Jean-Christophe Marvaud

Sergio Quevedo-Torres

Catherine Eckert

Claire Janoir

Fréderic Barbut

Virulence of new variant strains of Clostridium difficile producing only toxin A or binary toxin in the hamster model

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

INTRODUCTION

Clostridium difficile is a Gram positive anaerobic and spore-forming bacterium responsible of nosocomial digestive infections in most developed countries. The symptoms of C. difficile infections (CDI) range from mild self-limited diarrhea to life-threatening pseudomembranous colitis [START_REF] Vecchio | Clostridium difficile infection: an update on epidemiology, risk factors, and therapeutic options[END_REF].

The major virulence factors of C. difficile are two large protein toxins, that share the same structural features and the same mechanism of action, the glycosylation of the Rho and Ras proteins [START_REF] Aktories | Clostridium difficile Toxin Biology[END_REF][START_REF] Belyi | Bacterial toxin and effector glycosyltransferases[END_REF]. This leads to the disruption of the epithelial cell cytoskeleton and tight junctions between cells and the loss of epithelial integrity and more extensively tissue damage mainly in the colon. Despite their similarities in their sizes and modular structures, those two toxins do not recognize the same receptor for their binding (see review from Aktories [START_REF] Aktories | Clostridium difficile Toxin Biology[END_REF]).

Genes tcdA and tcdB coding for TcdA and TcdB, respectively, are part of a region of 19.6-kb named PaLoc for Pathogenicity Locus. The PaLoc also harbors 3 other genes, tcdR and tcdC, involved in the positive and negative transcriptional regulation of the toxin genes, respectively, and tcdE, which encodes a putative holin required for the efficient secretion of TcdA and TcdB [START_REF] Govind | Secretion of Clostridium difficile toxins A and B requires the holin-like protein TcdE[END_REF][START_REF] Martin-Verstraete | The Regulatory Networks That Control Clostridium difficile Toxin Synthesis[END_REF]. PaLoc is found mostly in the same genomic location and is replaced in non-toxigenic strains by a highly conserved 75/115 bp non-coding region [START_REF] Braun | Definition of the single integration site of the pathogenicity locus in Clostridium difficile[END_REF]. Further the genetic polymorphism found in the PaLoc can be explored by a PCR-restriction method called toxinotyping [START_REF] Rupnik | An Update on Clostridium difficile Toxinotyping[END_REF].

Most C. difficile clinical strains usually produce both toxins, but some strains only produce TcdB (strains A -B + ). These strains belong to different toxinotypes and the most frequent ones, (toxinotype VIII), are characterized by the presence within the PaLoc of a modified tcdA gene leading to a truncated non-active toxin A. They have been described worldwide and have caused large outbreaks across several Asian countries [START_REF] Kim | Clinical Characteristics and Treatment Outcomes of Clostridium difficile Infections by PCR Ribotype 017 and 018 Strains[END_REF]. In 2015, Janezic et al. described a new toxinotype strain (toxinotype XXXII) characterized by a lack of whole genes tcdA and tcdC and an atypical integration site of the PaLoc [START_REF] Janezic | A new type of toxin A-negative, toxin B-positive Clostridium difficile strain lacking a complete tcdA gene[END_REF]. More recently, a new variant strain A + B - strain, harboring tcdA but not tcdB [START_REF] Monot | Clostridium difficile: New Insights into the Evolution of the Pathogenicity Locus[END_REF], was isolated for the first time in humans and showed also different site of integration. The emergence of genetic variants of tcdA and tcdB genes raised the question of the role of TcdA and TcdB in C. difficile pathogenesis. The contribution of the two toxins to the disease has been evaluated through diverse in vitro or in vivo models. One of them, the hamster model, emerged because it mirrors many clinical aspects of human CDI, with hemorrhagic caecitis, and eventually death. Using this model and different mouse infection models, Lyras et al. [START_REF] Lyras | Toxin B is essential for virulence of Clostridium difficile[END_REF][START_REF] Carter | Defining the Roles of TcdA and TcdB in Localized Gastrointestinal Disease, Systemic Organ Damage, and the Host Response during Clostridium difficile Infections[END_REF] analyzed isogenic toxin mutants from two different C. difficile strains including JIR8094 a derivative of strain 630 strain 630 and demonstrated that the A + B -mutant was less virulent than both the parental A + B + and the A -B + mutant strains, whereas in studies performed by Kuehne et al. [START_REF] Kuehne | The role of toxin A and toxin B in Clostridium difficile infection[END_REF][START_REF] Kuehne | Importance of toxin A, toxin B, and CDT in virulence of an epidemic Clostridium difficile strain[END_REF] in the hamster model, the A + B -mutant from strains 630Δerm or R20291 were almost as virulent as the parental and the A -B + mutant strains. Despite this discrepancy, which has been putatively related to SNPs occurring between the two genetically close parental strains, these results suggest strongly that TcdB plays a major role in the occurrence of clinical signs.

A third toxin called binary toxin (CDT) is also produced by 23% of the toxigenic strains including the hypervirulent clones 027 and 078 [START_REF] Bauer | Clostridium difficile infection in Europe: a hospital-based survey[END_REF]. Briefly, the binary toxin of C. difficile targets the small G protein and its actin-specific ADP-ribosylating activity result in the disorganization of cytoskeleton of the cells (see review from Gerding [START_REF] Gerding | Clostridium difficile binary toxin CDT: Mechanism, epidemiology, and potential clinical importance[END_REF]). Although its precise role in the pathogenesis remains unclear, it is recognized that it could act synergistically with the TcdA and TcdB toxins. In particular, it was shown that CDT enhances the virulence of C. difficile in mice via the suppression of a protective host eosinophilic response [START_REF] Cowardin | The binary toxin CDT enhances Clostridium difficile virulence by suppressing protective colonic eosinophilia[END_REF]. It and embed bacterial cells, thereby largely increasing the adherence of C. difficile [START_REF] Schwan | Clostridium difficile toxin CDT induces formation of microtubule-based protrusions and increases adherence of bacteria[END_REF].

Role of the different toxins has already been evaluated by testing isogenic mutants of C. difficile in the hamster model. But to our knowledge, the virulence of clinical strains producing only the toxin A or the binary toxin has never been tested in this model. Therefore the objective of this study was to test the ability of two clinical variant strains, putatively involved in human infections, to reproduce the symptomatology in hamsters.

RESULTS

Typing and antimicrobial susceptibility of the C. difficile strains

Following MLST determination, the five C. difficile strains were classified in five different sequence types (STs), ST 11 (clade 5), ST 1 (clade 2) and ST15 (clade 1) for CD13-073 (A -B - CDT + ), CD13-125 (A + B + CDT + ) and CD15-159 (NT) respectively, and two new ST for RA09-070 (A + B -CDT -) and CD10-165 (A -B + CDT + ) (Table 1).

The alleles profile of the new ST of the strain RA09-070 (A + B -CDT - C. difficile CD10-165 (A -B + CDT + ) and RA09-070 (A + B -CDT -) were susceptible to all antibiotics tested (erythromycin, clindamycin, moxifloxacin, metronidazole, vancomycin). C. difficile CD13-073 (A -B -CDT + ) was susceptible to the same antibiotics except moxifloxacin (MIC=12 mg/L). C. difficile CD13-125 (A + B + CDT + ) and CD15-159 (NT) were susceptible to metronidazole and vancomycin but highly resistant to erythromycin (MIC>256 mg/L). C. difficile CD15-159 (NT) was also resistant to clindamycin (MIC>256 mg/L) and CD13-125 (A + B + CDT + ) was resistant to moxifloxacin (MIC>32 mg/L).

The colonization rates of the hamsters is similar for the five C. difficile strains

Clindamycin-pretreated hamsters were orogastrically challenged with spores of each C. difficile strain. We evaluated the degree of colonization by the five C. difficile strains by numeration of both vegetative forms and spores in fecal pellets. At day 2 post-infection, the level of colonization, evaluated by the fecal clearance of the bacteria (in CFU/g feces), was not significantly different for the five strains: 6.1 10 6 for RA09-070 (A + B -CDT -) to 1.5 10 7 for CD13-073 (A -B -CDT + ). In hamsters infected with RA09-070 (A + B -CDT -), CD13-073 (A -B - CDT + ) and CD15-159 (NT), the C. difficile colonization level remained stable, above 10 6 CFU/g feces at day 14 when the hamsters were euthanized (Fig. 1).

Clinical monitoring of hamsters

All hamsters given CD13-125 (A + B + CDT + ) or CD10-165 (A -B + CDT + ) died within 96 h, mostly between 48 h and 72 h, and were subject to wet tail, diarrhea, and loss of weight. In contrast, all hamsters given RA09-070 (A + B -CDT -) or CD15-159 (NT) were still alive at day 14 (Fig. 2).

No differences were found in term of clinical observations between the non-toxigenic strain and the RA09-070 (A + B -CDT -) strain; in particular, an increase of about 10% of weight was observed at the end of the experiment for the hamsters infected with these 2 strains (see Table S1). But hamsters infected with strain CD13-073 (A -B -CDT + ) presented two phenotypes.

Whereas 6 out of 7 hamsters presented no clinical signs and survived until the end of the assay, one died at day 4 without clinical signs prior to death.

Histological changes

In order to assess the impact on cecal histology of the five C. difficile strains, sections of cecal tissues were sampled at the time of death for all hamsters. Strains CD10-165 (A -B + CDT + ) and CD13-125 (A + B + CDT + ) produced very similar major histological changes and representative histopathology in the cecum is shown in Fig. 3. There was an acute haemorrhagic congestion resulting in edema within the submucosa and the lamina propria, a neutrophil infiltration, an acute hyperplasia and finally we found an extensive epithelial damage with disruption of the villi (mean histological score= 10.63 and 10.29 for strains CD10-165 (A -B + CDT + ) and CD13-125 (A + B + CDT + ) respectively in Fig. 4).

As expected, hamsters infected with the non toxigenic strain presented an intact cecum (Fig. 3 and mean histological score of 0.14 in Fig. 4). In contrast, despite lack of mortality and characteristic clinical signs of CDI, neutrophilia infiltration was observed with an extensive hyperplasia for hamsters infected with RA09-070 (A + B -CDT -) (Fig. 3). Epithelial cell loss was sometimes present but unclotted red blood cells were rarely found. The mean histological score of 4.5 was significantly different (p<0.0001) compared to the score of the TcdB producers CD10-165 (A -B + CDT + ) and CD13-125 (A + B + CDT + ). Interestingly, the 6 of the 7 hamsters infected with the strain CD13-073 (A -B -CDT + ) that survived to the challenge presented little alteration of the cecum with essentially some neutrophilia infiltration and the mean histological score was significantly higher compared to the score of the non toxigenic strain (mean histological score= 1.1 and 0.3 respectively, p<0.05). The seventh (that died within 48h postinfection) presented an important inflammation and an acute hyperplasia with an individual histological score of 9 (Fig. 3 and4).

Discussion

C. difficile can produce three different toxins and it is established that human CDI is a multi-factor occurrence which depends of the C. difficile strain and host susceptibility. The purpose of this study was to assess the pathogenesis of new variant strains isolated from symptomatic patients in the hamster model [START_REF] Lyras | Toxin B is essential for virulence of Clostridium difficile[END_REF][START_REF] Kuehne | The role of toxin A and toxin B in Clostridium difficile infection[END_REF]. Our panel of strains included a strain producing only the binary toxin CDT, a strain producing only TcdA and, as controls for the validation of the model, a non-toxigenic strain, a hypervirulent strain which produced the three toxins TcdA, TcdB and CDT and a strain producing TcdB and CDT.

The validation of our model was assessed because clinical strains TcdB producing strains CD13-125 (A + B + CDT + ) and CD10-165 (A -B + CDT + ) induced similar clinical signs in hamsters, time to death from infection and severe histological damages, highlighting the fact that TcdB appears clearly sufficient to induce CDI in the hamster model. The pathogenicity of the two variants producing only one toxin, TcdA or CDT was however different. Therefore RA09-070 (A + B -CDT -) which was recently characterized as the first clinical strain producing TcdA without TcdB [START_REF] Monot | Clostridium difficile: New Insights into the Evolution of the Pathogenicity Locus[END_REF] was isolated from a patient with an antibioticassociated diarrhea who recovered after metronidazole treatment, strongly suggesting that C. difficile was implicated in the disease. The genome of the strain possesses no copy of the classical PaLoc but a gene coding tcdA within a PaLoc encompassing tcdR and a new putative CDS coding a complete domain related to the prophage BhlA/UviB located far from the usual integration site of the PaLoc in C. difficile. Also this strain does not harbor genes coding the binary toxin CDT.

Regarding its virulence in the hamster model, no mortality was found as well as absence of clinical signs, notably the absence of diarrhea, with this strain that caused diarrhea in a patient.

Challenge of hamsters with this strain showed however a kinetic of colonization identical to the four other strains used in this study indicating that its in vivo fitness was not implicated in the lack of the virulence of the strain. Those observations are consistent with previous study of Lyras et al. [START_REF] Lyras | Toxin B is essential for virulence of Clostridium difficile[END_REF] in which a tcdB toxin gene mutant of a strain JIR8094, a derivative of C. difficile strain 630, was not associated with mortality in the hamster model. However the same authors [START_REF] Carter | Defining the Roles of TcdA and TcdB in Localized Gastrointestinal Disease, Systemic Organ Damage, and the Host Response during Clostridium difficile Infections[END_REF] found lethality with a significant delay for an isogenic mutant A + B -of a Canadian epidemic strain (strain M7404). Other genetic factors could modulate the virulence of the strain, highlighting that the criteria of lethality in the hamster model for strain producing only TcdA should be used carefully. RA09-070 (A + B -CDT -) infection was associated to cecal histological damages but at a lower extent in comparison with the TcdB producing strains (whether or not strains produced TcdA or CDT), with significant neutrophil infiltration and hyperplasia, signs of inflammation. Batah et al. [START_REF] Batah | Clostridium difficile flagella induce a proinflammatory response in intestinal epithelium of mice in cooperation with toxins[END_REF] demonstrated in a mouse model that the two toxins of C. difficile strains 630 or R20291 act in synergy with the flagellin, the major component of the filament of the flagella of the bacteria to produce the strong pro-inflammatory response observed during the pathogenesis of C. difficile. As RA09-70 (A + B -CDT -) possesses the different regulons coding the proteins of the flagella (Genbank accession Number JPPA00000000), we suggest that TcdA and the flagellin of this strain are responsible of the inflammation observed in our model. The fact that a strain producing only TcdA is involved in a human CDI must be taken into account in term of diagnostic strategy. This new variant also illustrates the genetic heterogeneity of C. difficile and further studies must be done to explain its pathogenicity in humans in contrast to what is observed in hamsters.

Strain CD13-073 (A -B -CDT + ) is a C. difficile strain producing only CDT. The A -B - CDT + strains are classified mostly as toxinotype XI and are seldom isolated in human infection [START_REF] Eckert | Prevalence and pathogenicity of binary toxin-positive Clostridium difficile strains that do not produce toxins A and B[END_REF] [START_REF] Androga | Infection with Toxin A-Negative, Toxin B-Negative, Binary Toxin-Positive Clostridium difficile in a Young Patient with Ulcerative Colitis[END_REF]. However their prevalence in animals, as observed in diarrheic calves, is more important [START_REF] Schneeberg | Presence of Clostridium difficile PCR ribotype clusters related to 033, 078 and 045 in diarrhoeic calves in Germany[END_REF]. The strain was isolated from a 56-years old patient treated with imipenem and gentamicin for pneumonia. He developed a pseudomembranous colitis and after metronidazole treatment the clinical signs resolved. Using the hamster model, Geric et al found no mortality or symptoms with three different strains producing CDT only [START_REF] Geric | Binary toxin-producing, large clostridial toxinnegative Clostridium difficile strains are enterotoxic but do not cause disease in hamsters[END_REF]. In contrast CD13-073 (A -B - CDT + ) infection resulted in death for one animal out of seven with histological damages similar to those found with TcdB-producing strains, and was able to produce mild histological damages in the remaining surviving animals. Death of 3 hamsters out of 8 was also observed by Kuehne et al. [START_REF] Kuehne | Importance of toxin A, toxin B, and CDT in virulence of an epidemic Clostridium difficile strain[END_REF] with a mutant strain producing CDT only, and animals presented atypical symptoms of CDI with moderate clinical signs as wet tail. Variation of virulence of strains producing only CDT in the hamster model suggest that individual susceptibilities and/or presence of bacterial factors may modulate the effect of binary toxin and may further explain why these variants of C. difficile are rarely isolated in humans.

Overall, we found that a severe inflammation in the ceca of infected hamsters is correlated with mortality of the animals. Also our results confirmed, using clinical strains and not laboratory mutants, the major role of TcdB and a less important role of TcdA for C. difficile virulence in the hamster model. Several factors could explain this observation: degree of dysbiosis of the host, presence in the microbiota of other species of bacteria promoting the effect of the pathogen, role of the innate immunity…. This highlights the limitation of the animal model.

MATERIALS AND METHODS

C. difficile strains and spore preparation

Four toxigenic C. difficile clinical isolates CD13-125 (A + B + CDT + ), CD10-165 (A -B + CDT + ), RA09-070 (A + B -CDT -) and CD13-073 (A -B -CDT + ) were used in this study. One non-toxigenic C. difficile clinical isolate CD15-159 (A -B -CDT -or NT), isolated from a liver abscess in 2015, was added as a negative control (Table 1). Strain CD13-125 (A + B + CDT + ) belongs to the epidemic PCR-ribotype 027 and was isolated from severe CDI cases in Marseille in 2013.

Strain CD13-073 (A -B -CDT + ) belongs to the PCR-ribotype 288 and was isolated from a patient with pseudomembranous colitis, in Bordeaux in 2012. Strains RA09-070 (A + B -CDT -) and CD10-165 (A -B + CDT + ), isolated from patients suffering from AAD and PMC, respectively, were characterized by whole genome sequencing as reported elsewhere [START_REF] Monot | Clostridium difficile: New Insights into the Evolution of the Pathogenicity Locus[END_REF]. . The identification of the strains was confirmed using Matrix-assisted laser desorption ionization (Maldi) time-of-flight (Tof) mass spectrometry (Brucker) and the glutamate dehydrogenase (GDH) component of the C. diff Quik Chek Complete® assay (Abbot). Spores were prepared using the method described by Siani et al. [START_REF] Siani | Efficacy of "sporicidal" wipes against Clostridium difficile[END_REF]. Briefly, strains were plated on solid media Wilkins-Chalgren agar for 48 h at 37°C in an anaerobic chamber. Then, plates were incubated aerobically at room temperature for 5 days. The entire bacterial lawn was scraped off using a sterile swab and resuspended in 1 ml sterile water. To kill the vegetative cells, bacterial suspensions were mixed with ethanol (vol/vol) and incubated for 30 min at room temperature. Then, the suspension was centrifuged (3000 r/min., 20 min.) and the pellet was resuspended in 1 ml ethanol, sonicated 1 min, and washed in cold water three times. Spore stocks were stored at +4°C and were enumerated by plating on Wilkins-Chalgreen agar containing taurocholate 0,1%.

Typing

MLST was performed according to the scheme developed by Griffith et al. [START_REF] Griffiths | Multilocus Sequence Typing of Clostridium difficile[END_REF]. Briefly, seven housekeeping genes (adk, atpA, dxr, glyA, recA, sodA and tpi) were amplified by PCR and sequenced as previously described. The sequence type (ST) was determined as a combination of alleles identified by comparing sequences with sequences available in the C. difficile MLST database (http://pubmlst.org/cdifficile/). Toxinotyping was performed according to the scheme developed by Rupnik et al. [START_REF] Rupnik | A novel toxinotyping scheme and correlation of toxinotypes with serogroups of Clostridium difficile isolates[END_REF].

Determination of Minimum inhibitory concentration (MIC)

Susceptibility testing for erythromycin, clindamycin, moxifloxacin, metronidazole and vancomycin was carried out using the E-test (bioMérieux) on Brucella Blood Agar (bioMérieux) as described elsewhere [START_REF] Barbut | Antimicrobial susceptibilities and serogroups of clinical strains of Clostridium difficile isolated in France in 1991 and 1997[END_REF].

Hamster infection model

Adult Mesocricetus auratus female hamsters (weight, 80-100 g) were obtained from Charles River Laboratories and were housed individually in polypropylene isolator cages fitted with filter covers holding disposable polyester air filters. All food, water, bedding, cages, wire lids and filter covers were autoclaved before being used and food and water were given ad libitum.

Animals were randomly distributed in five groups (minimum of seven animals per group) and five days before infection, each animal was given orogastrically a single dose of clindamycin at 50 mg/kg as described previously [START_REF] Sambol | Infection of hamsters with epidemiologically important strains of Clostridium difficile[END_REF]. On day 0, each animal received 10 4 spores of the adequate strain and animals were monitored daily for signs of disease such as weight loss, lack of activity, wet tail and diarrhea until death or during 14 days for surviving hamsters which were then euthanized. Bacterial colonization was monitored at 2-, 4-, 7-, 10-and 14-days post challenge for surviving hamsters. Briefly, a suspension at 10 mg/ml of stools was homogenized in PBS and then was diluted from 10 -1 to 10 -4 ; 100 µl of each dilution was inoculated on ChromID agar (bioMérieux) in duplicate and plates were incubated in anaerobic atmosphere at 37°C for 48 hours before counting of the colonies.

Histological staining and scoring

Cecal sections were collected from hamsters and were fixed in 10% formalin for a minimum of 2 h then transferred in ethanol 70% for 18 h and finally paraffin embedded. Sections of 3 µm were stained with hematoxylin and eosin and analyzed in a blind manner using the histopathological scoring scheme from Buckley et al. [START_REF] Buckley | Susceptibility of hamsters to Clostridium difficile isolates of differing toxinotype[END_REF]. Briefly, extent and depth of inflammation were evaluated with 4 different criteria on a scale ranging from 0 to 3: neutrophil infiltration (0, no neutrophil accumulation;

Statistical analysis

All analysis were performed using Graph Pad Prism 5. Results of colonization kinetics were expressed as mean number of total CFU per g of fecal pellets. Results of histology were expressed as mean (+/-standard deviation) histology score per strain.

  ) was: adk = 15, atpA = 21, dxr = 31, glyA = 38, recA = 21, sodA = 36 and tpi = 30. The alleles profile of the new ST of CD10-165 (A -B + CDT + ) was: adk = 13, atpA = 18, dxr = 22, glyA = 33, recA = 18, sodA = 31 and tpi = 26.

Fig. 1 .

 1 Fig. 1. Colonization kinetics of C. difficile strains in hamsters. Colonization of each C. difficile strain was monitored in faecal samples by numerating both vegetative and spore forms at day 2, 4 7, 10 and 14 for the surviving hamsters.

Fig. 2 .

 2 Fig. 2. Kaplan Meyer survival plots for hamster infected with the five different strains after a single dose of clindamycin (n=7 or 8 per group).

Fig. 3 .

 3 Fig. 3. Cecal histology of hamsters showed significant changes according to different strains used for

Fig. 4 .

 4 Fig. 4. Histological differences in the ceca of hamsters infected with the various strains of C. difficile. The criteria were neutrophil infiltration, haemorrhagic congestion, hyperplasia and percent of epithelial barrier involvements with a maximal score of 12. The bars represent the mean scores for each group of animals and standard deviations.

TABLE 1 . Clinical and biological data on the 5 strains.

 1

		Ribotype
		ST		Clinical symptoms	Origin			Genotype
	Strain	Clade	Age	/treatment	Year of isolation	Outcome	Phenotype	(PaLoc)
	CD10-165	New	74 y	PMC	Villefranche sur Sâone	Death attributable to CDI the day	A -B + CDT +	tcdR +
		New		None	(France), 2010	after CDI diagnosis		tcdB +
		Clade C-I						tcdE +
								tcdA -
								tcdC -
	RA09-070	New	60 y	AAD	Cambrai (France)	Resolution of diarrhea	A + B -CDT -	tcdR +
		New		Oral MTZ 500 mg x3	2009	No relapse		tcdB -
		Clade 5		10 days				tcdE -
								tcdA +
								tcdC -
	CD13-125	RT 027	73 y	AAD	Marseille (France)	unknown	A + B + CDT +	tcdR +
		ST 1		unknown	2013			tcdB +
		Clade 2						tcdE +
								tcdA +
								tcdC + -18pb deletion in

Acknowledgements

We sincerely thank the technical assistance of Valérie Domergue (Region Ile de France, IFR141 IPSIT) for animal facilities. We also thank Anlyata Youssouf, Sylvie Lambert-Bordes and Sandra Hoys for technical support.


Gaël Bonnin
email: gael.bonnin@neoma-bs.fr

Gaël Author

Marketing Bonnin

Neoma Professor

Business

familiarity with AR in the influence of AR on patronage intention

Keywords: Augmented reality, perceived risk, online store, hype Augmented reality, perceived risk, online store, hype

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

patronage intention

Introduction

In spite of its popularity, augmented reality (AR), defined as technologies in which "the display of an otherwise real environment is augmented by means of virtual (computer graphic) objects' [START_REF] Milgram | A Taxonomy of Mixed Reality Visual Displays[END_REF], fails to reach mass adoption: according to a survey of the Digital Marketing Institute in 2017, 60% of firms are currently not using AR and Gartner, in the 2018 edition of its hype cycle of emerging technologies, still sees AR as being in the "trough of disillusionment", a phase were a technology is perceived as not holding on to its promises. Retail managers need to know what benefits they can expect from using AR on their e-commerce site before investing in this technology: will it drive traffic? will it improve their image? will it last beyond the "hype" effect and when consumers become familiar with the technology?

To these questions, research offers only limited answers.

First, if the adoption of AR by consumers begins to be well documented (e.g. Kim & Forsythe, 2008) and if a few studies have been conducted on the expectations toward AR in online commerce (e.g. [START_REF] Dacko | Enabling smart retail settings via mobile augmented reality shopping apps[END_REF][START_REF] Olsson | Expected user experience of mobile augmented reality services: A user study in the context of shopping centres[END_REF], research on the process of influence of AR applications on online store visitors is still rare. The few studies on the topic have demonstrated that AR increases consumer satisfaction [START_REF] Poushneh | Augmented reality in retail: A trade-off between user's control of access to personal information and augmentation quality[END_REF], willingness to buy [START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF][START_REF] Yim | Is Augmented Reality Technology an Effective Tool for E-commerce? An Interactivity and Vividness Perspective[END_REF] or the intention to visit online stores [START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF][START_REF] Hilken | Augmenting the eye of the beholder: exploring the strategic potential of augmented reality to enhance online service experiences[END_REF][START_REF] Pantano | Enhancing the online decision-making process by using augmented reality: A two country comparison of youth markets[END_REF][START_REF] Poushneh | Discernible impact of augmented reality on retail customer's experience, satisfaction and willingness to buy[END_REF]. This impact of AR on these variables is mediated by increases in hedonic and utilitarian experiences with the web site [START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF][START_REF] Hilken | Augmenting the eye of the beholder: exploring the strategic potential of augmented reality to enhance online service experiences[END_REF][START_REF] Poushneh | Discernible impact of augmented reality on retail customer's experience, satisfaction and willingness to buy[END_REF][START_REF] Yim | Is Augmented Reality Technology an Effective Tool for E-commerce? An Interactivity and Vividness Perspective[END_REF] as well as by a greater comfort in the decision making process [START_REF] Hilken | Augmenting the eye of the beholder: exploring the strategic potential of augmented reality to enhance online service experiences[END_REF].

The objective of this research is to extend these results by integrating three variables as yet overlooked by previous research and thus to contribute to the knowledge of the process variables and boundary conditions pertaining to the influence of AR on online shoppers.

First, we integrate the perceived risk of making an online purchase. This is of primary importance because the influence of AR on perceived risk has not been empirically studied, although online purchase is still perceived as a risky behavior by consumers [START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF][START_REF] Cheng | Do extrinsic cues affect purchase risk at international e-tailers: The mediating effect of perceived e-tailer service quality[END_REF][START_REF] Pappas | Marketing strategies, perceived risks, and consumer trust in online buying behaviour[END_REF] and although it has been proposed that AR could decrease the perceived risk of making a purchase online [START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF][START_REF] Kim | Adoption of sensory enabling technology for online apparel shopping[END_REF][START_REF] Poushneh | Discernible impact of augmented reality on retail customer's experience, satisfaction and willingness to buy[END_REF]. It is important to note that our study is not about the risk of using a new technology (see for example [START_REF] Roy | Constituents and consequences of smart customer experience in retailing[END_REF] but about the risk of making an online purchase.

In addition, we integrate the concept of attractiveness toward alternative online stores [START_REF] Chuah | What drives Gen Y loyalty? Understanding the mediated moderating roles of switching costs and alternative attractiveness in the value-satisfaction-loyalty chain[END_REF][START_REF] Yim | Multiple reference effects in service evaluations: Roles of alternative attractiveness and self-image congruity[END_REF].

This goes beyond the current focus on purchasing and patronage intention and aims at capturing the potential effect of AR on online store image and assessing the long term advantage provided by AR to online stores.

Conceptual background and hypotheses

AR and the attractiveness towards alternative online store

AR embeds a virtual product (e.g. a dress, a piece of furniture) into the real environment of consumers. It also allows consumer to interact with products. These new possibilities offered by AR lead to "service augmentation" [START_REF] Hilken | Augmenting the eye of the beholder: exploring the strategic potential of augmented reality to enhance online service experiences[END_REF][START_REF] Poushneh | Augmented reality in retail: A trade-off between user's control of access to personal information and augmentation quality[END_REF].

To account and test the influences of AR on online stores, scholars have drawn from research on shopping experience that showed that two dimensions are of special importance for store evaluation: utilitarian evaluation (i.e. usefulness) and hedonic evaluation (i.e. pleasure) [START_REF] Babin | Work and Fun: Measuring Hodonic and Utilitarian Shopping Value[END_REF][START_REF] Childers | Hedonic and utilitarian motivations for online retail shopping behavior[END_REF][START_REF] Voss | Measuring the Hedonic and Utilitarian Dimensions of Consumer Attitude[END_REF]. Research has shown that AR-based service augmentation has a positive influence on both utilitarian and hedonic evaluations of online stores [START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF][START_REF] Hilken | Augmenting the eye of the beholder: exploring the strategic potential of augmented reality to enhance online service experiences[END_REF][START_REF] Poushneh | Discernible impact of augmented reality on retail customer's experience, satisfaction and willingness to buy[END_REF][START_REF] Yim | Is Augmented Reality Technology an Effective Tool for E-commerce? An Interactivity and Vividness Perspective[END_REF]. These evaluations increase patronage intentions (willingness to visit the online store) and purchase intentions (willingness to buy a product from the online store) [START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF][START_REF] Hilken | Augmenting the eye of the beholder: exploring the strategic potential of augmented reality to enhance online service experiences[END_REF][START_REF] Poushneh | Discernible impact of augmented reality on retail customer's experience, satisfaction and willingness to buy[END_REF][START_REF] Yim | Is Augmented Reality Technology an Effective Tool for E-commerce? An Interactivity and Vividness Perspective[END_REF]. Put shortly, AR has an indirect positive influence on patronage or purchase intention via an increase in utilitarian and hedonic attitude toward online stores.

But the question of the impact of AR on store image remains open. Answering this question is important because technological innovation has a positive influence on store image [START_REF] Beuckels | An experimental study to investigate the impact of image interactivity on the perception of luxury in an online shopping context[END_REF][START_REF] Fuentes-Blasco | Role of marketing and technological innovation on store equity, satisfaction and word-of-mouth in retailing[END_REF][START_REF] Fuentes-Blasco | Role of marketing and technological innovation on store equity, satisfaction and word-of-mouth in retailing[END_REF], because retailers use AR as a mean to be perceived as superior to competitors and gain attractiveness [START_REF] Bansal | Migrating " to New Service Providers : Toward a Unifying Framework of Consumer[END_REF], and because store equity, of which attractiveness is a facet, is an antecedent to shopping behavior [START_REF] Arnett | Developing parsimonious retailer equity indexes using partial least squares analysis: A method and applications[END_REF][START_REF] Gil-Saura | Store equity and behavioral intentions: The moderating role of the retailer's technology[END_REF][START_REF] Goedertier | Brand typicality and distant novel extension acceptance: How risk-reduction counters low category fit[END_REF][START_REF] Lee | Shopping value in online auctions: Their antecedents and outcomes[END_REF].

The dominant approach to attractiveness has been "alternative attractiveness" defined as "the positive characteristics of competing service providers" (Bansal et al., 2005, p.100). As our focus is the impact of using AR for an online store and as AR has not been widely adopted, we use the mirror concept of attractiveness of the online store (as opposed to alternative attractiveness). We define it as the perceived superiority of an option against other competing options. The focus is then on the evaluation of the online store itself rather than on the evaluation of its competitors. It is better suited to capture the influence of AR for the online store, as AR is expected to induce a difference toward the majority of online stores that haven't adopted it yet.

Alternative attractiveness has a negative influence on satisfaction [START_REF] Yim | Multiple reference effects in service evaluations: Roles of alternative attractiveness and self-image congruity[END_REF], on loyalty and on the satisfaction-loyalty link [START_REF] Chuah | What drives Gen Y loyalty? Understanding the mediated moderating roles of switching costs and alternative attractiveness in the value-satisfaction-loyalty chain[END_REF] and increases consumers intention to switch to other service providers [START_REF] Bansal | Migrating " to New Service Providers : Toward a Unifying Framework of Consumer[END_REF]. So, in line with these results, we can assume that online store attractiveness will have a positive influence on patronage intention.

Several studies have shown that the implementation of a technology influences the perception of the store, offline [START_REF] Fuentes-Blasco | Role of marketing and technological innovation on store equity, satisfaction and word-of-mouth in retailing[END_REF][START_REF] Fuentes-Blasco | Role of marketing and technological innovation on store equity, satisfaction and word-of-mouth in retailing[END_REF] or online [START_REF] Beuckels | An experimental study to investigate the impact of image interactivity on the perception of luxury in an online shopping context[END_REF]. But, as mentioned before, AR has a positive influence on hedonic and utilitarian evaluations.

And these evaluations have a positive influence on store perceptions [START_REF] Lee | Shopping value in online auctions: Their antecedents and outcomes[END_REF][START_REF] Overby | The effects of utilitarian and hedonic online shopping value on consumer preference and intentions[END_REF]. We can infer from this that AR has an indirect positive influence on online store attractiveness via utilitarian and hedonic evaluations.

In sum, we can hypothesize a process of serial mediation from AR to patronage intention (for the sake of simplification, each hypotheses is followed by a simplified representation of the path between the independent variable and the final dependent variable; =>+ means positive influence; =>-means negative influence):

H1a. AR has an indirect positive influence on patronage intention via online store utilitarian evaluation and online store attractiveness (double mediation). (AR=> + Utilitarian evaluation =>+ attractiveness =>+ patronage intention)

H1b. AR has an indirect positive influence on patronage intention via online store hedonic evaluation and online store attractiveness (double mediation). (AR=> + Hedonic evaluation =>+ attractiveness =>+ patronage intention)

2.2.AR and perceived risk of making a purchase on an online store

Perceived risk is usually defined as the "consumer's perceptions of uncertainty and adverse consequences of buying a product (or service)" (Dowling and Staelin, 1994, p.119) or "the subjective expectation of a loss" [START_REF] Nepomuceno | How to reduce perceived risk when buying online: The interactions between intangibility, product knowledge, brand familiarity, privacy and security concerns[END_REF]. In other words, perceived risk is the expectation of a loss, and the consequences of such a loss if it occurs. A substantive amount of research has been dedicated to the topic.

But it is still an important avenue of research [START_REF] Pappas | Marketing strategies, perceived risks, and consumer trust in online buying behaviour[END_REF].

Understanding elements that can decrease perceived risk is especially crucial [START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF][START_REF] Cheng | Do extrinsic cues affect purchase risk at international e-tailers: The mediating effect of perceived e-tailer service quality[END_REF].

Four facets of perceived risk are usually distinguished: psychosocial risk (harm to identity or self-esteem), financial risk (loss of money), time risk (loss of time because of late delivery for example) and product or performance risk (when expectations about the product are not met when it is used) [START_REF] Aghekyan-Simonian | The role of product brand image and online store image on perceived risks and online purchase intentions for apparel[END_REF][START_REF] Casidy | A risk worth taking: Perceived risk as moderator of satisfaction, loyalty, and willingnessto-pay premium price[END_REF][START_REF] Nepomuceno | How to reduce perceived risk when buying online: The interactions between intangibility, product knowledge, brand familiarity, privacy and security concerns[END_REF]. Among these, product risk is the one with the most important and stable impact on shopper behavior [START_REF] Aghekyan-Simonian | The role of product brand image and online store image on perceived risks and online purchase intentions for apparel[END_REF][START_REF] Suki | Modeling the determinants of consumers' attitudes toward online group buying: Do risks and trusts matters?[END_REF][START_REF] Nepomuceno | How to reduce perceived risk when buying online: The interactions between intangibility, product knowledge, brand familiarity, privacy and security concerns[END_REF].

To diminish perceived risk, online retailers can use cues, be they extrinsic (not directly related to the website design, assortment or service) or intrinsic (related to or part of the offering) [START_REF] Cheng | Do extrinsic cues affect purchase risk at international e-tailers: The mediating effect of perceived e-tailer service quality[END_REF]. Research has shown that extrinsic cues (e.g. service quality, brand equity, quality guarantees, brand and online images) decrease perceived product risk [START_REF] Aghekyan-Simonian | The role of product brand image and online store image on perceived risks and online purchase intentions for apparel[END_REF][START_REF] Cheng | Do extrinsic cues affect purchase risk at international e-tailers: The mediating effect of perceived e-tailer service quality[END_REF]. But, the impact of extrinsic cues seems to be lesser for online stores than for physical stores [START_REF] Aghekyan-Simonian | The role of product brand image and online store image on perceived risks and online purchase intentions for apparel[END_REF]. It is thus important for online stores to find other means to decrease perceived risk [START_REF] Cheng | Do extrinsic cues affect purchase risk at international e-tailers: The mediating effect of perceived e-tailer service quality[END_REF].

Among intrinsic cues, AR is an interesting option. Indeed, one of the main causes of perceived product risk in online shopping is that consumers cannot actually interact physically with the product during the shopping trip (touch it, try it on). The intangibility of products presented online entails difficulties in the evaluation of features of the product [START_REF] Aghekyan-Simonian | The role of product brand image and online store image on perceived risks and online purchase intentions for apparel[END_REF][START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF][START_REF] Kim | Adoption of sensory enabling technology for online apparel shopping[END_REF][START_REF] Nepomuceno | How to reduce perceived risk when buying online: The interactions between intangibility, product knowledge, brand familiarity, privacy and security concerns[END_REF]. This results in an uncertainty about the choice, and an increase in perceived risk [START_REF] Cheng | Do extrinsic cues affect purchase risk at international e-tailers: The mediating effect of perceived e-tailer service quality[END_REF][START_REF] Nepomuceno | How to reduce perceived risk when buying online: The interactions between intangibility, product knowledge, brand familiarity, privacy and security concerns[END_REF]. AR can help consumers get a better sense of product features, and thus reduce the risk of making a mistake when purchasing the product [START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF][START_REF] Kim | Adoption of sensory enabling technology for online apparel shopping[END_REF].

Perceived risk has a negative influence on perceptions, like attitudes [START_REF] Suki | Modeling the determinants of consumers' attitudes toward online group buying: Do risks and trusts matters?[END_REF], trust [START_REF] Pappas | Marketing strategies, perceived risks, and consumer trust in online buying behaviour[END_REF] or brand evaluations [START_REF] Baek | When comparative valence frame affects brand extension evaluations: the moderating role of parent-extension fit[END_REF][START_REF] Goedertier | Brand typicality and distant novel extension acceptance: How risk-reduction counters low category fit[END_REF]. It also has a strong negative influence on patronage intention [START_REF] Aghekyan-Simonian | The role of product brand image and online store image on perceived risks and online purchase intentions for apparel[END_REF][START_REF] Nepomuceno | How to reduce perceived risk when buying online: The interactions between intangibility, product knowledge, brand familiarity, privacy and security concerns[END_REF]. Moreover, perceived risk mediates the influence of external cues on purchase intention [START_REF] Aghekyan-Simonian | The role of product brand image and online store image on perceived risks and online purchase intentions for apparel[END_REF]. Finally, the influence of perceived risk on purchase intention is mediated by perceptions [START_REF] Goedertier | Brand typicality and distant novel extension acceptance: How risk-reduction counters low category fit[END_REF].

Given the results of previous research, we can hypothesize a process of serial mediation from AR to patronage intention:

H2. AR has an indirect positive influence on patronage intention via perceived product risk and the attractiveness of the online store (double mediation). (AR=> -Perceived risk =>-attractiveness =>+ patronage intention)

2.3.The moderating role of familiarity with AR on the influence of AR on patronage intention

Familiarity is defined as "the number of product related experiences that have been accumulated by the consumer" (Alba and Hutchinson, 1987, p.411). With experience, consumers develop a set of knowledge about the product or service and know what to expect from a specific product or service. Several studies have shown that familiarity has a moderating influence on the relationships between product or service perceptions and consumer responses. But these studies have not investigated the influence of familiarity with AR. And more generally these studies have focused on the familiarity with a product and the evaluations of this product, and not familiarity with a technology on the impact of this technology.

The moderating role of familiarity on the indirect effect of AR on patronage intention is justified by several reasons. First, at a general level and concerning evaluations of the online store, consumers with more experience of a product or service tend to perceived it as less novel and typical, which in turns decreases their evaluations of the product [START_REF] Murray | Examining the role of store design on consumers' cross-sectional perceptions of retail brand loyalty[END_REF][START_REF] Yim | Is Augmented Reality Technology an Effective Tool for E-commerce? An Interactivity and Vividness Perspective[END_REF][START_REF] Babin | Seeking something different? A model of schema typicality, consumer affect, purchase intentions and perceived shopping value[END_REF][START_REF] Ainsworth | Comfort in brick and mortar shopping experiences: Examining antecedents and consequences of comfortable retail experiences[END_REF]. So we can infer that people more familiar with AR will show a weaker relationship between AR and hedonic and utilitarian evaluation.

On the contrary, concerning risk, when consumers have already had previous experiences with a product, they anticipate the potential results of the use of a product and feel less uncertainty. People new to AR may not trust AR ability to help them in evaluating the product, whereas people who already have used AR, as they have had an experience before, may trust more AR to help them to make a purchase with less risk. In this case, people more familiar with AR will show a stronger relationship between AR and perceived risk.

Concerning attractiveness and patronage intention, [START_REF] Nel | Online customers' habit-inertia nexus as a conditional effect of mobile-service experience: A moderated-mediation and moderated serial-mediation investigation of mobile-service use resistance[END_REF] have shown that when internet experience is high, the influence of hedonic attitude on purchase intention of mobile-service decreases [START_REF] Nel | Online customers' habit-inertia nexus as a conditional effect of mobile-service experience: A moderated-mediation and moderated serial-mediation investigation of mobile-service use resistance[END_REF]. So we can assume that people more familiar with AR will see a weaker influence of hedonic evaluation on attractiveness. On the contrary, utilitarian evaluation and perceived risk being less linked to emotion will benefit of previous experiences with AR.

People more familiar with AR will show a stronger link between utilitarian evaluation and attractiveness on the one hand and between product perceived risk and attractiveness on the other hand.

Study 1

The goal of study 1 was to assess the mediating roles of perceived risk and attractiveness in the influence of AR on patronage intention.

3.1.Design and procedure

The design of study was similar to the one of other studies on the influence of AR on online stores (e.g. [START_REF] Javornik | It's an illusion, but it looks real!' Consumer affective, cognitive and behavioural responses to augmented reality applications[END_REF][START_REF] Poushneh | Discernible impact of augmented reality on retail customer's experience, satisfaction and willingness to buy[END_REF].

A web-based between-subject experiment was conducted in France in may 2016. It manipulated the presence of AR on an online webstore. The product category chosen was sunglasses.

In condition 1 (no AR), participants were shown the picture of the online store of a retailer selling glasses (Fig. 2) which was introduced by the following text: "Please watch carefully this 98 participants participated in the survey and were randomly assigned to one of the two conditions. We had 53 participants for condition 1, 45 for condition 2. Although there is a difference in size between the two conditions, it is small enough to be acceptable. As to age, participants were rather young: 64.2% were between 18 and 25; 16.3% between 26 and 40; 9.2% between 41 and 50; and 10.2% more than 50. 56% of participants were men and 44% women. There was no difference in gender distribution across conditions (p=.761).

3.2.Measures

All concepts of interest to the research objective were measured using existing scales that were adapted to the context of the study.

Hedonic evaluation was measured with 3 items and seven-point semantic differential scales: fun/not fun; thrilling/not thrilling;

exciting/not exciting [START_REF] Voss | Measuring the Hedonic and Utilitarian Dimensions of Consumer Attitude[END_REF] To measure the attractiveness of the online store, we adapted the "attractiveness of competitors" scale from [START_REF] Bansal | Migrating " to New Service Providers : Toward a Unifying Framework of Consumer[END_REF] to measure the attractiveness of the online store. We used three items and used five-point Likert scale (1= Totally disagree; 5= Totally agree): this website has advantages competitors don't have; this website solves problems competitors don't solve; this website is superior to competitor (cronbach's alpha =.921; AVE=.864).

Finally, patronage intention was measured with one item taken from [START_REF] Bart | Are the Drivers and Role of Online Trust the Same for All Web Sites and Consumers?: A Large-Scale Exploratory Empirical Study[END_REF] and used a five-point Likert scale (1= Totally disagree; 5= Totally agree): I would purchase an item at this online store.

3.3.Analysis and results

To test our hypotheses, we used the PROCESS V 3.3 macro [START_REF] Hayes | Introduction to Mediation, Moderation, and Conditional Process Analysis[END_REF]model 80). Results are summarized in table 1.

Results showed no significant indirect effect of AR on patronage intention via utilitarian evaluation and attractiveness (BootLLCI=-.026; ULCI=.023). H1.a. is then not supported. If AR increases utilitarian evaluation (p=.047), this effect is not transferred to attractiveness or to patronage intention, even though utilitarian evaluation has a direct influence on patronage intention (p=.01).

H1.b. and H2 are supported.

An online store with AR is evaluated as more fun, and this increases its attractiveness which in turn augments patronage intention (H1.b.; β =.199; BootLLCI=.010; ULCI=.401). The effect is rather strong. It should be noted that the indirect effect via hedonic evaluation and patronage intention (without the mediation of attractiveness) is not significant.

The presence of AR on an online store also decreases the perceived risk of making a purchase at this online store, which increases attractiveness and in turn patronage intention (H2.; β =.046; BootLLCI=.000; ULCI=.114). It should be noted first that the effect is low compared to the effect of hedonic evaluation. It should also be noted that the presence of AR has an effect of patronage intention via perceived risk without the mediation of attractiveness (β =.237; BootLLCI= .060;

BootULCI=.436). In this case the effect is stronger.

The results of study 1 confirm the important role of perceived risk in the understanding of the mechanisms of influence of AR on online store. Attractiveness is important mostly to account for the effect of hedonic evaluation.

Study 2

Study 2 aimed to replicate results from study 1 to another product category and to assess the moderating effect of familiarity with AR on patronage intention via utilitarian evaluation, hedonic evaluation, perceived risk and attractiveness of the online store.

4.1.Design and procedure

A between subject experiment with two conditions was conducted in France in June 2019. Compared to study 1, the only change in design and procedure was the choice of the product category: sneakers. The webstore of the brand "Converse" was chosen. In condition 1 (figure 4), participants

were presented the non-AR webstore of the brand. In condition 191 participants took part in the survey and were randomly assigned to one of the two conditions. We had 102 participants for condition 1, 89 for condition 2. Again the difference in size is small enough to be acceptable. Mean age of participants was 45, ranging from 18 to 65. 50.3% of participants were men and 49.7% women. There was no difference in gender distribution across conditions (p=.713).

4.2.Measures

Measures were the same as for study 1: hedonic evaluation (cronbach's alpha=.934; AVE=.883), utilitarian evaluation (cronbach's alpha=.898; AVE=.699), perceived product risk (cronbach's alpha=.877; AVE=.794), attractiveness of the online store (cronbach's alpha=.929; AVE=.766) and patronage intention (mono item).

To these measures, we added a measure of familiarity with AR.

It was measured with one item measured on a 7-point Likert scale: I have already used AR applications when making purchase on a webstore.

4.3.Results

To test our hypotheses, we used the PROCESS V 3.3 macro [START_REF] Hayes | Introduction to Mediation, Moderation, and Conditional Process Analysis[END_REF].For the test of H1.a., H1.b. and H2, we used model 80. To account for the moderation of serial mediations (H3.a., H3.b. and H3.C.), we customized model 80. In this case, Wmatrix was: 1,1,0,1,0,0,1,0,0,0,1,0,0,0,0. Results are summarized in table 2.a. (indirect effects) and 2.b. (moderation of the indirect effects).

H1.a. was not supported (BootLLCI =-.005 Boot ULCI= .030).

The presence of AR did not increase patronage intention via utilitarian evaluation and attractiveness. Actually, the presence of AR did not even increase utilitarian evaluation (p=.364).

This result is in contradiction with the results of study 1 of the few previous research on the impact of AR (e.g. [START_REF] Hilken | Augmenting the eye of the beholder: exploring the strategic potential of augmented reality to enhance online service experiences[END_REF][START_REF] Pantano | Enhancing the online decision-making process by using augmented reality: A two country comparison of youth markets[END_REF][START_REF] Poushneh | Discernible impact of augmented reality on retail customer's experience, satisfaction and willingness to buy[END_REF].

On the contrary, H1.b. was validated (β= .062; BootLLCI =.001 Boot ULCI= .150). As in study 1 and in echo to previous research, the presence of AR improves hedonic evaluation of the online store, which increases attractiveness and, in turn patronage intention. And, as in study 1, there was no indirect relationship between AR and patronage intention via hedonic evaluation without the mediation of attractiveness (BootLLCI=-.126 ULCI=.115). The influence of AR via hedonic evaluation is realized mostly via the fact that people perceive the online store as being different. Without this perception of difference, the influence of AR via hedonic evaluation on patronage intention seems to disappear. It should be noted that the effect is lower than for study 1.

H2. was also supported (β = .034; BootLLCI =.000 Boot ULCI=.087). As in study 1, AR decreases perceived risk, which improves attractiveness of the store and then patronage intention. As in study 1 too, the decrease in perceived risk induced by the presence of AR directly increases patronage intention, without the mediation of attractiveness (β = .193; BootLLCI =.051 Boot ULCI= .364). Again the effect is stronger than in the case of double mediation.

In sum, study 2 confirms the result of study 1 with the exception of utilitarian evaluation.

If we turn to familiarity with AR, the moderating role of this variable is confirmed in the case of perceived risk only. BootULCI=.154). There seems to be a relationship, but not in the direction expected. Vasquez-Parraga, 2017) and has been confirmed as robust in an area of research where "real immersion" may be supposed to be more relevant: research on store design [START_REF] Roschk | Calibrating 30 Years of Experimental Research : A Meta-Analysis of the Atmospheric Effects of Music , Scent , and Color[END_REF].

Moreover, concerning hedonic and utilitarian variables, results are in line with the results from studies based on real use of AR (at least for study 1 concerning utilitarian evaluation, an interpretation of the absence of effect of utilitarian evaluation in study 2 is given below). Finally, part of our goal, was to assess the "communication" and "novelty" effect of AR. Given these objectives, the use of a presentation of a technology is relevant. Of course, more research is needed to confirm and nuance our results when people use AR, and especially to assess the influence of AR features (e.g. environmental embedding, simulated physical control, interactivity,…) on risk.

If we turn to contributions, probably the most significant result of the two experiments lies in the role of perceived risk in accounting for the influence of AR for online store. It mediates the influence of AR on patronage indirectly via the mediating role of attractiveness, but mostly directly. Moreover, these effects are reinforced when people become more familiar with AR. This is an important result as it shows that AR, if it is designed to address the issue of the uncertainties people have when they buy a product online, can survive the "newness" effect of AR. These results contribute to the literature on perceived risk in online retail settings, and answer the calls from [START_REF] Cheng | Do extrinsic cues affect purchase risk at international e-tailers: The mediating effect of perceived e-tailer service quality[END_REF] about the necessity to identify means to reduce perceived risk of online purchase and from [START_REF] Beck | I virtually try it … I want it ! Virtual Fitting Room: A tool to increase on-line and off-line exploratory behavior, patronage and purchase intentions[END_REF] about the need to account for perceived risk in the study of the influence of AR.

The role of attractiveness has also been demonstrated but it is closely link to hedonic evaluation. Attractiveness does not mediate the indirect relationship between AR and patronage intention via utilitarian evaluation. It does for perceived risk, but this link is weak. And the influence of AR via perceived risk on patronage intention can be direct, with a strong effect.

But for hedonic evaluation the effect is only through attractiveness. This is also an important result because the hedonic influence of AR on patronage intention is dependent of the fact that the online store is perceived as different. Once the development of AR becomes more massive, this effect may disappear and not survive the "hype" effect. This is sustained by another result. Only for people moderately familiar with AR is this result significant. For people who don't know AR or who are familiar with AR, the hedonic route of the influence of AR on patronage intention via attractiveness is not significant.

This contributes to research on the impact of AR on online settings and, more generally, on the impact of technology in retail, where hedonic experience is of key importance. We show here that the direct link between hedonic evaluation and patronage intention is due to a "being different" effect. This should be taken into account when studying the impact of technology. In this line of reasoning, the integration of the role of familiarity with AR, or more generally with the technology studied, seems important. Different shapes of relationships can emerge when familiarity with technology is studied, especially really new technology.

A last but more surprising result is the fact that utilitarian has a low effect (study 1) or has no effect (study 2). The result of study 2 may be connected to the product category. Sneakers and the brand "Converse" may be a product category where the utility of AR is less evident. This is a relatively well known product where the added value of AR may be less evident.

Even the use of a mirror in a store may be less important for sneakers than for sunglasses. Nevertheless, it pleads for further investigations on the possibility to generalize these results and the ones of previous research to different product categories.

Conclusion and managerial implications

This research has demonstrated with two experiments the role of perceived risk in the influence of AR for online stores, the importance of accounting for familiarity with AR and attractiveness, especially concerning hedonic evaluation.

We see two main managerial implications to our research. They both deal with the relevance of the use of AR by online retailers.

Firstly, the role of hedonic evaluation, and the impact on attractiveness, shows that online retailers will benefit from using AR, and probably technology more generally, as part of their communication strategy. An online store just showing the possibility to use new technologies will probably be perceived as different from competitors, as long as the technology has not been widely adopted. But it also means that this "hype" benefit may be short lived. Once people become more familiar with the technology and more online store use it, the hedonic effect of the presence of the technology may disappear. This means that online store needs to make the technology even more fun or different.

An alternative strategy is to focus on the long term benefits AR can provide to online store visitors: making them more confident with their choice of a product online. This may lead to other design developments of AR applications: more simple, more realistic, maybe less fun but more efficient applications.

Finally

  , we introduce the role of familiarity with AR. The goal of accounting for the influence of familiarity is to assess the potential of AR to provide a competitive advantage in the long run. If the effects of AR decrease or disappear after consumers have become familiar with it, then we can assume that AR will be a "hype" phenomenon. Another objective is to integrate familiarity in the conceptual model of the influence of AR, because this variable has been understudied despite its potential importance. We first present the research background and hypotheses concerning the integration of attractiveness toward alternative online stores, perceived risk and familiarity with AR. The design and results of two online experiments are then presented. Study 1 demonstrates the mediating role of perceived risk and attractiveness in the influence of AR on patronage intention. Study 2 confirms these results and extend them by showing that the more people are familiar with AR, the more a decrease in perceived risk increases attractiveness and patronage intention.

  In sum, our hypotheses are: H3.a. Familiarity with AR moderates the indirect relationship between AR and patronage intention via utilitarian evaluation and attractiveness: people more familiar with AR will show a weaker positive influence of AR on patronage intention via utilitarian evaluation and patronage intention. H3.b. Familiarity with AR moderates the indirect relationship between AR and patronage intention via hedonic evaluation and attractiveness: people more familiar with AR will show a weaker positive influence of AR on patronage intention via hedonic evaluation and patronage intention. H.3.c. Familiarity with AR moderates the indirect relationship between AR and patronage intention via perceived risk and attractiveness: people more familiar with AR will show a weaker positive influence of AR on patronage intention via perceived risk and patronage intention. The research model is summarized in figure 1.

Fig. 1 .

 1 Fig. 1. Research model.

Fig. 2 .Fig 3 .

 23 Fig. 2. Image presented in condition 1.

2

  (figure 5), participants were shown an image of the same website to which we added images showing the foot of a person virtually trying sneakers on.

Figure 4 .Figure 5 .

 45 Figure 4. Image presented in condition 1 (study 2)

  H3.a. (moderation of the indirect effect of AR on patronage intention via utilitarian evaluation and attractiveness) is rejected. Whatever the level of familiarity with AR, the serial mediation is not significant (Familiarity = 1: BootLLCI=-. (moderation of the indirect effect of AR on patronage intention via utilitarian evaluation and attractiveness) is also rejected. The serial mediation is not significant for lower level of familiarity (Familiarity = 1: BootLLCI=-.005 ULCI=.165) and higher level of familiarity (Familiarity = 5: BootLLCI=-.004 BootULCI=.154). But it is significant for moderate level of familiarity (Familiarity = 3: BootLLCI=.003

  the contributions of the research, one main limitation must be highlighted. The experiment we designed was not based on the actual use of the technology. This of course may affect the results, even though this methodology has been used substantially in AR research (e.g.Poushneh and

Table 1 .

 1 Summary of results for study 1.

	Hypotheses	Result
	H1.a. (rejected)	Indirect effect
		AR=>Utilitarian evaluation=>Attractiveness =>Patronage
		intention (BootLLCI=-.026; ULCI=.023)
		Relevant results concerning direct effect(s)
		AR=>Utilitarian evaluation: NS (Mno_AR=3.901; MAR=4.423;
		R²=.040; F=4.037; p=.047)
		AR=>Utilitarian evaluation=>Patronage intention: NS
		(BootLLCI=-.001; ULCI=.235)
		Utilitarian evaluation=> Attractiveness: NS (p=.941)
		Utilitarian evaluation=>Patronage intention (R²=.566;
		F=23.996; p=.01)
	H1.b. (validated)	Indirect effect
		AR=>Hedonic evaluation=>Attractiveness =>Patronage
		intention (β =.199; BootLLCI=.010; ULCI=.401)
		Relevant results concerning direct effect(s)
		AR=>Hedonic evaluation (Mno_AR=2.629; MAR=4.689; R²=.426;
		F=71.260; p=.000)
		AR=>Hedonic evaluation=>Patronage intention (BootLLCI=-
		.112; BootULCI=.589)
		Hedonic evaluation => attractiveness (R²=.660; F=45.138;
		p=.000)
		Attractiveness=>Patronage intention (R²=.566; F=23.996;
		p=.038)
	H2.(Validated)	AR =>Risk =>Attractiveness =>Patronage intention (β =.046;
		BootLLCI=.000; ULCI=.114)
		Relevant results concerning direct effect(s)
		AR=>Perceived product risk (Mno_AR=2.764; MAR=3.287;
		R²=.068; F=6.958; p=.010)
		Perceived product risk => attractiveness (R²=.660; F=45.138;

Table 2 .

 2 a. Summary of results for study 2 (indirect effects).

Contributions