref. [6]’s study, in which the concept of atmospherics, defined as the “conscious designing of buying environments to produce specific emotional effects in the buyer that enhance his purchase probability” (p. 50), is introduced for the first time. Second, the ref. [9]’s study, in which the S–O–R framework is presented. In more detail, as Stimuli, [9] refer to the physical aspects of the environment (i.e., colour, thermal stimulation, light intensity, sound stimulation, taste and odour, tactile stimulation). As Organism, they refer to PAD (i.e., Pleasure-Arousal-Dominance), where pleasure-displeasure is the person’s feeling state, ranging from extreme pain or unhappiness to extreme happiness or satisfaction; arousal was defined as a mental activity determining the degree to which a person feels excited, stimulated, alert, or active in a situation, and dominance-submissiveness refers to the extent to which the individual feels in control of the situation rather than being restricted in his/her behaviour. Finally, according to [9], any response to an environment can be categorized as either “approach” or “avoidance” behaviour, which include four important aspects: the desire to physically stay in the situation; the desire to explore the situation; the desire to work in the situation; the desire to affiliate with the situation. Interestingly, these two scholars hypothesize the presence of moderating variables, e.g., neuroticism, extraversion, affiliative tendency. Third, the ref. [7]’s paper in which the marketing research relating to atmospherics and the S–O–R framework find their integration in the servicescape model, whose purpose is to understand how the physical surroundings affect both customers and employees in service organizations. These three studies are profoundly influencing the research on the effect of the online environment on customer’s behaviour. In this regard, worth mentioning are [10,11] who, for the first time, theoretically apply and thereafter empirically test the S-O-R approach to the online shopping environment
The second theory is the flow theory. Flow was introduced by [12], who defines it as “the state in which people are so involved in an activity that nothing else seems to matter” (p. 4). Additionally, it is described as “the holistic sensation that people feel when they act with total involvement” (p. 36). Recently the flow concept has been used for describing human-computer interactions in a computer-mediated environment, and it is conceptualised as a cognitive state which is determined by: (1) high levels of skill and control; (2) high levels of challenge and arousal; (3) focused attention; and (4) interactivity and telepresence [13]. Thus, according to the scholars who adopt such an approach to analyse the impact of the online environment on customer’s behaviours, customers must experience flow in their online interactions in order to generate positive behaviour outcomes. Moreover, the elements of flow are clustered into two categories. The first includes the functional flow elements, for example interactive speed of the website, which are typically associated to a satisfying virtual buying experience for users with utilitarian goals. The second category comprehends the so-called hedonic flow elements (e.g., time distortion), that typically allow users to perceive him/herself as more socially adept than in reality. Ref. [14] show that the concept of flow has major impact in terms of benefits for the so-called utilitarian customer, in comparison to the experiential-oriented ones.
The third theory is the technology acceptance model (TAM). The TAM is widely used in information systems and aims to predict the user’s intention to use the technology by considering the web store as a technology system and the web consumer as a computer user. Although since its introduction research has extended to the point to identify TAM 2 and TAM 3 [15,16], the original TAM postulates that usage intentions depend on the perceived ease of use (PEOU) and perceived usefulness (PU) of an information system [17]. PU is defined as the extent to which a person believes that using the system will enhance his or her performance, while PEOU is defined as the extent to which a person believes that using the system will be free of effort. More recently, “enjoyment” has been proposed as a new construct to consider, and it was defined by [17] as the degree to which using technology supplies reinforcement by itself, aside from any results in terms of outcomes that might be foreseen.
Stemming from this brief overview, this paper aims at systematizing the theoretical and empirical management papers that, over the years, have applied the three above defined theories to analyse the influence of the online environment on customers’ behaviour. In order to address this question as precisely as possible, we adopt the systematic literature review (SLR) method, whose criteria and main results are highlighted in the next section.

3. Method and Review Framework

The research question of this study has been addressed by conducting an SLR, and [18]’s approach—among the most cited for SLR in management—has been followed.
Accordingly, four steps have been developed.

3.1. General Planning of the Review, in terms of Identification of Keywords, Databased Research and Protocol

In this step, 30 keywords have been identified to start the process. These keywords are: “e-servicescape” or “e servicescape” or “online-servicescape” or “online servicescape” or “electronic servicescape” or “electronic-servicescape” or “web servicescape” or “virtual servicescape” or “e-scape” or “cyberscape” or “e-atmosphere*” or “e atmosphere*” or “online-atmosphere*” or “online atmosphere*” or “electronic atmosphere*” or “electronic-atmosphere*” or “web atmosphere*” or “website atmosphere*” or “web site atmosphere*” or “virtual atmosphere*” or “e-environment*” or “e environment*” or “online-environment*” or “online environment*” or “electronic environment*” or “electronic-environment*” or “ web environment*” or “website environment*” or “web site environment*” or “virtual environment*”.
The asterisk at the end of a search word allowed for different suffixes (e.g., “virtual environment” or “virtual environments”).
These keywords have been selected in order to ensure inclusion of all those papers dealing with online environment issues.
Three databases have been selected to conduct the research: Clarivate Web of Science (WoS), Ebsco, and Scopus. We selected these three databases as they are considered the most comprehensive sources of studies in the social sciences (e.g., [19,20]), which also contain a great range of high-quality peer-reviewed journals [21]; therefore, they have been widely adopted in previous management research (e.g., [22,23,24]).
We searched the keywords previously identified within peer-reviewed “journal articles” (purposely excluding conference papers, books, and book chapters); moreover, we considered only papers written in English and only management journals were selected (the Journal of Quality List 2021 was used for Ebsco Host’s papers identification). Overall, 5440 papers were identified. After eliminating duplicates, 297 articles were identified.
Details are shown in Table 1.

3.2. Inclusion/Exclusion Criteria

Abstracts were reviewed to ensure substantive context. Three main inclusion/exclusion criteria were used: (i) papers related to the physical environment were discarded; (ii) papers related to the influence of the online environment not focused on customers’ behaviour were discarded; (iii) only those papers grounded on a clear theoretical framework aimed at investigating the influence of the online environment on customers’ behaviour were considered.
This process excluded 159 papers, leading to 138 relevant documents.

3.3. The Selected Articles’ Evaluation

A full-text analysis of selected papers was performed to ensure articles’ substantive relevance and the previous three criteria were further applied. Finally, the research outputs were consolidated by adopting the snowballing technique. 105 articles were considered eligible for the SLR.
Figure 1 illustrates the flow diagram of the different steps undertaken for this systematic review.

4. Research Results

4.1. The Evidence Base

In this section, we provide an overview of the evidence base we have used for this manuscript.
Specifically, we analyzed the 105 selected papers according to (i) the journals in which they have been published; (ii) the distribution of the years of publications.
Regarding the journals involved in the conversation, in Table 2, the journals having published at least three or more papers on the subject in the investigated period are identified.
Interesting to note is the fact that the number of journals that have published a minimum of three papers on this issue is consistently lower in comparison to the overall number of journals in our dataset (equal to 52). Few are, indeed, the journals really committed in understanding the underling dynamics of an online environment and, among them, Journal of Business Research definitely plays an outstanding role, with 15 papers published on this topic.
If we then move to the distribution of papers per year, Figure 2 shows that the distribution of publications on a yearly base has been swinging over time, even though a consistent increase in the interest towards this topic can be noticed starting from 2008.
At an overall level, indeed, if we consider the entire period, an average of 4.7 papers per year has been published, but if we consider the time period 2000–2007, an average of 2.1 papers per year have been published, against an average of 6.3 papers per year published in the time period 2008–2021.

4.2. Papers’ Analysis

Extraction and synthesis of data represent the final step of the SLR process [25], allowing for an in-depth analysis of the selected papers in order to highlight the areas of interest, the links among each of the papers, and the connections between and among each research theme. Specifically, in order to analyse the 105 papers, a three-step analysis has been performed. Firstly, by manually sorting three dimensions, namely: (a) the paper’s keywords, (b) the paper’s research question(s), and (c) the employed theoretical framework, codes for each paper have been identified. Secondly, coherent codes have been grouped into four themes:
  • Theme 1—S–O–R application.
  • Theme 2—Flow theory application.
  • Theme 3—TAM application.
  • Theme 4—Convergences.
Finally, an in-depth systematic analysis of the selected 105 papers was conducted. To do this, a reading guide for the papers was established, shared among the authors, and then employed to read and analyze the articles.
In Table 3, a sample of the investigated papers is presented.

5. Analysis of the Literature

An in-depth analysis of the most intriguing food for thought of the selected papers, according to the adopted theoretical framework, is hereafter provided.

5.1. Theme 1—S–O–R Application

The first identified theme refers to all the papers within our dataset dealing with the S–O–R approach. In academic literature, the S–O–R approach is traditionally grounded on three core studies: Ref. [6]’s one, the ref. [9]’s study and the ref. [7]’s paper. These three studies are still, to date, profoundly influencing the research on the online environment’s impact on patronage intentions as this theme clusters the highest number of papers. Worth mentioning are [10,11] who, for the first time, theoretically apply and then empirically test the S–O–R approach to a virtual purchasing setting.
Interestingly, the results from their empirical analysis show that “online store atmosphere does…make a difference” [11] (p. 148). Specifically, the virtual environment’s atmosphere influences pleasure, which affects attitude, which then has strong effects not only on satisfaction and approach/avoidance behaviour, but also on customers’ pleasure and arousal.
That being stated, two sub clusters in this theme have been identified:
  • new insights: in this sub-cluster a deep analysis of how scholars, starting from [10,11], have revised the traditional S–O–R model to find a better fit with the online environment is presented.
  • Emerging trends: in this sub-cluster papers that investigate new issues by applying the S–O–R approach are categorised.

5.1.1. New Insights

In this sub-cluster, papers have been further analysed according to the investigated S–O–R’s dimension—i.e., stimuli (S)–organism (O)–responses (R)—and its moderators.

Stimuli

Papers here clustered take a step further in research on S–O–R’s stimuli dimension applicable to the online environment.
Two different kinds of papers can be identified: those that, considering a significant number of e-servicescape cues, examine the online setting from a holistic perspective, such as [28,31,38]; those that have basically followed [10]’s indications, grounding their analyses on specific cues with the aim of understanding how e-servicescape influences customers’ behaviour, such as [39,40,41,42,43,44]’s papers.
Interestingly, differently from the research on the physical servicescape, still few are the papers in the dataset which analyse the effects of cues such as colours and music on the Internet purchasers’ emotional responses thus, consequently, on their behaviours; an exception is represented by the paper by [44], whose results show that Taiwanese interviewers experiencing a fast-tempo music condition show a higher level of approach-behavioural intention than those experiencing a slow-tempo condition and that warm colour generates higher levels of purchasing intention. Even fewer are those works that take a step further by analysing the interaction between music and colour through the lens of the S–O–R model. This line of inquiring is coherent with the idea, well developed in studies on the physical servicescape [45], that the “right” fit between music and colour can strengthen the participants’ level of arousal and pleasure as the servicescape is a holistic system.

Organism

Papers here clustered contribute to the literature by considering new variables able to conceptualise the organism dimension of the S–O–R model.
The first group of papers “revises” the traditional pleasure/arousal model. [46], for example, use “excitement” as the organism and define it as “a positive emotional state that consists of high levels of pleasure and arousal” (p. 1172). [47] uses the traditional pleasure and arousal dimensions as the organism, but they also introduced the expression “delight”, referring to it as a particular emotion which derives from the mix between the specific emotions of arousal and pleasure.
The second group of papers takes into consideration the dominance emotion of the PAD model. Specifically, [48] clearly explains why it is important to investigate such emotion when referring to the online environment and the reason can be identified in the fact that “online shoppers control the shopping process” (p. 227). Ref. [49] employs the entire PAD model to analyse the effect that product presentation (flat or “on model”) and music have on emotions, further examining if and how emotions affect cognitive (attitude towards the website) and conative responses (purchase intention). Results show that the way in which products are presented has an impact on pleasure, as well as on arousal and dominance.
The third group of papers adopts different measures derived from PAD to investigate emotions. Ref. [50], for example, introduces the concept of “mood”, which refers to a variable related to the organism, specifically measured adopting [51] “Joy and Distress” scale. Ref. [40] abandons the PAD model in favour of the concept of emotions proposed by [52]. Ref. [53] uses, as organism, both the personal cognitive evaluations related to states based on circumstances and the six emotional states from [54].
Finally, the fourth group of papers introduces trust as the organism. Worth citing among them are surely three papers; the first is the paper by [44] that, differently from [11], is based on [7]’s model. By using trust in the website as the organism and purchase intentions as responses, results show that aesthetic appeal is the most significant e-servicescape dimension on trust and that trust is positively related to shoppers’ purchase intentions. The second is the paper by [55] that, for the first time, analyses the Thai Generation Y group, showing that for this target, online repurchase intention is positively related to the extent to which they trust the website. The third is the paper by [56], which examines the relationships between e-servicescape and trust; trust and E-WOM; and trust and customer loyalty. Results show that e-servicescape is “positively related to trust”; consistent with previous studies [8,34,57], trust is positively associated with E-WOM and customer loyalty. Moreover, trust affects E-WOM behavioral intentions.

Response

No specific papers have been allocated to this sub-theme. This is a result of the way in which papers have been classified. In order to reduce complexity, each paper has been indeed allocated to a single theme, according to the criteria previously identified. Therefore, although some—however still modest—modifications have been proposed over the years relating to this dimension (e.g., [58]), they do not strongly emerge from this analysis, as the corresponding papers have contributed more to the advancements of other S–O–R dimensions.

Moderators in the S–O and O–S junctions

A new interest is arising in the variables able to moderate the S–O and O–R junctions of the S–O–R model.
Ref. [59], for example, hypothesizes the moderating effect of one personal characteristic (product involvement) in the S–O junction, confirming that low task-relevant cues attract customers with a low level of product involvement, while customers with a high level of involvement can be attracted by more detailed product and service information.
Strong interest is growing in relation to the moderating role of gender. In the already analysed paper by [47], this variable has been introduced as moderator. Ref. [60] takes a step further as they use the selectivity hypothesis to interpret gender differences. According to their results, if a website must target men, it should be enriched with low task-relevant cues; if a website must target women, it should mix both low task and high task-relevant cues, and great effort should be devoted in increasing the richness and quality of the information.

5.1.2. Emerging Trends

In this sub-cluster, those papers that explain the most relevant developments in the e-servicescape literature are grouped. Accordingly, three sub-themes can be identified: one refers to the analysis of the culture’s influence on online customers’ behaviour; one refers to the atmospherics of 3D virtual reality stores; one refers to the combination of online and offline environments.
Regarding the first sub-theme, surprisingly, in the dataset only few papers develop cross-cultural research. The paper by [61] compares the online behaviour of Chinese and American customers adopting [62]’s classification of collectivism and individualism. Specifically, their results show that “culture does affect the ways in which American and Chinese online customers respond to atmospheric cues” (pp. 810–811). These pioneering results clearly show that the possibility of creating “a website that fits all” is very unlikely: In a collectivist socio-cultural context, websites should be planned and structured in order to stimulate arousal while the same websites can have negative effects on customers’ behaviour in an individualistic context. A new perspective is proposed by [63,64], which inverts the S–O–R model and tests it in Chinese and Canadian cultures; results from the analysis show that in an individualistic socio-economic culture (Canada), the most relevant emotion is that of pleasure, while in a collectivistic society (China), such a role is played by dominance. Moreover, according to Hofstede’s model, the impact of low task-relevant cues on the attitude towards the website and the consequent level of involvement is stronger for the Chinese than for the Canadians.
Relating to the second sub-theme, two papers in the dataset, [65,66], compare the atmospherics of traditional stores both to 2D and 3D virtual stores; both the studies point out that 2D online stores seem to be more different from traditional stores if compared to 3D ones. These two papers develop a taxonomy for the so-called “virtual store atmospherics” for the first time in the literature. Recently, a work on immersive virtual convenience store by [66] has been published and, interestingly, results show that participants continue to exhibit realistic shopper behaviours making such stores a cost-effective alternative to other methods for measuring consumer behaviour.
Regarding the third sub-theme, the first paper to use the same survey (with minor adjustments) for evaluating the same brand’s online and offline stores is that by [67]. Results show that emotions and loyalty are positively influenced by the graphic layout in the case of the offline store; on the contrary, no significant relationship has been tested in the online one. These findings underline how different the two environments are for the customers and how difficult it is for managers to transfer a model developed for one context to another context. Recently, ref. [36] shows that “individuals exposed to a virtual-reality-based retail environment perceive higher levels of presence than those exposed to a more traditional, physical store environment”.

5.2. Theme 2—Flow Theory

Here clustered are those papers implementing the flow theory to understand online consumer behaviour.
By analysing the papers included in our dataset, it emerges that, although several studies adopting this theory have been published over the years (e.g., [68]), still few are those published in management journals. Among them, the paper by [27] contributes to the literature by analysing how flow elements affect “pathological Internet use” (PIU). According to the scholars, “if a state of flow serves as a trigger or precursor of compulsive behaviour, marketers who attempt to induce online flow may also have an obligation to try to avoid socially negative consequences for consumers” (p. 310). Their results show that developing hedonic website value by facilitating escaping elements of flow does not lead to increased online sales that are of interest to marketers, but it could result in PIU. In addition, they proved that there is a positive connection between functional flow components and online purchasing behaviour. Finally, ref. [69]’s results show that the flow experience on B&B websites is more positively influenced by hedonic motivations than utilitarian ones.

5.3. Theme 3—TAM Model

Here clustered are those papers which combine information systems and consumer behaviour.
The analysis of the selected papers applying this theory shows that results generally support the significant correlation between the atmospherics of the website and online customers’ purchasing behaviour as well as the positive relationship between PEOU and PU. In line with this, for example, ref. [33] shows that PEOU affects customers’ attitude directly and indirectly (through PU) toward online shopping. Worth mentioning is also the paper by [70] which, in line with the theory, verifies that enjoyment can play a key role in affecting attitudes. Interestingly, ref. [37] adds four exogenous factors, namely, “perceived enjoyment”, “perceived risk”, “price consciousness” and “web atmospherics” to the existing TAM in order to increase its explanatory power and better predict online luxury goods consumption behavior. Specifically, the author hypothesizes that web atmospherics moderate the effect of attitude on online luxury purchase intention and the empirical research support such a hypothesis.

5.4. Theme 4—Convergences

In this theme, the first attempts of cross-fertilization between at least two different and separate research communities have been identified. Such cross-fertilization mainly occurs between those papers that apply the S–O–R model to analyze the impact of the online servicescape on customers’ behaviour and those that apply the flow framework for the same scope. In this regard, a very cited paper is that by [26] which, as the authors declare, for the first time, “translates recent research on flow and the Internet into the S–O–R model” (p. 319). Similarly, and more recently, ref. [71] develops a theoretical model in which the typical elements of the virtual servicescape are combined with the flow concept, highlighting that more studies on this possible overlap are definitely needed.

6. Discussion and Conclusion

The main aim of the paper was to systematically analyse the effects of the online environment on customers’ behaviour in order to offer a first, comprehensive state-of-the-art of this research.
Accordingly, the systematic literature review method has been adopted, on the basis of which 105 papers were considered eligible to be included in the final dataset.
The in-depth analysis of the 105 papers according to the adopted theoretical approach has shown that, undoubtedly, the S–O–R approach is the most used by scholars to deepen the effect of the e-servicescape on customers’ behaviour and that the traditional S–O–R model has been slightly modified by scholars in order to be suitable to fit with the peculiarities of the online setting. In Figure 3, the most intriguing advancements introduced for each variable of the S–O–R model are highlighted. What follows is a deep comment on the figure in order to better specify the possible future research avenues.
Regarding the stimuli, “classical” cues are generally taken into consideration (e.g., navigation, colours, graphics, music, product presentation, security), forgetting the opportunities new technologies have recently offered and that are likely to be implemented in the near future, such as online scent and online taste, flash motion pictures/videos, and interactive avatars, which can enhance customers’ experience (see ref. [72]). Even the interactivity of the website with blogs and social media is still under-researched, and no papers have yet considered the interaction with other communication methods (e.g., smartphones). Moreover, while the review of the literature brings to light that the starting point in all the papers is that the e-servicescape cues can positively affect customers’ emotion and cognition, results also show that no empirical research on the negative effect has yet been published. Questions such as: “What happens in the case of an overuse or negative use of some cues?” still have to be answered by scholars.
With regard to the organism, several advancements can be registered. Worth mentioning are, for example, the (still few) attempts to consider the “dominance” dimension, that has been neglected in the physical servicescape studies but transpires to be important in the e-servicescape, as it reflects the level of control over the shopping situation. However, if scholars agree on the possibilities to use such a dimension, a question needs to be answered: how can previous results that do not consider dominance and its possible influence on pleasure and arousal and customers’ behaviour be interpreted? Moreover, if the PAD model continues to be used, new insights able to overtake the current criticism related to the fact that it is too narrow in its internal states and thus unable to capture the overall effect of site atmosphere [10], must be implemented. One possibility is, for example, to consider the three PAD dimensions as a multidimensional construct; according to [73], indeed, arousal could be considered as a broader concept, including energetic and tense forms of it. Interestingly, by analysing the selected papers, attempts to use different scales for measuring emotions, at least in theory more effective than the PAD as they offer a richer assessment of emotional responses (e.g., [53,74,75]), were observed. Stemming from these pioneering studies, future research should consider new emotions, such as interest, surprise, joy, delight, frustration and disgust, in order to propose an alternative to the PAD model as well as better testing the effect of dominance and/or better explaining the PAD model (e.g., [76]).
With regard to the responses, very few papers analyse the impact of emotions on e-customers’ time and money spent on a specific website, which deserves future empirical research. Moreover, what is surprising is the scant attention given to social interaction considerations. For example, cognitive technologies have not been considered by scholars yet, opening up a research gap that urgently needs to be filled, in order to have academia aligned with practice.
Some scholars have also expanded the S-O-R model by including moderators in the S-O junction as well as the O-R junction. Although they are still used in a small number of papers, their results show how important it is to target the right customers with the right website. What emerges from these studies is the strong need to customize the websites according to, for example, the customers’ age, gender, task, and involvement. As these are the first attempts in this direction, future research should continue using moderators, taking into consideration, for example, age cohort effects, customers’ psychological traits, different product categories, different situational involvement (e.g., experiential and utilitarian orientations), the presence of a physical store, customer familiarity with the e-servicescape, cultural background, and the online retail reputation.
After having focused the attention on the S–O–R framework, the second part of this conclusion deepens the more general issues that have emerged in this research area and are related to the methodology employed by scholars, which can delineate future research methods.
A first issue deals with the website(s) used for research. A debate is still ongoing about the convenience of using mock vs. real websites. The positions are, indeed, divergent. According to those scholars who use real website(s), by using mock websites, with a number of disabled functions, limited product assortment and conducting the experiment in a laboratory, the reality of the virtual purchasing is shrunk. Conversely, according to those scholars who use mock website (s), a laboratory experimental design allows the researchers to manipulate the stimuli, to select the right ones, and to eliminate distorting effects, such as those from prior experience, from brand awareness and reputation, etc. Comparisons between results by using mock and real websites could probably solve such a dilemma.
A second issue concerns the type of analysis employed. Interestingly, no papers use a longitudinal approach. Although difficult, such an approach could allow scholars to trace the evolution and adaptation of customer behaviour when changes are introduced to the website. Moreover, considerations can emerge by analysing the few papers that compare the offline and online settings of the same company. Future research should work to understand if and how the two settings influence each other in shaping expectations, forming emotions, and influencing behaviours (see ref. [77,78]).
Other considerations emerge, finally, by analysing the first empirical attempts of cross-fertilization between the different research communities. Future research in this direction could help to improve the understanding of customers’ behaviours in the online setting.
Regarding the limitations of this paper, they generally are ascribable to SLRs (e.g., ref. [18]). Therefore, the first limit is related to the databases chosen for the analysis (Scopus, WoS, and EBSCO) as they could not include all the management abstracts dealing with the investigated issue. The second limit is related to (i) the keywords and (ii) the criteria employed to select the papers, which have led the authors to identify a final dataset that other keywords and criteria may not have.
Despite these limitations, the paper’s findings can be useful both for researchers and practitioners. Marketers and designers should, on the one hand, work hard to “tailor” the websites according to the characteristics their customers have and, on the other hand, to integrate off-line and on-line communication. Scholars should start from this relevant basis to foster those new and emerging insights that currently are ready to be developed.

Author Contributions

Introduction, all the authors; Theoretical Underpinnings, M.M.; Method and Review Framework, A.K.; Research Results, P.S.; Analysis of the Literature, S.P.; Discussion and Conclusion, Michela Mari. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Statista. Retail e-Commerce Sales Worldwide from 2014 to 2025 (in Billion U.S. Dollars). 2022. Available online: https://www.statista.com/statistics/379046/worldwide-retail-e-commerce-sales/ (accessed on 14 January 2022).
  2. Hamed, S.; El-Bassiouny, N.; Ternès, A. Hospital servicescape design for inpatient wellbeing. Serv. Mark. Q. 2019, 40, 1–32. [Google Scholar] [CrossRef]
  3. Siguaw, J.A.; Mai, E.; Wagner, J.A. Expanding servicescape dimensions with safety: An exploratory study. Serv. Mark. Q. 2019, 40, 123–140. [Google Scholar] [CrossRef]
  4. Tinnilä, M. A classification of service facilities, servicescapes and service factories. Int. J. Serv. Oper. Manag. 2012, 11, 267–291. [Google Scholar] [CrossRef]
  5. Shobeiri, S.; Mazaheri, E.; Laroche, M. Improving customer website involvement through experiential marketing. Serv. Ind. J. 2014, 34, 885–900. [Google Scholar] [CrossRef]
  6. Kotler, P. Atmospherics as a marketing tool. J. Retail. 1973, 49, 48–64. [Google Scholar]
  7. Bitner, M.J. Servicescapes: The impact of physical surroundings on customers and employees. J. Mark. 1992, 56, 57–71. [Google Scholar] [CrossRef]
  8. Harris, L.C.; Goode, M.M.H. Online servicescapes, trust, and purchase intentions. J. Serv. Mark. 2010, 24, 230–243. [Google Scholar] [CrossRef]
  9. Mehrabian, A.; Russell, J.A. An Approach to Environmental Psychology; The MIT Press: Cambridge, MA, USA, 1974. [Google Scholar]
  10. Eroglu, S.A.; Machleit, K.A.; Davis, L.M. Atmospheric qualities of online retailing: A conceptual model and implications. J. Bus. Res. 2001, 54, 177–184. [Google Scholar] [CrossRef]
  11. Eroglu, S.A.; Machleit, K.A.; Davis, L.M. Empirical testing of a model of online store atmospherics and shopper responses. Psychol. Mark. 2003, 20, 139–150. [Google Scholar] [CrossRef]
  12. Csikszentmihalyi, M. Play and intrinsic rewards. J. Humanist. Psychol. 1975, 15, 41–63. [Google Scholar]
  13. Hoffman, D.L.; Novak, T.P. Marketing in hypermedia computer-mediated environments: Conceptual foundations. J. Mark. 1996, 60, 50–68. [Google Scholar] [CrossRef]
  14. Novak, T.P.; Hoffman, D.L.; Duhachek, A. The influence of goal-directed and experiential activities on online flow experiences. J. Consum. Psychol. 2003, 13, 3–16. [Google Scholar] [CrossRef]
  15. Venkatesh, V.; Davis, F.D. A theoretical extension of the technology acceptance model: Four longitudinal field studies. Manag. Sci. 2000, 46, 186–204. [Google Scholar] [CrossRef] [Green Version]
  16. Venkatesh, V.; Bala, H. Technology acceptance model 3 and a research agenda on interventions. Decis. Sci. 2008, 39, 273–315. [Google Scholar] [CrossRef] [Green Version]
  17. Davis, F.D.; Bagozzi, R.P.; Warshaw, P.R. User acceptance of computer technology: A comparison of two theoretical models. Manage. Sci. 1989, 35, 982–1003. [Google Scholar] [CrossRef] [Green Version]
  18. Newbert, S.L. Empirical research on the resource-based view of the firm: An assessment and suggestions for future research. Strateg. Manag. J. 2007, 28, 121–146. [Google Scholar] [CrossRef]
  19. Mongeon, P.; Paul-Hus, A. The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics 2016, 106, 213–228. [Google Scholar] [CrossRef]
  20. Vieira, E.; Gomes, J. A comparison of Scopus and Web of Science for a typical university. Scientometrics 2009, 81, 587–600. [Google Scholar] [CrossRef]
  21. Verma, S.; Gustafsson, A. Investigating the emerging COVID-19 research trends in the field of business and management: A bibliometric analysis approach. J. Bus. Res. 2020, 118, 253–261. [Google Scholar] [CrossRef]
  22. Liñán, F.; Fayolle, A. A systematic literature review on entrepreneurial intentions: Citation, thematic analyses, and research agenda. Int. Entrep. Manag. J. 2015, 11, 907–933. [Google Scholar] [CrossRef]
  23. Mariani, M.; Borghi, M. Industry 4.0: A bibliometric review of its managerial intellectual structure and potential evolution in the service industries. Technol. Forecast. Soc. Change 2019, 149, 119752. [Google Scholar] [CrossRef]
  24. Zupic, I.; Čater, T. Bibliometric methods in management and organization. Organ. Res. Methods 2015, 18, 429–472. [Google Scholar] [CrossRef]
  25. Tranfield, D.; Denyer, D.; Smart, P. Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br. J. Manag. 2003, 14, 207–222. [Google Scholar] [CrossRef]
  26. Williams, R.; Dargel, M. From servicescape to ‘cyberscape’. Mark. Intell. Plan. 2004, 22, 310–320. [Google Scholar] [CrossRef]
  27. Bridges, E.; Florsheim, R. Hedonic and utilitarian shopping goals: The online experience. J. Bus. Res. 2008, 61, 309–314. [Google Scholar] [CrossRef]
  28. Hopkins, C.D.; Grove, S.J.; Raymond, M.A.; LaForge, M.C. Designing the e-servicescape: Implications for online retailers. J. Internet Commer. 2009, 8, 23–43. [Google Scholar] [CrossRef]
  29. Dholakia, R.R.; Zhao, M. Effects of online store attributes on customer satisfaction and repurchase intentions. Int. J. Retail. Distrib. Manag. 2010, 38, 482–496. [Google Scholar] [CrossRef]
  30. Brengman, M.; Karimov, F.P. The effect of web communities on consumers’ initial trust in B2C e-commerce websites. Manag. Res. Rev. 2012, 35, 791–817. [Google Scholar] [CrossRef]
  31. Brunner-Sperdin, A.; Scholl-Grissemann, U.S.; Stokburger-Sauer, N.E. The relevance of holistic website perception, how sense-making and exploration cues guide consumers’ emotions and behaviors. J. Bus. Res. 2014, 67, 2515–2522. [Google Scholar] [CrossRef]
  32. Hassouneh, D.; Brengman, M. Retailing in social virtual worlds: Developing a typology of virtual store atmospherics. J. Electron. Commer. Res. 2015, 16, 218–241. [Google Scholar]
  33. Lim, W.M. Antecedents and consequences of e-shopping: An integrated model. Internet Res. 2015, 25, 184–217. [Google Scholar] [CrossRef]
  34. Wu, W.Y.; Quyen, P.T.P.; Rivas, A.A.A. How e-servicescapes affect customer online shopping intention: The moderating effects of gender and online purchasing experience. Inf. Syst. e-Bus. Manag. 2017, 15, 689–715. [Google Scholar] [CrossRef]
  35. Connell, C.; Marciniak, R.; Carey, L.I.; McColl, J. Customer engagement with websites: A transactional retail perspective. Eur. J. Mark. 2019, 53, 1882–1904. [Google Scholar] [CrossRef]
  36. Pizzi, G.; Vannucci, V.; Aiello, G. Branding in the time of virtual reality: Are virtual store brand perceptions real? J. Bus. Res. 2020, 119, 502–510. [Google Scholar] [CrossRef]
  37. Jain, S. Examining the moderating role of perceived risk and web atmospherics in online luxury purchase intention. J. Fash. Mark. Manag. 2021, 25, 585–605. [Google Scholar] [CrossRef]
  38. Kim, M. Conceptualization of e-servicescapes in the fitness applications and wearable devices context: Multi-dimensions, consumer satisfaction, and behavioral intention. J. Retail. Consum. Serv. 2021, 61, 102562. [Google Scholar] [CrossRef]
  39. Krasonikolakis, I.; Vrechopoulos, A.; Pouloudi, A.; Dimitriadis, S. Store layout effects on consumer behavior in 3D online stores. Eur. J. Mark. 2018, 52, 1223–1256. [Google Scholar] [CrossRef]
  40. Kim, J.; Lennon, S.J. Effects of reputation and website quality on online consumers’ emotion, perceived risk and purchase intention: Based on the stimulus-organism-response model. J. Res. Interact. Mark. 2013, 7, 33–56. [Google Scholar] [CrossRef]
  41. Manganari, E.E.; Siomkos, G.J.; Rigopoulou, I.D.; Vrechopoulos, A.P. Virtual store layout effects on consumer behaviour: Applying an environmental psychology approach in the online travel industry. Internet Res. 2011, 21, 326–346. [Google Scholar] [CrossRef] [Green Version]
  42. Martínez-Navarro, J.; Bigné, E.; Guixeres, J.; Alcañiz, M.; Torrecilla, C. The influence of virtual reality in e-commerce. J. Bus. Res. 2019, 100, 475–482. [Google Scholar] [CrossRef]
  43. Roberts, J.; Grassi, A. A review of studies on virtual layout and atmospherics-potential applications to the fashion industry. Int. Rev. Retail. Distrib. Consum. Res. 2021, 31, 432–456. [Google Scholar] [CrossRef]
  44. Wu, C.S.; Cheng, F.F.; Yen, D.C. The atmospheric factors of online storefront environment design: An empirical experiment in Taiwan. Inf. Manag. 2008, 4, 493–498. [Google Scholar] [CrossRef]
  45. Mari, M.; Poggesi, S. Servicescape cues and customer behavior: A systematic literature review and research agenda. Serv. Ind. J. 2013, 33, 171–199. [Google Scholar] [CrossRef]
  46. Jayawardhena, C.; Wright, L.T. An empirical investigation into e-shopping excitement: Antecedents and effects. Eur. J. Mark. 2009, 43, 1171–1187. [Google Scholar] [CrossRef] [Green Version]
  47. Loureiro, S.M.C.; Ribeiro, L. Virtual atmosphere: The effect of pleasure, arousal, and delight on word-of-mouth. J. Promot. Manag. 2014, 20, 452–469. [Google Scholar] [CrossRef]
  48. Hsieh, J.K.; Hsieh, Y.C.; Chiu, H.C.; Yang, Y.R. Customer response to web site atmospherics: Task-relevant cues, situational involvement and PAD. J. Interact. Mark. 2014, 28, 225–236. [Google Scholar] [CrossRef]
  49. Kim, J.H.; Kim, M.; Lennon, S.J. Effects of web site atmospherics on consumer responses: Music and product presentation. Direct Mark. Int. J. 2009, 3, 4–19. [Google Scholar] [CrossRef]
  50. Park, J.; Stoel, L.; Lennon, S.J. Cognitive, affective and conative responses to visual simulation: The effects of rotation in online product presentation. J. Consum. Behav. Int. Res. Rev. 2008, 7, 72–87. [Google Scholar] [CrossRef]
  51. Izard, C.E.; Bartlett, E.S.; Marshall, A.G. Patterns of Emotions; Academic Press: New York, NY, USA, 1972. [Google Scholar]
  52. Izard, C.E. Human Emotions; Plenum: New York, NY, USA, 1977. [Google Scholar]
  53. Éthier, J.; Hadaya, P.; Talbot, J.; Cadieux, J. B2C web site quality and emotions during online shopping episodes: An empirical study. Inf. Manag. 2006, 43, 627–639. [Google Scholar] [CrossRef]
  54. Roseman, I.J. Appraisal determinants of emotions: Constructing a more accurate and comprehensive theory. Cogn. Emot. 1996, 10, 241–278. [Google Scholar] [CrossRef]
  55. Zhu, B.; Kowatthanakul, S.; Satanasavapak, P. Generation Y consumer online repurchase intention in Bangkok: Based on Stimulus-Organism-Response (SOR) model. Int. J. Retail. Distrib. Manag. 2019, 48, 53–69. [Google Scholar] [CrossRef]
  56. Tran, G.A.; Strutton, D. Comparing email and SNS users: Investigating e-servicescape, customer reviews, trust, loyalty and E-WOM. J. Retail. Consum. Serv. 2020, 53, 101782. [Google Scholar] [CrossRef]
  57. Tran, G.A.; Strutton, D.; Taylor, D.G. Do microblog postings influence consumer perceptions of retailers’e-servicescapes? Manag. Res. Rev. 2012, 35, 818–836. [Google Scholar] [CrossRef]
  58. Loureiro, S.M.C.; Roschk, H. Differential effects of atmospheric cues on emotions and loyalty intention with respect to age under online/offline environment. J. Retail. Consum. Serv. 2014, 21, 211–219. [Google Scholar] [CrossRef]
  59. Ha, Y.; Lennon, S.J. Effects of site design on consumer emotions: Role of product involvement. J. Res. Interact. Mark. 2010, 4, 80–96. [Google Scholar] [CrossRef]
  60. Tsichla, E.; Hatzithomas, L.; Boutsouki, C. Gender differences in the interpretation of web atmospherics: A selectivity hypothesis approach. J. Mark. Commun. 2016, 22, 563–586. [Google Scholar] [CrossRef]
  61. Davis, L.; Wang, S.; Lindridge, A. Culture influences on emotional responses to on-line store atmospheric cues. J. Bus. Res. 2008, 61, 806–812. [Google Scholar] [CrossRef]
  62. Hofstede, G. Cultural dimensions in management and planning. Asia Pac. J. Manag. 1984, 1, 81–99. [Google Scholar] [CrossRef]
  63. Mazaheri, E.; Richard, M.O.; Laroche, M. Online consumer behavior: Comparing Canadian and Chinese website visitors. J. Bus. Res. 2011, 64, 958–965. [Google Scholar] [CrossRef] [Green Version]
  64. Mazaheri, E.; Richard, M.O.; Laroche, M.; Ueltschy, L.C. The influence of culture, emotions, intangibility, and atmospheric cues on online behavior. J. Bus. Res. 2014, 67, 253–259. [Google Scholar] [CrossRef]
  65. Krasonikolakis, I.G.; Vrechopoulos, A.; Pouloudi, A. Defining, applying and customizing store atmosphere in virtual reality commerce: Back to basics? Int. J. E-Serv. Mob. Appl. 2011, 3, 59–72. [Google Scholar] [CrossRef] [Green Version]
  66. Schnack, A.; Wright, M.J.; Holdershaw, J.L. An exploratory investigation of shopper behaviour in an immersive virtual reality store. J. Consum. Behav. 2020, 19, 182–195. [Google Scholar] [CrossRef]
  67. Loureiro, S.M.C.; Bilro, R.G.; Japutra, A. The effect of consumer-generated media stimuli on emotions and consumer brand engagement. J. Prod. Brand. Manag. 2019, 29, 387–408. [Google Scholar] [CrossRef]
  68. Saxena, A.; Khurana, A.; Kothari, D.P.; Jain, S.K. Development of a “Flow Process Scale” to measure flow among web users. J. Internet Commer. 2004, 2, 55–86. [Google Scholar] [CrossRef]
  69. Jeon, M.M.; Lee, S.; Jeong, M. e-Social influence and customers’ behavioral intentions on a bed and breakfast website. J. Hosp. Mark. Manag. 2018, 27, 366–385. [Google Scholar] [CrossRef]
  70. Childers, L.; Carr, C.L.; Peck, J.; Carson, S. Hedonic and utilitarian motivations for online retail shopping behavior. J. Retail. 2001, 77, 511–535. [Google Scholar] [CrossRef]
  71. Lee, S.; Jeong, M. Effects of e-servicescape on consumers’ flow experiences. J. Hosp. Tour. Technol. 2012, 3, 47–59. [Google Scholar] [CrossRef]
  72. Petit, O.; Velasco, C.; Spence, C. Digital sensory marketing: Integrating new technologies into multisensory online experience. J. Interact. Mark. 2019, 45, 42–61. [Google Scholar] [CrossRef] [Green Version]
  73. Thayer, R.E. Toward a psychological theory of multidimensional activation (arousal). Motiv. Emot. 1978, 2, 1–34. [Google Scholar] [CrossRef]
  74. Wang, H.C.; Pallister, J.G.; Foxall, G.R. Innovativeness and involvement as determinants of website loyalty: II. Determinants of consumer loyalty in B2C e-commerce. Technovation 2006, 26, 1366–1373. [Google Scholar] [CrossRef]
  75. Wang, Y.J.; Hernandez, M.D.; Minor, M.S. Web aesthetics effects on perceived online service quality and satisfaction in an e-tail environment: The moderating role of purchase task. J. Bus. Res. 2010, 63, 935–942. [Google Scholar] [CrossRef]
  76. Ball, J.; Barnes, D.C. Delight and the grateful customer: Beyond joy and surprise. J. Serv. Theory Pract. 2017, 27, 250–269. [Google Scholar] [CrossRef]
  77. Mari, M.; Poggesi, S. Facility management: Current trends and future perspectives. Int. J. Glob. Small Bus. 2014, 6, 177–192. [Google Scholar] [CrossRef]
  78. Schilleci, P. Exploring the impact of the physical work environment on service employees: An analysis of literature. J. Facil. Manag. forthcoming. [CrossRef]
Sustainability 14 04131 g001 550
Figure 1. SLR steps.
Figure 1. SLR steps.
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Sustainability 14 04131 g002 550
Figure 2. Distribution of papers per year.
Figure 2. Distribution of papers per year.
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Figure 3. Advancements in the application of the S–O–R model to the e-servicescape.
Figure 3. Advancements in the application of the S–O–R model to the e-servicescape.
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Table
Table 1. The search options for Scopus, Web of Science, and Ebsco.
Table 1. The search options for Scopus, Web of Science, and Ebsco.
DatabaseCriteriaResults
ScopusSearch in: Article Title, Abstract, Keywords2003
Document type: Article; Review
Subject area: Business, management and accounting
Data range: all years to 2021
Language: English
Web of Science (WoS)Search in: Topic781
Document type: Article, Review, Editorial Materials
Subject area: Business; management; operations research management science
Data range: all years to 2021
Language: English
EbscoSearch in: Abstract2656
Document type: Peer reviewed journal articles
Data range: all years to 2021
Language: English
Source: Own elaboration.
Table
Table 2. Journals most involved in the conversation.
Table 2. Journals most involved in the conversation.
JournalNo. of Published Papers
Journal of Business Research15
Journal of Retailing & Consumer Services8
European Journal of Marketing6
International Journal of Retail & Distribution Management6
Internet Research4
Information & Management3
Journal of Consumer Behaviour3
Journal of Fashion Marketing & Management3
Journal of Internet Commerce3
Journal of Service Research3
Source: Own elaboration.
Table
Table 3. A sample of the selected papers.
Table 3. A sample of the selected papers.
ThemeAuthor(s)Year of PublicationJournalKeywordsResearch Question(s)Methodological ApproachSampleType of Sample
1Eroglu, S.A.; Machleit, K.A.; Davis, L.M. [10]2003Psychology & Marketingn.a.The study presents an empirical verification of the effect of online atmospherics on shopper outcomes and responses.SEM/confirmatory factor analysis328students
4Williams, R.; Dargel, M. [26]2004Marketing Intelligence & PlanningInternet, Electronic commerce, Worldwide webThe aim of this paper is to consider how the “cyberscape” may be designed and planned in such a way as to induce positive approach behaviours—prolonged usage, intention to return, and recommendation to others, the latter being perhaps the most important driver of traffic to commercial websites. n.a.
2Bridges, E.; Florsheim, R. [27]2008Journal of Business Research Online buying behavior, Online flow, Pathological Internet useThe authors address the relationship between various elements of flow, the online experience, and purchasing online. Further, they examine what hedonic elements can accomplish from the marketer’s viewpoint.multiple regression337students
1Hopkins, C.D.; Grove, S.J.; Raymond, M.A.; LaForge, M.C. [28]2009Journal of Internet CommerceAmbient conditions, Attitude toward Web site, e-servicescape, Purchase intentions, Spatial layout/functionalityThe purposes are to (1) develop a theory-driven framework to conceptualize the Web site as an e-servicescape, (2) discern the degree to which the dimensions of an e-servicescape impact effective Web site design, and (3) identify the relative importance of the e-servicescape dimensions with respect to customers’ online experience.SEM216web surfers
1Harris, L.C.; Goode, M.M.H. [8]2010Journal of Services MarketingInternet, Service levels, Trust, Purchasing, RetailingThis study aims to provide insights into how consumers’ interpretations of e-servicescape affect their subsequent evaluations of web site trustworthiness and ultimately their intentions to repurchase.SEM/confirmatory factor analysis257web surfers
1Dholakia, R.R.; Zhao, M. [29]2010International Journal of Retail & Distribution ManagementInternet shopping, Customer satisfaction, Consumer behaviour, Repeat buyingThe study is an attempt to shed additional insights into the relationships between website attributes and their effects on customer satisfaction and loyalty. regression1079 (in 2003) and 1242 (in 2004)web surfers
1Brengman, M.; Karimov, F.P. [30]2012Management Research ReviewElectronic commerce, Consumer behaviour, Trust, Social media, Internet, Initial online trust, Social networks, Corporate blog, B2C e-commerceThe objective of the study is to investigate whether the mere integration of web communities, such as an SNS and/or a corporate blog in the e-tail interface can affect consumers’ initial trust towards an unfamiliar e-vendor and subsequent purchase intentions.MANCOVA and ANCOVA226students
1Brunner-Sperdin, A.; Scholl-Grissemann, U.S.; Stokburger-Sauer, N.E. [31]2014Journal of Business ResearchWebsite perception, Gestalt approach, Sense-making, Exploration, Emotions, Consumer responsesThe study aims to develops and tests a conceptual model that accounts for consumers’ holistic perception of websites. Moreover, it aims to validate the web-Gestalt model and to assess whether a website’s sense-making potential and exploration potential lead to emotional responses, such as pleasure and arousal, which consequently affect satisfaction and loyalty intentions to the website.SEM/confirmatory factor analysis191 (study 1) and 213 (study 2)students (study 1) and customers who had previously booked a hotel on the website (study 2)
1Hassouneh D.; Brengman L. [32]2015Journal of Electronic Commerce ResearchMetaverse Retailing, Atmospherics, Content Analysis, Second Life, Store DesignThis paper aims to set a first step towards understanding virtual store design principles by exploring current practices in terms of the application of store atmospherics in Social Virtual World stores and proposing a new typology for 3D virtual store atmospherics.content analysis27Second Life Stores
3Lim, W.M. [33]2015Internet ResearchConsumer behaviour, e-commerceThe objectives of this study were twofold: (1) to enhance understanding of the antecedents of e-shopping acceptance and usage behavior drawn from both IS and CB theoretical underpinnings; and (2) to subsequently test the significance of this model empirically and thus offer useful and practical implications for organizations wanting to venture successfully into e-shopping in terms of realizing and maintaining gains of site traffic and e-shopping transactions.SEM320e-shoppers
1Wu, W.Y.; Quyen, P.T.P.; Rivas, A.A.A. [34]2017Information Systems and e-Business Managemente-servicescapes, Website trustworthiness, Website attitude, Brand attitude, e-WOM intention, Purchase intentionThe study aims to contribute to the literature as follows: (1) by examining the nature of e-servicescapes and the e-servicescape dimensions from the view of Taiwanese consumers, and the effects that these dimensions have on the perceived trustworthiness of a website, customer responses to a website, brand evaluations, purchase intentions and e-WOM intentions. (2) By also examining the moderating effects of gender and online purchasing experience on the relationship between e-servicescape and internal responses.PLS-SEM290students
1Connell, C.; Marciniak, R.; Carey, L.I.; McColl, J. [35]2019European Journal of MarketingOnline consumer behaviour, Fashion, Online retailing, Customer engagement, Websites, Environmental psychologyThis study addresses three research areas: firstly, the question of how retail websites engage customers will be considered with a specific focus on identifying the environmental cues that stimulate Customer Engagement. Secondly, the nature of CE with websites will be established by identifying the relationships between specific environmental cues and CE dimensions. Finally, insight will be provided into the role of the website in a customer-brand engagement process.thematic analysis22over-55-year-old women who have browsed and bought fashion and fashion-related items online
1Pizzi, G.; Vannucci, V.; Aiello, G. [36]2020Journal of Business ResearchVirtual reality, Retailing, Presence, Shopping experience, Inattentional blindness, Patronage intentionThe purpose of the study is twofold: to observe whether higher or lower levels of inattentional blindness emerge for consumers who are exposed to the virtual versus physical store environment (RQ1). Second, whether being exposed to a virtual or physical retail store environment sequentially affects individuals’ perceptions of social presence, shopping experience, change in value perceptions, WOM referral intention, and patronage intention; and whether the lack of conscious recognition of the retail store brand significantly moderates this set of relationships (RQ2).SEM/confirmatory factor analysis200web surfers
3Jain, S. [37]2021Journal of Fashion Marketing and ManagementAttitude, India, Online luxury purchase intention, Perceived risk, Web atmospherics, Technology acceptance model (TAM)The prime objective of the study is to develop a conceptual framework based upon technology acceptance model (TAM), which integrates the role of key variables that influence consumers’ intention to purchase luxury fashion goods online. The second objective of the study is to understand the mediating role of attitude in the relationship between antecedent factors (perceived usefulness, perceived ease of use, perceived enjoyment and price consciousness) and online luxury purchase intention. Finally, it aims to measure the moderating effect of perceived risk and web atmospherics on the relationship between attitude and online luxury purchase intentions.SEM/confirmatory factor analysis and Hayes Process macro in SPSS250luxury fashion consumers
Source: own elaboration.
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Poggesi, S.; Mari, M.; Kamangar, A.; Schilleci, P. The Role of Virtual Environment in Online Retailing: State of the Art and Research Challenges. Sustainability 2022, 14, 4131. https://doi.org/10.3390/su14074131

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Poggesi S, Mari M, Kamangar A, Schilleci P. The Role of Virtual Environment in Online Retailing: State of the Art and Research Challenges. Sustainability. 2022; 14(7):4131. https://doi.org/10.3390/su14074131

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Poggesi, Sara, Michela Mari, Arash Kamangar, and Pinalba Schilleci. 2022. "The Role of Virtual Environment in Online Retailing: State of the Art and Research Challenges" Sustainability 14, no. 7: 4131. https://doi.org/10.3390/su14074131

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