Michael Adu Kwarteng
email: kwarteng@utb.cz

Abdul Bashiru Jibril
email: jibril@utb.cz

Elsamari Botha

Christian Nedu Osakwe

The influence of price comparison websites on online switching behavior: A consumer empowerment perspective

Keywords: Consumer empowerment, customer service experience consciousness, eSwitching, online ads, price comparison websites, shopper innovativeness

While online price comparison websites have burgeoned, there is scant understanding of how they influence online consumer behavior. This study addresses this gap in the literature by investigating the influence of price comparison websites on online switching behavior, and also suggests some additional factors that may be considered when looking at this relationship. We argue that shopper innovativeness, their perceived usefulness of the ad, and their customer service experience consciousness are important factors to consider when evaluating the impact of price comparison websites on eSwitching behavior. We also argue that the most appropriate theoretical lens through which to investigate this relationship is that of the consumer empowerment paradigm. A conceptual model is proposed and tested. Our analysis of 345 sample respondents finds that perceived usefulness of ads and customer service experience expectations are important enablers to price comparison websites use. Similarly, we find that shopper innovativeness and customer service expectations, in addition to price comparison websites use, are significant enablers to eSwitching behaviour. However, contrary to prediction, we find that shopper innovativeness has little to no influence on shoppers' use of price comparison websites; we also observed similar patterns concerning the link between the perceived usefulness of online ads and eSwitching behaviour. In conclusion, our research contributes to better understanding the influence of price comparison websites on online switching behavior, and the factors that might influence this relationship.

Introduction

While online price comparison websites have burgeoned, there is scant understanding of how they influence online consumer (eSwitching) behavior. This study addresses this gap in the literature by investigating the influence of price comparison websites on online switching behavior. While Osakwe and Chovancova (2015) examined female shoppers' perceptions towards the use of price comparison websites, Jung et al. (2014) examined work shoppers' response to price comparison websites, and [START_REF] Pourabedin | Customers' online channel switching behavior: The moderating role of switching cost[END_REF] investigated the role of customer value and attitudes in online channel switching behavior, there are no studies to the authors' knowledge that investigates the relationship between eSwitching behavior and price comparison websites. The emerging question, therefore, is whether the use of price comparison websites can lead to eSwitching behavior. This study by addressing this question seeks to close the void in our understanding concerning the relationship between price comparison websites and eSwitching behavior. This study also suggests some additional factors that may be considered when looking at this relationship.

Accordingly, and based on a survey of existing research (Broniarczyk & [START_REF] Zhang | Online service switching behavior: The case of blog service providers[END_REF], it is argued that shoppers' innovativeness, their perceived usefulness of online ads, and their customer service experience consciousness are important factors to consider when evaluating the impact of price comparison websites on eSwitching behavior and this forms the overarching objective of our paper. We also argue that the most appropriate theoretical lens through which to investigate this relationship is that of the consumer empowerment paradigm (e.g. [START_REF] Broniarczyk | Decision difficulty in the age of consumer empowerment[END_REF][START_REF] Camacho | The effect of customer empowerment on adherence to expert advice[END_REF][START_REF] Kucuk | Consumer empowerment model: From unspeakable to undeniable[END_REF]. In other words, by employing the consumer empowerment paradigm, this paper's objective is to investigate the relationship between (the use of) price comparison websites and eSwitching behavior in addition to the investigation of the determinants behind these phenomena, which we have identified above.

Altogether, this allows us to contribute to the literature on online shopping in at least two important ways. First, is that we contribute to the online shopping literature particularly concerning the presentation of evidence that the use of price comparison websites, especially with regard to young and existing online shoppers, significantly empowers shoppers to engage in eSwitching behavior. The second contribution pertains to the investigation of the determinants behind the perceived use of price comparison websites in addition to the investigation of the empirical question on the determinants of eSwitching behavior. In particular, we find that shoppers' traits primarily customer experience consciousness and innovativeness are enablers to eSwitching behavior, while positive perceptions towards the use of online ads as well as customer experience consciousness engender the use of price comparison websites.

Because it is commonly known that young adults, especially student population, are usually heavy users of online services and in general more receptive to emerging technologies (see also [START_REF] Yoo | Developing a scale to measure the perceived quality of an internet shopping site (Sitequal)[END_REF], we chose to test the study hypotheses using a (university) student sample; which is also consistent with studies on consumer switching in the technology context (e.g. [START_REF] Bhattacherjee | User switching of information technology: A theoretical synthesis and empirical test research[END_REF]. At the same time, it is worth noting that our sample is primarily made up of experienced internet users and who are familiar with online shopping. Taken together, this empirical context is appropriate for our investigation.

The following literature review addresses each of these constructs in turn, before suggesting the theoretical model that was tested. This is followed by a brief overview of the methodology, and findings of an exploratory study to test the model. We conclude with a short discussion of these findings.

Literature informing hypotheses development 2.1 Consumer empowerment paradigm

The consumer empowerment paradigm in marketing is an important extension of the psychological empowerment construct, long studied, in the psychology literature (cf. [START_REF] Zimmerman | Psychological empowerment: Issues and illustrations[END_REF][START_REF] Cattaneo | The process of empowerment: A model for use in research and practice[END_REF]. Camacho et al. (2014:294), while citing previous research, describe empowerment as "strategies or mechanisms that equip people with sufficient knowledge and autonomy to allow them to exert control over a certain decision". Similarly, it has been noted in the marketing literature that "empowerment requires mechanisms for individuals to gain control over issues that concern them, including opportunities to develop and practice skills necessary to exert control over their decision making" (Pires et al., 2006, p. 938). In light of previous discussions and among them Broniarczyk and Griffin (2014), [START_REF] Kucuk | Consumer empowerment model: From unspeakable to undeniable[END_REF], and [START_REF] Pires | The internet, consumer empowerment and marketing strategies[END_REF], the current investigation argues that this paradigm can help us gain understanding into the perceived use of price comparison websites and eSwitching behaviour in particular among existing shoppers. In general, the internet equips users with the tool to gain access to credible and quality information and this by implication confers more power and freedom of choice to users and in this case online shoppers. Moreover, since it is known that customers often rely on expert advice (in this instance, price comparison websites) when making purchase decisions [START_REF] Camacho | The effect of customer empowerment on adherence to expert advice[END_REF], such advice -well-intentionedcan dramatically reduce switching cost. One of the benefits of comparison tools and in this case price comparison websites is that they offer shoppers a range of choices [START_REF] Broniarczyk | Decision difficulty in the age of consumer empowerment[END_REF], thus allowing shoppers to shop across stores. Online switching behaviour (or eSwitching) is considered to be a possible outcome of this process. Similarly, since it is has been suggested in the literature that digital ads may be an important source of consumer empowerment today [START_REF] Hudders | Editorial: Digital advertising and consumer empowerment[END_REF], it is considered therefore to play an influential role in shoppers' behavioural tendencies to use price comparison websites and to consequently eSwitch. Consequently, the following hypothesis is proposed: H1: Price comparison websites' perceptions positively influence eSwitching behaviour.

At the same time, it is known that intrapersonal factors, described as "how people think about themselves and includes domain-specific perceived control and self-efficacy, motivation to control, perceived competence, and mastery" (Zimmerman, 1995, p. 588), is a key aspect of empowerment. Accordingly, we consider intrinsic factors, or more precisely traits, like the customer service experience and consumer/shopper innovativeness, to be strong propelling force for price comparison websites use and eSwitching behaviour. Before discussing each of these in turn, we turn to eSwitching behaviour.

eSwitching Behaviour

The reasons why customers engage in switching intentions and/or behaviour remains an important topic in the literature to this day (Bhattacherjee et but a factor often identified as a key determinant is the attractiveness of alternatives [START_REF] Chuang | Research on customer switching behavior in the service industry[END_REF][START_REF] Xu | Exploring individuals' switching behaviour: An empirical investigation in social network games in China[END_REF][START_REF] Zhang | Online service switching behavior: The case of blog service providers[END_REF]. In the context of this study, consumers might easily switch between online stores when it is believed they can get better price deals elsewhere. Price comparison websites lower the barriers to switching by offering such alternatives in one central place, with links that could easily navigate to said alternatives. Because price comparison websites are price aggregators, it offers the opportunity for shoppers to easily know the prices of each competing online stores and this consequently reduces switching cost. This study hypothesized (see H1) that these price comparison websites directly influence eSwitching behavior. The following section describes the former.

Price comparison websites

Comparison shopping can be defined as "the practice of comparing the prices of items from different sources to find the best deal" (Hajaj et al., 2015: 563). Price comparison websites provide the online alternative to this and we, therefore, define online price comparisons as the online tool that allows for the comparison of item prices from different sources to find the best deal. The use of price comparison websites has been acknowledged as an important search information tool, which has strong potential to alter shopping behaviour both in the online and offline environment (Bodur et Because shoppers can easily compare prices of similar firms and/or brands in a matter of seconds, the active use of price comparison websites not only reduces search costs but also empowers shoppers to buy from firms offering the best deal. This study argues that the greater the perceived usefulness of price comparison websites, the more it is expected that shoppers will use the information available on these sites in their pre-and post-purchase decisions. It, therefore, acts as a key mediator in the relationship between key influencing factors and online switching behavior. From a consumer empowerment perspective, it is pertinent to consider how these websites influence the relationship between eSwitching and shopper innovativeness, perceived usefulness of an ad and the consumers' service experience consciousness. Each of these now discussed in turn.

Shopper Innovativeness

Consumer/shopper innovativeness, or what some scholars may well refer to as variety seeking propensity, is a well-researched concept in the literature (e.g. Agarwal & Prasad, 1998; [START_REF] Bhattacherjee | User switching of information technology: A theoretical synthesis and empirical test research[END_REF][START_REF] Xu | Exploring individuals' switching behaviour: An empirical investigation in social network games in China[END_REF][START_REF] Mishra | Consumer innovativeness and consumer decision styles: A confirmatory and segmentation analysis, The International Review of Retail[END_REF]. In this instance and following prior literature [START_REF] Agarwal | A conceptual and operational definition of personal innovativeness in the domain of information technology[END_REF][START_REF] Bhattacherjee | User switching of information technology: A theoretical synthesis and empirical test research[END_REF], we define shopper innovativeness as a trait reflecting the willingness on the part of the shopper to experiment and/or try out any new products or range of services. Moreover, because consumer innovativeness has been implied in the internet browser context to positively relate to switching intentions among a similar sample of respondents like this study [START_REF] Bhattacherjee | User switching of information technology: A theoretical synthesis and empirical test research[END_REF], it stands to reason, that both the relationship between shopper innovativeness and eSwitching behavior, and its relationship to price comparison website perceptions begs investigation. Hence, we proposed that: H2: Shopper innovativeness positively influences eSwitching behavior. H3: Shopper innovativeness is positively related to price comparison website perceptions.

Customer Service Experience Consciousness

The role of customer service experience is well researched in academic and business literature (Berry et Osakwe & Chovancova, 2015). However, its relationship to online switching behavior and price comparison websites remains underdeveloped in empirical research. Service experience consciousness reflects a trait among shoppers who are highly demanding in service encounters, and thus tend to exhibit a higher dissatisfaction threshold. This trait, for example, has been reported to be an important enabler to customer-perceived use of price comparison websites (Osakwe & Chovancova, 2015), and is therefore included in the proposed conceptual model: H4: Customer service experience consciousness is positively related to price comparison website perceptions.

We extend this research by arguing that since this set of shoppers invests a significant amount of cognitive, emotional and even intellectual resources into service interactions/encounters with the firm, they are therefore more demanding, difficult to please and more likely to move from one store to another in search for better services at all times. Customer service experience consciousness has already been identified as a trait reflecting the likelihood of a customer to become highly dissatisfied with service encounters and since customer dissatisfaction has been linked to switching intentions in prior research (e.g. Fan & Suh, 2014), it can be posited therefore that customer service experience consciousness and eSwitching behavior are related. Moreover, following previous research [START_REF] Keaveney | Customer behavior in service industries: An exploratory study[END_REF][START_REF] Liang | Service quality and customer switching behavior in china's mobile phone service sector[END_REF], we argue that service inconvenience, impolite behavior on the part of service personnel, and occurrence of core service and service encounter failures will be less tolerated by those scoring high in customer service experience consciousness and thus in this case impacting eSwitching behavior. Consequently, the following hypothesis has been developed: H5: Customer service experience consciousness is positively related to eSwitching behavior.

The final construct, from an empowered customer perspective, we felt pertinent to include in the study is that of the perceived usefulness of online ads.

Perceived Usefulness of Online Ads

Consumers' attitudinal response to advertisements in general and online ads, in particular, is mixed [START_REF] Le | Consumer attitude towards website advertising formats: A comparative study of banner, pop-up and in-line display advertisements[END_REF][START_REF] Shavitt | Public attitude toward advertising: More favorable than you might think[END_REF][START_REF] Schlosser | Survey of internet users' attitudes toward internet advertising[END_REF]), yet it is considered an important contributing factor when investigating online consumer behavior (Ducoffe & Carlo, 2000;[START_REF] Mehta | Advertising attitudes and advertising effectiveness[END_REF]Osakwe & Chovanocva, 2015;[START_REF] Paliwoda | Determinants and antecedents of general attitudes towards advertising[END_REF]. Some consumers have ill-feelings about online ads, others may be indifferent to online ads, while some have positive perceptions about online ads. In theory, however, ads are often meant to inform consumers and offer choices which they can easily choose from. Online ads, therefore, empower consumers concerning his/her buying decisions (cf. [START_REF] Ducoffe | Advertising value and advertising processing[END_REF]. Therefore, in this instance, online ads can confer significant power to consumers [START_REF] Hudders | Editorial: Digital advertising and consumer empowerment[END_REF], especially when it is perceived to be informative and valuable. In an online services context, strong perceptions towards online ads provide fertile ground for shoppers to become increasingly pricesensitive (Osakwe & Chovancova, 2015). This may be particularly true with regard to the use of price comparison websites. This study, therefore, extends this line of the suggestion by including eSwitching behaviour as an alternative outcome of online ads' perceived usefulness. Consequently, the following hypotheses were developed: H6: Customers' perceived usefulness of ads positively influences their perception of price comparison websites. H7: Customers' perceived usefulness of ads positively influences their eSwitching behavior.

The above literature review and proposed hypotheses can be summarized in the theoretical model proposed in Figure 1. This model extends prior research (e.g. Osakwe & Chovancova, 2015) by our assessment of enablers to the perceived use of price comparison websites and eSwitching behavior, especially concerning young and existing online shoppers.

Figure 1. Empirical model

The methodology used to test the proposed model is outlined in the following section.

Empirical study

Survey data and method

More specifically, student sample was used in the study because this is an important consumer segment for studying online behaviour and has also been extensively employed in the literature [START_REF] Fan | Why do users switch to a disruptive technology? An empirical study based on expectation-disconfirmation theory[END_REF][START_REF] Hong | Understanding the consumer's online merchant selection process: The roles of product involvement, perceived risk, and trust expectation[END_REF][START_REF] Ozok | An empirical comparison of consumer usability preferences in online shopping using stationary and mobile devices: Results from a college student population[END_REF][START_REF] Wu | A meta-analysis of the impact of trust on technology acceptance model: investigation of moderating influence of subject and context type[END_REF]. This study recruited participants from one of the state universities in the Czech Republic using a convenience-based sampling approach which we consider to be most practical in this case. This study uses both online and self-administered surveys, nevertheless, most of the completed responses were from the self-administered questionnaire. Because we wanted to ensure that those who participated in the study have fairly good internet experience with online purchases, in the endparticularly after deleting responses from six non-online shoppers-we had in total 345 valid responses. Therefore, the empirical focus is on existing online shoppers.

The majority of sample respondents were female (59%), aged between 17-24 (80%), and undergraduates (66%). In this study, statistical analyses were performed using both IBM SPSS and WarpPLS [START_REF] Kock | WarpPLS 6.0 user manual[END_REF]. Finally, the research constructs -except for demographics -were measured using a five-point scale (ranging from completely disagree to completely agree).

Construct measurement validation

In order to improve the face and construct validity of the research constructs, constructs were adapted constructs from the literature. In particular, the measures for customer service experience consciousness, perceptions regarding the use of online ads and price comparison websites were based on Osakwe and Chovancova (2015), while the measure for consumer innovativeness was based on [START_REF] Daghfous | Values and adoption of innovations: A crosscultural study[END_REF] and finally the measure for eSwitching was modified from [START_REF] Kim | A study of factors that affect user intentions toward email service switching[END_REF] in addition to reading from the broader literature. The research hypotheses were tested by using the PLS-path modeling technique and precisely using mode A algorithm. The inspected composite reliability scores were as follows: 0.85 (online ads perceptions/OAD), 0.84 (price comparison websites use/PCWs), 0.80 (shopper innovativeness/INNOV), 0.71 (customer service experience consciousness/CSEC), and 0.74 (eSwitching behavior/eSWITCH). At the same time, all indicator loadings and weights were statistically significant at p<0.01, besides all the indicator loadings but two exceeded the 0.6 scores required for this kind of exploratory work. In terms of convergent validity, average variance extracted (AVE) scores range from 0.59 (OAD), 0.58 (PCW), 0.58 (INNOV), 0.46(CSEC), to 0.49 (eSWITCH). Although not reported here, following Fornell and Larcker (1981) discriminant validity was established for the constructs.

Structural Model

Model fit and quality criteria were inspected based on SRMR and R-squared contribution ratio (RSCR). We obtained 0.09 (SRMR value and thus acceptable since it is less than 0.1) and RSCR scores of 0.99 (which approximates to the ideal cut-off value of 1) [START_REF] Kock | WarpPLS 6.0 user manual[END_REF]. Regarding the hypothesized relationships, there is evidence for all but two (see Table 1 for details). Notably, the control variable i.e. gender neither statistically impacted price comparison websites use nor eSwitching. Finally, model predictive power concerning shoppers' use of PCW was 14%, whereas for eSwitching it was 30%; meaning that the empirical model explains about 14% and 30% variations in the use of price comparison websites and eSwitching respectively.

Short discussion and conclusion

This study has been able to identify antecedent factors leading to switching behaviour in the context of service and in particular in online stores beyond the usual suspects in the literature, for instance, attitudes towards switching (cf. [START_REF] Pourabedin | Customers' online channel switching behavior: The moderating role of switching cost[END_REF]. Through the consumer empowerment paradigm, we find, not surprisingly, the perceived use of price comparison websites relates strongly with eSwitching. This novel finding in some ways mirrors the conclusion in past research about the role that searchintentions play in customers' channel switching [START_REF] Gopta | An empirical study of consumer switching from traditional to electronic channels: A purchase-decision process perspective[END_REF]). The point is that shoppers who use price comparison websites mainly use it for bargain hunting. This suggests that to reduce this positive effect on online switching behaviour, online retail merchants, particularly with a focus on young shoppers, will need to do more in the area of sales promotion and loyalty coupons as this might be one of the most effective ways to reduce the incidence of eSwitching and even customer churn.

Also, we find that a higher possession of the following traits in shoppers namely innovativeness and their perception of the customer service experience empowers these shoppers to engage substantively in online switching behavior. Shopper innovativeness had the greatest impact on eSwitching. Since it has been suggested that individuals who are more likely to experiment with new ideas and/or products are more prone to switching [START_REF] Bhattacherjee | User switching of information technology: A theoretical synthesis and empirical test research[END_REF][START_REF] Xu | Exploring individuals' switching behaviour: An empirical investigation in social network games in China[END_REF] and perceived innovativeness of the services provider inhibits customer switching intentions [START_REF] Malhotra | Exploring switching behavior of us mobile service customers[END_REF], the study's finding, therefore, is a reinforcement to extant research.

Because shoppers who possess a higher level of service experience conscientiousness than others may be more prone to service dissatisfaction, the finding, therefore, mirrors previous discussions about the role of customer dissatisfaction in customer switching behaviour (cf. [START_REF] Chuang | Research on customer switching behavior in the service industry[END_REF][START_REF] Fan | Why do users switch to a disruptive technology? An empirical study based on expectation-disconfirmation theory[END_REF]. Moreover, as predicted and consistent with previous research (Osakwe & Chovancova, 2015), this study finds that positive perceptions concerning online ad usefulness, in addition to service expectations, increasingly empower shoppers to use price comparison websites.

Although this study initially proposed that consumer innovativeness and perceived use of price comparison websites are strongly related, evidence, however, shows it to be marginal, at best. Therefore, further research is needed to explore not only this insignificant finding but even further the supported research evidence reported in this paper. In other words, there is a need for more analysis on the research issues discussed in this work because until they are reassessed our findings are at best preliminary and limited to a specific sample. Furthermore, since the strength of relationships was never hypothesized, it is important therefore for future analysis to validate the assumption that shopper innovativeness, compared to others, has the strongest impact on online switching behaviour. Meanwhile, an important limitation of this analysis is that it was conducted using a student population and so makes it difficult to generalize beyond the target population. This consequently reinforces our call for further research on this topic. Finally, this study despite its limitations has added to the customer switching behaviour literature in addition to the heavily under-researched research stream of price comparison websites through the demonstration of the antecedents for eSwitching and shoppers use of price comparison websites based on the consumer empowerment paradigm.

  Griffin, 2014; Hudders et al., 2019; Osakwe & Chovancova, 2014; Xu et al., 2013;

  al., 2012; Fan & Suh, 2014; Gopta et al., 2004; Malhotra & Malhotra, 2013; Mosavi et al., 2018; Pourabedin et al., 2016). Multiple reasons exist for this kind of behaviour (Chuang & Tai, 2016; Keaveney, 1995; Malhotra & Malhotra, 2013; Mosavi et al., 2018; Zhang et al. 2012)

  al., 2015; Broeckelmann & Groeppel-Klein, 2008, Osakwe & Chovancova, 2015; Passyn et al., 2013). Osakwe and Chovancova (2015:597) describe price comparison websites as "a near-frictionless marketing intermediary that can drive down online shoppers' search costs".

  al., 2002; Khan et al., 2015; Meyer & Schwager, 2007;

Table 1 :

 1

	Structural Model statistics
	Hypothesis	β (t-ratios)	p-values	Significant /Not
	H1	.19 (3.26)	<.01	Yes
	H2	.36 (6.31)	<.01	Yes
	H3	.04 (.51)	.30	Not
	H4	.29 (4.58)	<.01	Yes
	H5	.26 (4.88)	<.01	Yes
	H6	.20 (4.36)	<.01	Yes
	H7	.03 (.49)	.31	Not

Acknowledgement

This work was supported by the Internal Grant Agency of FaME through TBU in Zlín No. IGA/FaME/2020/002; and further by the financial support of research project NPU I no. MSMT-7778/2020 RVO -Digital Transformation and its Impact on Customer Behaviour and Business Processes in Traditional and Online markets.


Kuttimani Tamilmani
email: kuttimani.tamilmani@gmail.com

Nripendra P Rana

Yogesh K Dwivedi
email: ykdwivedi@gmail.com

Hatice Kizgin
email: h.kizgin@bradford.ac.uk

Consumer Mobile Shopping Acceptance Predictors and Linkages: A Systematic Review and Weight Analysis

Keywords: Mobile Shopping, Weight Analysis, continuous intention

Mobile phones have become an integral part of human lives with majority of people using them to access product and services for their day-today needs. However, mobile shopping adoption across the globe is not wide or fast as expected. In addition, the research is very scant in understanding various predictors of consumer adoption towards mobile shopping. The objective of this study is to identify most significant and non-significant predictors of consumer mobile shopping acceptance. Systematic review and weight analysis on 34 mobile shopping studies revealed researchers mostly employed TAM and UTAUT model as theoretical lens. This study found an interesting revelation that extrinsic motivation variables such as social influence and perceived usefulness determine consumer mobile shopping behavioral intention during early stages. However, in later stages intrinsic motivation variables such as satisfaction and trust play crucial role to emerge as best and promising predictor of consumer continuous intention respectively.

Introduction

Mobile technologies are the most adopted form of consumer technology across the world in 21 st century with 5 billion unique mobile subscribers in 2017, which encompasses two thirds of global population [START_REF] Gsmaintelligence | Global Mobile Trends[END_REF]. The characteristics of smartphones with wireless Internet enable consumers to purchase goods and services from anywhere at any time, even in the absence wired broadband connections popularly known as mobile shopping [START_REF] Tan | Mobile shopping: the new retailing industry in the 21st century[END_REF]. It empowers consumer with ability to search, browse, compare, and purchase products and services through wireless handheld mobile devices. And, they can buy range of products and services such as electronics, apparels, housewares, books, tickets, beauty, and grocery to name a few [START_REF] Agrebi | Explain the intention to use smartphones for mobile shopping[END_REF][START_REF] Cheng | High speed rail passengers' mobile ticketing adoption[END_REF][START_REF] Ko | Modeling consumer adoption of mobile shopping for fashion products in Korea[END_REF]. The unprecedented smartphones adoption rate is in turn fuelling the mobile shopping growth to reshape the online retail environment. Leading market research firm Statista report suggests that mobile e-commerce is poised for growth globally and could possibly rake in upwards of 3.5 trillion USD constituting almost three quarters (72.9 percent) of all e-commerce sales [START_REF]Mobile E-commerce is up and poised for further grwoth[END_REF]. Mobile phones unique characteristics enable organisations to reach right consumers anytime anywhere through mobile advertising [START_REF] Maneesoonthorn | Texting behaviour and attitudes toward permission mobile advertising: an empirical study of mobile users'acceptance of sms for marketing purposes[END_REF][START_REF] Yang | Exploring factors affecting consumer intention to use mobile advertising in Taiwan[END_REF]. Organisation's spend on mobile advertising is on upward trajectory with a whopping amount of 105.95 billion USD in 2017 and an estimated amount of 175.64 billion USD in 2020 [START_REF]Mobile adverstising spending worldwide from[END_REF].

The above discussion underscores the central role of mobile phones as a medium for shopping to consumers and advertising to organisations respectively. Despite the potential of mobile technology, mobile readiness report on Fortune 500 companies' mobile websites revealed just one-quarter had mobile-responsiveness and majority of the companies were unprepared [START_REF] Mccorkindale | An analysis of the mobile readiness and dialogic principles on Fortune 500 mobile websites[END_REF]. the majority of existing consumer on mobile shopping acceptance studies focused on intention related outcome variables such as behavioural intention [START_REF] San-Martín | Mobile shoppers: types, drivers, and impediments[END_REF][START_REF] Wong | Predicting the consumers' intention to adopt mobile shopping: an emerging market perspective[END_REF][START_REF] Wong | Mobile shopping: the next frontier of the shopping industry? An emerging market perspective[END_REF], purchase intention [START_REF] Chen | Antecedents of customer satisfaction and purchase intention with mobile shopping system use[END_REF][START_REF] Zhou | An empirical examination of the determinants of mobile purchase[END_REF], and continuous intention [START_REF] Chen | What drives consumers' mobile shopping? 4Ps or shopping preferences?[END_REF][START_REF] Chung | Empirical study on determinants for the continued use of mobile shopping apps[END_REF] rather than use behaviour.. Mobile shopping adoption can be achieved at faster rate based on the learning from existing research on this topic across different countries. Existing review articles on mobile shopping mostly provide descriptive information [e.g., [START_REF] Shankar | Mobile shopper marketing: Key issues, current insights, and future research avenues[END_REF][START_REF] Marriott | What do we know about consumer mshopping behaviour[END_REF] without highlighting on the effective predictors necessary for successful adoption. Therefore, the objective of this study is to employ weightanalysis to synthesise existing findings on mobile shopping and identify the most/least frequently used predictors, and among these the best, worst, and promising predictors [START_REF] Tamilmani | Mobile Application Adoption Predictors: Systematic Review of UTAUT2 Studies Using Weight Analysis[END_REF][START_REF] Jeyaraj | A review of the predictors, linkages, and biases in IT innovation adoption research[END_REF]. This study will undertake following steps to fulfil the objective:  Locate consumer focused mobile shopping empirical studies that employed consumer intention/use behaviour-based outcome variables.  Conduct weight analysis on the empirical studies to understand the significant and non-significant path relationships and their performance.

The remaining sections of this paper is structured as follows: The following section i.e. Section 2 describes the research method employed in this study; Section 3 presents the findings of weight analysis and systematic literature review followed by discussion in Section 4 and conclusion in Section 5.

Research Method

This study deemed as a combination of "systematic review", "Keyword search" and "weight-analysis" techniques as appropriate methodology to synthesize the existing research findings on consumer intention and usage towards mobile shopping [START_REF] Tamilmani | Use of 'Habit' is Not a Habit in Understanding Individual Technology Adoption: A Review of UTAUT2 based Empirical Studies[END_REF][START_REF] Tamilmani | Exploring the Role of 'Price Value' for Understanding Consumer Adoption of Technology: A Review and Metaanalysis of UTAUT2 based Empirical Studies[END_REF][START_REF] Tamilmani | A systematic review of citations of UTAUT2 article and its usage trends[END_REF][START_REF] Tamilmani | Social media research in the context of emerging markets: An analysis of extant literature from information systems perspective[END_REF][START_REF] Dwivedi | Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model[END_REF][START_REF] Ismagilova | The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis[END_REF][START_REF] Dwivedi | Use of Social Media by b2b Companies: Systematic Literature Review and Suggestions for Future Research[END_REF][START_REF] Ismagilova | Persuasiveness of eWOM communications: literature review and suggestions for future research[END_REF][START_REF] Waseem | Value co-creation: The role of actor competence[END_REF][START_REF] Juntunen | B2B brands on Twitter: Engaging users with a varying combination of social media content objectives, strategies, and tactics[END_REF].

It employed keyword based search in the Scopus, Web of Science, and EBSCO Business Source complete databases with search terms such as "mobile shopping" OR "m-shopping" OR "mobile purchasing" AND "Adoption" OR "Acceptance" OR "Diffusion" OR "Usage" OR "Intention" to locate articles related to mobile shopping. The initial search from the year 2009 to 2019 resulted in 72 articles. On further screening, it was found that some of the articles were not accessible through researcher's library and numerous studies employed outcome variables other than consumer intention and usage towards mobile shopping. Such instances include but are not limited to outcome variables such as switching intention [START_REF] Chang | Applying push-pull-mooring to investigate channel switching behaviors: M-shopping self-efficacy and switching costs as moderators[END_REF], loyalty [START_REF] Groß | Mobile shopping loyalty: The salient moderating role of normative and functional compatibility beliefs[END_REF], and patronage [START_REF] Aldás-Manzano | Exploring individual personality factors as drivers of M-shopping acceptance[END_REF]. . Therefore, studies that did not report relevant data for weight analysis were also excluded resulting in 34 final manuscripts that focussed only on consumer intention and usage as outcome variable to qualify for weight analysis

Findings

This section presents and explains the findings from the systematic review and weight analysis.

Dominant Theories/Models

Researchers employed as much as thirteen unique theories/models as theoretical lens across the 34 studies to examine consumer intention and usage towards mobile shopping. Table 1 provides summary of dominant theories that are employed on two or more instances. Technology acceptance model (TAM) emerged as the most dominant theory with as much as 12 studies adapting TAM as theoretical lens by often extending the model with external constructs. For instance, Groß [START_REF] Groß | Exploring the acceptance of technology for mobile shopping: an empirical investigation among Smartphone users[END_REF] extended TAM with perceived enjoyment and trust and found these attributes as significant predictor of consumers mobile shopping in Germany. Venkatesh, Morris, Davis and Davis [START_REF] Venkatesh | User acceptance of information technology: Toward a unified view[END_REF]'s , UTAUT theory emerged as the distant second most popular theory with five research investigations. Three studies adapted Expectancy Confirmation Model making it the third most popular theoretical lens in the consumer mobile shopping acceptance arena. Multifaceted trust-risk model and theory of planned behaviour jointly occupied fourth position by serving as theoretical lens on two instances each. Furthermore, there were eight theories/models such as 1) 4P's marketing theory [START_REF] Chen | What drives consumers' mobile shopping? 4Ps or shopping preferences?[END_REF],

2) Behavioural reasoning theory [START_REF] Gupta | Understanding determinants and barriers of mobile shopping adoption using behavioral reasoning theory[END_REF], 3) Elaboration likelihood model [START_REF] Kim | Dual-route of persuasive communications in mobile tourism shopping[END_REF], , 4) Flow theory [START_REF] Gao | Understanding consumers' continuance intention towards mobile purchase: A theoretical framework and empirical study-A case of China[END_REF], 5) IS success model [START_REF] Chen | Antecedents of customer satisfaction and purchase intention with mobile shopping system use[END_REF], 6) Stimulus-Organism-Response (SOR) framework [START_REF] Hew | Mobile social tourism shopping: a dual-stage analysis of a multi-mediation model[END_REF], 7) Technology readiness [START_REF] Celik | Roles of self-monitoring, fashion involvement and technology readiness in an individual's propensity to use mobile shopping[END_REF], and 8) Trust transfer theory [START_REF] Zhou | An empirical examination of the determinants of mobile purchase[END_REF] that researchers employed on one instance each. Finally, there were two studies [START_REF] Amoroso | The importance of institution-based trust in mobile adoption with online shopping applications[END_REF][START_REF] Kim | An empirical analysis of factors influencing M-shopping use[END_REF] that did not employ any dominant theories to examine consumer mobile shopping acceptance.

Weight analysis

Weight analysis technique determines indicative predictive power of an independent variable over dependant variable. This is performed by calculating weight, which is as a ratio of total number of significant relationships between an independent and dependant variable (a) to the total number of all relationships between these two variables (b) and thus weight is calculated using formula (a)/(b) [START_REF] Jeyaraj | A review of the predictors, linkages, and biases in IT innovation adoption research[END_REF].

Coding independent and dependent variables

This study employed generalized coding scheme adapted from Jeyaraj, Rottman and Lacity [START_REF] Jeyaraj | A review of the predictors, linkages, and biases in IT innovation adoption research[END_REF], to uniformly code findings between various independent and dependant variables among the 34 consumer mobile shopping studies. The coding template comprised of 'rows' and 'columns. Each row in the template represented one of the 34 studies, while each column represented the path relationship between an independent and a dependant variable. The intersection points between studies in a "row" and path relationship in the "column" captured the significance of the particular path relationship corresponding to that study. The coding scheme has four different values: 1) '+1' in the case where the path relationship examined was significant and hypothesized in positive direction; 2) '-1' in the case where the path relationship examined was significant and hypothesized in negative direction; 3) '0' in the case where the path relationship examined was non-significant; and 4) "Blank" when the relationship was not studied [START_REF] Jeyaraj | A review of the predictors, linkages, and biases in IT innovation adoption research[END_REF]. This study thoroughly examined all the hypotheses in the 34 articles to identify various dependent and independent variables that researchers employed to examine consumer mobile shopping acceptance. The examination resulted in identifying 41 independent variables, five dependent variables, and 59 different path relationships among these independent and dependent variables. However, the findings of this study are limited to path relationships that are examined on two or more instances. This resulted in final 14 independent variables, three dependant variables i.e. behavioural intentional, continuous intention, and use behaviour and their 20 path relationships. Table 2 provides summary and definition of the final 14 independent variables ranging from anxiety to trust in mobile vendor and three dependent variables. The extent to which individuals have positive or negative evaluation about the behaviour under question [START_REF] Ajzen | The theory of planned behavior[END_REF].

Groß [START_REF] Groß | Heterogeneity in consumers' mobile shopping acceptance: A finite mixture partial least squares modelling approach for exploring and characterising different shopper segments[END_REF]; Gupta and Arora [START_REF] Gupta | Understanding determinants and barriers of mobile shopping adoption using behavioral reasoning theory[END_REF]; Yang [START_REF] Yang | Determinants of US consumer mobile shopping services adoption: implications for designing mobile shopping services[END_REF]; Yang [START_REF] Yang | Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior[END_REF]

Compatibility

The degree to which an innovation is perceived to be consistent with the values, past experiences, and needs of potential adopters [START_REF] Rogers | Diffusion of Innovations[END_REF].

Lu and Yu-Jen Su [START_REF] Lu | Factors affecting purchase intention on mobile shopping web sites[END_REF], Wong, Tan, Ooi and Lin [START_REF] Wong | Mobile shopping: the next frontier of the shopping industry? An emerging market perspective[END_REF] 4 Facilitating Conditions

The degree to which an individual believes that an organisational and technical infrastructure exists to support use of the system [START_REF] Venkatesh | User acceptance of information technology: Toward a unified view[END_REF].

Tan and Ooi [START_REF] Tan | Gender and age: Do they really moderate mobile tourism shopping behavior?[END_REF]; Yang [START_REF] Yang | Determinants of US consumer mobile shopping services adoption: implications for designing mobile shopping services[END_REF] 5 Perceived Behavioural Control Individuals perception of his/her capability to performing a behaviour of interest [START_REF] Ajzen | The theory of planned behavior[END_REF].

San-Martín, López-Catalán and Ramón-Jerónimo [START_REF] San-Martín | Mobile shoppers: types, drivers, and impediments[END_REF], Yang [START_REF] Yang | Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior[END_REF] 6 Perceived

Ease of Use

The degree to which a person believes that using a particular system would be free of effort [START_REF] Davis | Perceived usefulness, perceived ease of use, and user acceptance of information technology[END_REF].

Hew, Leong, Tan, Lee and Ooi [START_REF] Hew | Mobile social tourism shopping: a dual-stage analysis of a multi-mediation model[END_REF], Natarajan, Balasubramanian and Kasilingam [START_REF] Natarajan | The moderating role of device type and age of users on the intention to use mobile shopping applications[END_REF], Saprikis, Markos, Zarmpou and Vlachopoulou [START_REF] Saprikis | Mobile shopping consumers' behavior: an exploratory study and review[END_REF], Tan and Ooi [START_REF] Tan | Gender and age: Do they really moderate mobile tourism shopping behavior?[END_REF] 7 Perceived Enjoyment

The extent to which the activity of using a computer/particular system is perceived to be enjoyable in its own right, apart from any performance consequences that may be anticipated [START_REF] Davis | Extrinsic and intrinsic motivation to use computers in the workplace[END_REF]. The degree to which a person believes that using a particular system would enhance his or her job performance [START_REF] Davis | Perceived usefulness, perceived ease of use, and user acceptance of information technology[END_REF].

Natarajan, Balasubramanian and Kasilingam [START_REF] Natarajan | The moderating role of device type and age of users on the intention to use mobile shopping applications[END_REF], Tan and Ooi [START_REF] Tan | Gender and age: Do they really moderate mobile tourism shopping behavior?[END_REF], Wong, Tan, Ooi and Lin [START_REF] Wong | Mobile shopping: the next frontier of the shopping industry? An emerging market perspective[END_REF] Innovativeness

The willingness of an individual to try out any new information technology [START_REF] Agarwal | A conceptual and operational definition of personal innovativeness in the domain of information technology[END_REF].

Natarajan, Balasubramanian and Kasilingam [START_REF] Natarajan | The moderating role of device type and age of users on the intention to use mobile shopping applications[END_REF], Saprikis, Markos, Zarmpou and Vlachopoulou [START_REF] Saprikis | Mobile shopping consumers' behavior: an exploratory study and review[END_REF], Wong, Tan, Ooi and Lin [START_REF] Wong | Mobile shopping: the next frontier of the shopping industry? An emerging market perspective[END_REF] 11 Satisfaction

The psychological or emotional state resulting from a cognitive assessment of the gap between the expectations and the actual performance of an information system [START_REF] Oliver | Measurement and evaluation of satisfaction processes in retail settings[END_REF].

Agrebi and Jallais [START_REF] Agrebi | Explain the intention to use smartphones for mobile shopping[END_REF],Amoroso [START_REF] Amoroso | The importance of institution-based trust in mobile adoption with online shopping applications[END_REF], Natarajan, Balasubramanian and Kasilingam [START_REF] Natarajan | The moderating role of device type and age of users on the intention to use mobile shopping applications[END_REF] 12 Social Influence

The degree to which an individual perceives that important others believe he or she should use the new system [START_REF] Venkatesh | User acceptance of information technology: Toward a unified view[END_REF].

Groß [START_REF] Groß | Heterogeneity in consumers' mobile shopping acceptance: A finite mixture partial least squares modelling approach for exploring and characterising different shopper segments[END_REF], San-Martín, López-Catalán and Ramón-Jerónimo [START_REF] San-Martín | Mobile shoppers: types, drivers, and impediments[END_REF], Tan and Ooi [START_REF] Tan | Gender and age: Do they really moderate mobile tourism shopping behavior?[END_REF], Yang and Forney [START_REF] Yang | The moderating role of consumer technology anxiety in mobile shopping adoption: differential effects of facilitating conditions and social influences[END_REF] 13 Trust

The most important factor for establishing relationships, both of interpersonal and commercial nature between two or more parties that determine their future action [START_REF] Mcknight | What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology[END_REF].

Groß [START_REF] Groß | Exploring the acceptance of technology for mobile shopping: an empirical investigation among Smartphone users[END_REF], Marriott and Williams [START_REF] Marriott | Exploring consumers perceived risk and trust for mobile shopping: A theoretical framework and empirical study[END_REF], Tan and Ooi [START_REF] Tan | Gender and age: Do they really moderate mobile tourism shopping behavior?[END_REF] 14 Trust in mobile vendor

Comprises of consumer's trusting beliefs (e.g. ability, integrity, and benevolence) and their intention to engage in a business relationship with m-vendors by providing personal information, following the mvendor's advice, or making purchases and transferring money directly via smartphone Groß [START_REF] Groß | Impediments to mobile shopping continued usage intention: A trust-riskrelationship[END_REF].

Groß [START_REF] Groß | Impediments to mobile shopping continued usage intention: A trust-riskrelationship[END_REF] Sl.No Dependent Variables

Definition Example citation(s) 1 Behavioural Intention

Represents individual intention to perform an underlying behaviour with stronger intentions leading to higher chances of performing the underlying behaviour [START_REF] Ajzen | The theory of planned behavior[END_REF].

Groß [START_REF] Groß | Exploring the acceptance of technology for mobile shopping: an empirical investigation among Smartphone users[END_REF], Groß [START_REF] Groß | Heterogeneity in consumers' mobile shopping acceptance: A finite mixture partial least squares modelling approach for exploring and characterising different shopper segments[END_REF],

Yang [START_REF] Yang | Determinants of US consumer mobile shopping services adoption: implications for designing mobile shopping services[END_REF] 2

Continuous Intention

This refers to consumers in postpurchase stage, where their consumption experience determines the future behaviour [START_REF] Bhattacherjee | Understanding information systems continuance: an expectationconfirmation model[END_REF].

Gao, Waechter and Bai [START_REF] Gao | Understanding consumers' continuance intention towards mobile purchase: A theoretical framework and empirical study-A case of China[END_REF],Hung, Yang and Hsieh [START_REF] Hung | An examination of the determinants of mobile shopping continuance[END_REF],Kang, Hung, Yang, Hsieh and Tang [START_REF] Kang | Factors affecting the continued intention of mobile shopping[END_REF], Groß [START_REF] Groß | Impediments to mobile shopping continued usage intention: A trust-riskrelationship[END_REF] 3 Use Behaviour The degree and manner in which customers utilise the capabilities of an underlying technology/system [START_REF] Delone | Information systems success: The quest for the dependent variable[END_REF] Groß [START_REF] Groß | Exploring the acceptance of technology for mobile shopping: an empirical investigation among Smartphone users[END_REF], Groß [START_REF] Groß | Heterogeneity in consumers' mobile shopping acceptance: A finite mixture partial least squares modelling approach for exploring and characterising different shopper segments[END_REF]

Dominant predictors of mobile shopping acceptance

Weight analysis classifies independent variables into two types based on the numbers of times the variable is used a predictor on a dependent variable. An independent variable is termed as 'well-utilized' predictor when examined by researchers in five or more studies. Otherwise, the independent variable is considered as an 'experimental' predictor in case of less than five examinations. Furthermore, the independent variable qualifies as the best predicator of dependant variable when they are used in five or more studies (well-utilized) and have a weight of 0.80 or more. On the other hand, independent variable can be considered as a promising predicator when it is used in less than five studies (experimental) and have perfect weight of one [START_REF] Jeyaraj | A review of the predictors, linkages, and biases in IT innovation adoption research[END_REF]. The summary of weight analysis findings for all the three dependant variables behavioural intentional, continuous intention, and use behaviour is depicted in Table 3.

Well Utilized Predictors of Behavioural Intention

Six variables fulfilled the criteria (five or more examinations) to qualify as the well utilized predictor of consumer behavioural intention towards mobile shopping. The following three predictors: perceived usefulness/performance expectancy (examined 11 times, significant 11 times), attitude (examined 8 times, significant 8 times), and social influence (examined 6 times, significant 6 times) fell under the 'best predictor' category. Since, these variables were explored five or more times and have a weight equal to or greater than 0.80. The remaining three 'well utilized' predictors 'perceived enjoyment' (examined 9 times, significant 6 times), satisfaction (examined 5 times, significant 3 times), and perceived ease of use/ effort expectancy (examined 9 times, significant 4 times) having weight of 0.67, 0.60, and 0.44 respectively are termed as least effective predictor and needs further examination.

Experimental Predictors of Behavioural Intention

Notwithstanding the six 'well utilized' predictors on behavioural intention also had seven experimental predictors such as: 1) perceived risk, 2) personal innovativeness, 3) trust, 4) compatibility, 5) anxiety, 6) facilitating conditions, and 7) perceived behavioural control. From the seven aforementioned 'experimental predictors' only two predictors such as: compatibility (examined 2 times, significant 2 times) and perceived behavioural control (examined 2 times, significant 2 times) with perfect weight of one, qualified as the promising predictors of consumer behavioural intention towards mobile shopping.

Predictors of Continuous Intention

There were five dominant predictors in determining consumer continuous intention towards mobile shopping. The first one is satisfaction that qualified both as a well utilized and best predictor of consumer continuous intention with significant results on all five instances of examination. The remaining four predictors such as : 1) trust (examined 3 times, significant 3 times); 2) trust in mobile vendor 3) perceived risk (examined 2 times, significant 2 times); and 4) perceived usefulness/performance expectancy (examined 2 times, significant '0' times) each with less than five examinations emerged as 'experimental predictors'. The first three 'experimental predictors' of continuous intention (trust, trust in mobile vendor, and perceived risk) also qualified as promising predictor perfect weight of one. Meanwhile, perceived usefulness/performance expectancy emerged as the as least effective predictor of continuous intention.

Predictors of Use behaviour

Use behaviour comprised of only two experimental predictors with less than five examination such as 'satisfaction' (examined 2 times, significant 2 times) and 'behavioural intention' (examined 2 times, significant 2 times). This indicates researchers scarcely employed use behaviour as outcome variable in consumer mobile shopping acceptance research. Both the experimental predictors qualified as the promising predictors of use behaviour with perfect weight of one.

Discussion

Literature synthesis on consumer mobile shopping acceptance studies reveal that researchers to date have mostly employed theories such as TAM and UTAUT. These theories were originally developed in the organisational context with major focus on individual employee characteristics and their motivation in using underlying technologies to improve job related outcomes. In addition, perceived usefulness similar to performance expectancy (11 studies) and perceived ease of use (9 studies) similar to effort expectancy the two independent variables of technology acceptance model (TAM) emerged as the most utilized variables emphasising TAM's dominance in individual adoption research. Besides individual characteristics from dominant technology acceptance theories, researchers have scarcely employed theories such as IS success model [e.g., [START_REF] Chen | What drives consumers' mobile shopping? 4Ps or shopping preferences?[END_REF], 72] and flow theory [e.g., [START_REF] Gao | Understanding consumers' continuance intention towards mobile purchase: A theoretical framework and empirical study-A case of China[END_REF][START_REF] Tan | Gender and age: Do they really moderate mobile tourism shopping behavior?[END_REF] to evaluate impact of system characteristics such as system quality, information quality, and system flow experience on consumer mobile shopping acceptance. The preceding discussion reveals researches mostly deployed theories developed in the organisation context as theoretical lens and seldom employed consumer-focused theories such as extended unified theory of acceptance and use of technology (UTAUT2) to examine mobile shopping acceptance.

The weight analysis findings reveal an interesting pattern that the role and relevance of various attributes depend upon the time period when the consumer starts using the underlying technology. The best predictors of consumer behavioural intention, which refers to early and potential users of technology are perceived usefulness, attitude, and social influence. This is followed by compatibility and perceived behavioural control that emerged as most promising predictors with all significant results for early mobile shopping users. However, attributes such as satisfaction, trust, and perceived risk emerged as least effective predictors of consumer behavioural intention. The plausible explanation could be early users haven't utilized the technology enough and/or bought product/service to evaluate their satisfaction, trust, and risk level of both the platform and vendors.

Interestingly, for consumers in the post-purchase stage, 'satisfaction' emerged as the single most well utilized and best predictor of their continuous intention. In addition, attributes such as trust, perceived risk, and trust in mobile vendor emerged as the promising predictor with all significant results. This underscores the significant role of both the platform and vendors in sustaining the existing consumers and influencing their continuous intention for future transactions. The emergence of variables such as Trust in mobile vendor as promising predictor only for continuous intention and not for behavioural intention further validates the role of product/service providers in improving the longevity of consumers towards mobile shopping. Surprisingly, perceived usefulness/performance expectancy that was best predictor of behavioural intention became least effective predictor of consumer continuous intention towards mobile shopping. The plausible explanation for this pattern comes from Hung, Yang and Hsieh [START_REF] Hung | An examination of the determinants of mobile shopping continuance[END_REF] study that extended Expectation-Confirmation model with Trust to examine consumer continuous intention towards mobile shopping. The study results among 244 consumers found that extrinsic motivation variable perceived usefulness became non-significant determinant of continuous intention over time. However, during repurchasing activities, intrinsic motivation variable 'trust' explained the most variance on consumer continuous intention towards mobile shopping followed by Satisfaction. Finally, both Satisfaction and Behavioural intention the two predictors of Use behaviour emerged as promising predictor with all significant results. The preceding discussion indicates Use behaviour is sparingly examined as outcome variable in consumer mobile shopping acceptance. This pattern is understandable as consumer mobile shopping is still nascent stages of acceptance in many parts of the world and researchers trying measures the intention rather than actual behaviour [START_REF] Tamilmani | Mobile Application Adoption Predictors: Systematic Review of UTAUT2 Studies Using Weight Analysis[END_REF]. However, Wu and Du [START_REF] Wu | Toward a better understanding of behavioral intention and system usage constructs[END_REF] meta-analysis on BI and UB caution the notion of IS researchers considering BI as surrogate of UB. Because, individual's user behaviour towards cannot be measured without assessing their actual system usage. Furthermore, Wu and Du [START_REF] Wu | Toward a better understanding of behavioral intention and system usage constructs[END_REF] cautioned research community that they should be circumspect of studies that measure only behavioural intention without investigating use behaviour. Figure 1 depicts the resultant model emerging from weight analysis on mobile shopping empirical studies.

Conclusion

This study identified various predictors of consumer mobile shopping acceptance and their linkage by synthesising findings from extant literature through weight analysis.

The findings emerging from this study is important for future researchers in this domain and practitioners alike. Weight analysis results found among fourteen unique independent variables (Table 3) only four emerged as the best predictor three on behavioural intention (perceived usefulness, attitude, and social influence) and one on continuous intention (Satisfaction). This is followed by five promising predictor two on behavioural intention (compatibility, perceived behavioural control) and three on continuous intention (trust, trust in mobile vendor, and perceived risk), which are more likely candidates to emerge as best predictor in future. Therefore, researchers should continue using promising predictors while investigating consumer mobile shopping acceptance alongside the best predictors. The remaining five final independent variables perceived ease of use, perceived enjoyment, personal innovativeness, anxiety, and facilitating conditions emerged only as least effective predictors on consumer mobile shopping acceptance endogenous variables. Perceived ease of use one of the core construct of TAM, despite being the second most frequently used predicator produced the most non-significant results. Therefore, researchers should be more cautious while operationalizing this type of construct in their research model. They should make necessary adaptations and/or omit irrelevant constructs such as least effective predictors from the model depending upon context rather than having obligation to replicate all the constructs in underpinning model/theory. Moreover, the review found almost half -47% studies in consumer mobile shopping arena employed theories developed under organisational context such as TAM and UTAUT. Therefore, future researchers should employ more consumer focussed theories such as UTAUT2.

Notwithstanding the precautionary measures taken for coding and analysis, the findings of this study is not without its limitations. First the studies involved for weight analysis were limited only to three databases such as Scopus, Web of Science, and EBSCO Business Source complete restricting the total number of empirical studies available for weight analysis. In future, researchers should widen their search horizon to more databases that will increase the number of studies available for analysis and minimize publication bias. Second, weight analysis does not take sample size into consideration like meta-analysis and cannot provide true effect size in a path relationship. In future, researchers should try to combine meta-analysis with weight analysis to calculate the true-effect size of path relationships. Third, this research included studies that employed intention and use related outcome variables pertaining to consumer mobile shopping acceptance. In future, researchers should include all outcome variables to provide comprehensive overview on various outcomes measured in consumer mobile shopping acceptance arena and their predictors. Finally, this study included only quantitative studies that reduced final number of studies available for analysis. Future studies should include both qualitative and quantitative studies in weight analysis.

Table 1 :

 1 Dominant

	Mobile Shopping acceptance theories/models
	Theory/Model	Frequency References
	Technology acceptance model	12 Agrebi and Jallais [3];Chen, Hsu and
	(TAM)	Lu [44]; Groß [35]; Groß [45]; Ko, Kim
		and Lee [5]; Lu and Yu-Jen Su [46];
		Natarajan, Balasubramanian and
		Kasilingam [47]; San-Martín, López-
		Catalán and Ramón-Jerónimo [11];
		Saprikis, Markos, Zarmpou and
		Vlachopoulou [48]; Shang and Wu
		[49];Wong, Lee, Lim, Chua and Tan
		[12]; Wong, Tan, Ooi and Lin [13]
	Unified theory of acceptance and	5 Chau, Seshadri, Broekemier and
	use of technology (UTAUT)	Pamornpathomkul [50]; Lu, Yu, Liu
		and Wei [51]; Tan and Ooi [52]; Yang
		and Forney [53]; Yang [54]
	Expectancy Confirmation Model	3 Chung, Chun and Choi [17]; Hung,
		Yang and Hsieh [55]; Kang, Hung,
		Yang, Hsieh and Tang [56]
	Multifaceted trust-risk model	2 Groß [57]; Marriott and Williams [58]
	Theory of planned behaviour	2 Prodanova, San-Martín and Jimenez
		[59]; Yang [60]

Table 2 :

 2 Most frequently studied variables in mobile shopping

	Sl. No Independent	Definition	Example citation(s)
	Variable
	1 Anxiety	Refers to negative emotions in	Lu and Yu-Jen Su
		cognitive states that are evoked during	[46];Saprikis, Markos,
		actual or imaginary interactions with	Zarmpou and
		underlying behaviour (e.g. Using	Vlachopoulou [48]
		mobile for shopping) [61].
	2 Attitude

Table 3 :

 3 Weight analysis summary approach adapted from Jeyaraj, Rottman and Lacity[START_REF] Jeyaraj | A review of the predictors, linkages, and biases in IT innovation adoption research[END_REF]

	SN Independent Variable	DV Sig	Non-	Total	Weight
			(a)	Sig	(b)	(a/b)
	1 Perceived usefulness/Performance	BI	11	0	11	1.00
	expectancy
	2 Perceived ease of use/ Effort expectancy		4	5	9	0.44
	3 Perceived Enjoyment		6	3	9	0.67

[Legend: BI: Behavioural Intention; CI: Continuous Intention; D.V: Independent Variable; Non-Sig: Number of non-significant path values; Sig (a): Number of significant path values; UB: Use Behaviour]

EE: PU/PE PR TR TRM V SAT T PBC CI BI UB PEOU/EE PEJ ATT SI PIN COM M FC ANX

	Well Utilized Predictor
	Experimental Predictor

[LEGEND: ANX: Anxiety; AT: Attitude; BI: Behavioural Intention; COM: Compatibility; CI: Continuous Intention; FC: Facilitating Conditions; PBC: Perceived Behavioural Control; PEOU/Perceived Ease of Use/ Effort Expectancy; PEJ: Perceived Enjoyment; PR: Perceived Risk; PU/PE: Perceived Usefulness/ Performance Expectancy; PIN: Personal Innovativeness; SAT: Satisfaction; SI: Social Influence; TR: Trust; TRMV: Trust in Mobile Vendor; UB: Use Behaviour] FIG. 1.: Emergent model of mobile shopping weight-analysis


Shiraz Amod

Sumarie Roodt
email: sumarie.roodt@uct.ac.za

How Corporates in South Africa are using Serious games in Business

Keywords: Serious games, serious gaming, corporate, barriers to adoption, awareness, Digital game-based learning, Commercial off the Shelf, serious games in business

It has been shown that serious games are useful in the military, healthcare, and education sectors. Meanwhile corporate interest in serious gaming in business has rapidly grown internationally. However the level of awareness and adoption of serious gaming among South African corporates in business is still unclear. This interpretive study explores South African corporate awareness of serious gaming in business and the barriers to its adoption. Semi-structured interviews were used to collect qualitative data from managers in Johannesburg Stock Exchange-listed companies. Eight participants were interviewed across four different industries. Data analysis was guided by the general inductive approach. The absence of serious gaming adopters among the participants, and the general lack of awareness of serious gaming in business were identified as the most salient features. The analysis suggests that corporates currently use technologies related to serious games (e-learning, collaborative tools, and simulation tools), and that there is a demand for the greater promotion and use of serious gaming. While the findings provide new insights into the level of serious gaming awareness, caution should be exercised when attempting to generalize these findings due to the small sample and the scarcity of prior research.

Introduction

The contribution offers a novel understanding on the adoption and potential use of serious games in corporate business environments. Serious games use the artistic medium of games to deliver a message, teach a lesson, or provide an experience. A serious game is an "interactive computer application, with or without significant hardware component that has a challenging goal, is fun to play and engaging, incorporates some scoring mechanism, and supplies the user with skills, knowledge or attitudes useful in reality" [START_REF] Bergeron | Developing serious games[END_REF]. Studies abound that show the application of serious games in the entertainment, military, healthcare, and education sectors [START_REF] Levin | 3D internet and enterprise: emergence of virtual worlds and serious games in the workplace[END_REF][START_REF] Smith | Game Impact Theory: The Five Forces That Are Driving the Adoption of Game Technologies within Multiple Established Industries[END_REF][START_REF] Zyda | From Visual Simulation to Virtual Reality to Games[END_REF]. However, there are limited studies on the application within the corporate sector. The field of serious games is relatively new and therefore, limited research has been conducted in this area (Azadegan, Riedel, & Baalsrud Hauge, 2012; [START_REF] Levin | 3D internet and enterprise: emergence of virtual worlds and serious games in the workplace[END_REF]. Few studies exist about the application of serious games in the South African business context. Therefore, the study serves to raise corporate awareness of serious games and the potential applications in the context of South Africa business.

2 Literature Review

Definitions

Serious games involve a broader spectrum of uses than Digital Game-Based Learning (Breuer & Bente, 2010; Connolly, Boyle, MacArthur, Hainey, & Boyle, 2012; [START_REF] Michael | Serious games: games that educate, train and inform[END_REF]. DGBL is a term used in the domain of education as it involves the use of digital games primarily for learning purposes [START_REF] Breuer | Why so serious ? On the Relation of Serious games and Learning[END_REF][START_REF] Susi | Serious games -An Overview[END_REF]. Serious gaming relates to the concepts of virtual worlds and DGBL [START_REF] Connolly | A systematic literature review of empirical evidence on computer games and serious games[END_REF][START_REF] Susi | Serious games -An Overview[END_REF]. DGBL found in education involves applying digital games primarily for learning purposes [START_REF] Breuer | Why so serious ? On the Relation of Serious games and Learning[END_REF][START_REF] Susi | Serious games -An Overview[END_REF]. Virtual worlds are "computer-simulated, usually 3-D, representations that allow avatars to interconnect and communicate in relatively lifelike environments" [START_REF] Ives | APC Forum: Business Implications of Virtual Worlds and Serious Gaming[END_REF]). These environments persist; continue to exist and undergo changes even when players are not present [START_REF] Cox | Online and multiplayer gaming -An overview[END_REF] 2012). COTS involves re-purposing an existing game to harness the power of serious games without the risk and expense of developing a bespoke serious game that may not be sufficiently engaging [START_REF] Connolly | A systematic literature review of empirical evidence on computer games and serious games[END_REF]. Both categories of serious games are included in this study.

Application of Serious games

Three broad application areas of serious games in business exist: [START_REF] Azadegan | Serious games Adoption in Corporate Training[END_REF] 2010). Serious games are also employed for demonstrations and education [START_REF] Herrlich | A Tool for Landscape Architecture Based on Computer Game Technology[END_REF][START_REF] Levin | 3D internet and enterprise: emergence of virtual worlds and serious games in the workplace[END_REF]. Serious games provide unique immersive environments that teach complex material [START_REF] Susi | Serious games -An Overview[END_REF]. Serious games aid marketing and performing demonstrations of products or services [START_REF] Herrlich | A Tool for Landscape Architecture Based on Computer Game Technology[END_REF][START_REF] Levin | 3D internet and enterprise: emergence of virtual worlds and serious games in the workplace[END_REF]. COTS games have been suitable for this purpose because of their low cost, fast implementation, and high level of engagement ("flow") [START_REF] Herrlich | A Tool for Landscape Architecture Based on Computer Game Technology[END_REF][START_REF] Rankin | Re-Purposing a Recreational Video Game as a Serious games for Second Language Acquisition[END_REF].

Barriers to Adoption of Serious games

The application of serious games is new, especially in a business context ( In-depth semi-structured interviews were conducted with corporate managers, who were prepared with a briefing on serious games before answering related questions on awareness and adoption. The work follows the study on the adoption of serious games in corporate training in the United Kingdom (Azadegan et al., 2012). The sample consists of eight South African corporations across a range of four industries that includes; Financial Services, Retail, Insurance, and Construction. A qualitative analysis of the interview transcripts was conducted via a thematic analysis. Thematic analysis was performed using open coding and then axial coding to assess the most common uses and barriers to adoption of serious games in South African corporations. To avoid biased results comparative analysis was only performed on the questions that were consistently posed to all subjects.

Results and Data Analysis

Interviews were conducted with eight participants from different South African corporations for this study. For a description of the sample data, the characteristics of the participants are summarized (See Table 1). Participant D became aware of serious gaming (more specifically DGBL) at a learning conference in 2010 where "there was an international speaker and he was very, very keen to bring in some kind of digital gaming for learning into Africa". The other participants who were partially aware of serious gaming understood it in relation to gamification (Participant G), or generally as "a way to aid learning by using technology so that learning is more practical, hands on, [and] simulated" (Participant A). Although there is very little awareness of the concept of serious gaming, there is slightly more aware of the potential benefits that gaming can provide in a corporate context. Four of the eight participants acknowledged the benefits of serious gaming: -Participant G Participants were more aware of the limitations than the benefits or the concept of serious games. Five of the eight participants (63%) identified limitations of gaming in the corporate environment. Although more participants were more aware of the limitations than benefits of serious games, their descriptions of the limitations were less detailed and more abstract than descriptions of the benefits. Limitations include; the impracticality of using games for certain business activities: "You're not going to be able to convert every kind of organisational functioning into some sort of gaming con-cept…without losing something in the process" (Participant G), and target audiences: "…it probably depends on the target audience… I think it would be very suited for the new generation of trainees or staff" (Participant F). Participant B highlighted the need for a broader strategic programme to ensure serious games are used appropriately: "They should be effective within a proper context of a strategy to utilise learning technology to support development of [the] businesses".

Positive relationship exists between the participants' level of awareness and their attitude towards serious gaming. As participants' awareness of serious gaming (the concept, benefits and limitations) improve, attitude towards serious gaming became move toward positive. An exception to this rule is Participant G who demonstrated higher than average awareness of serious gaming and was not particularly positive about the prospects of serious gaming. Upon closer review, it became apparent that the lack of positivity shown by Participant G is not directed at serious gaming in general, but specifically at using serious gaming within her particular company: "I think there is value [in serious games]…you've got to be careful that you don't try and take the next biggest thing and make it the only thing, especially depending on the kind of business we have…It's not an easy fit for the kind of business we are. We're an insurance business…a more traditional kind of conservative business. The profile of employee and customer we have are probably not your target market for that typically." -Participant G A considerably low level of serious gaming awareness (13%) is a significant result. The observation is even lower than the result of Azadegan et al (2012) of awareness in the UK (29%). The low level of awareness is likely to affect the results of the subsequent section on "Barriers to Adoption of Serious Gaming" because little is known about the concept of serious gaming itself. Participants correctly identified the potential of serious gaming for education and simulations; however, none identified the potential for collaboration or demonstrations. This could indicate that the participants understand serious gaming in a narrow scope, relating only to training.

Analysis performed is on the barriers to adoption of serious gaming using the framework defined by Azadegan et al (2012) and the results summarized in Table 3. All participants reported that their lack of familiarity with serious gaming was a barrier to its adoption. The prevalence of familiarity barriers is significant, but expected, considering the preceding findings on the low level of serious gaming awareness. Practicality barriers are the second most common reason for not adopting serious gaming, as indicated by three participants (38%). The barriers that participants described least were financial barriers (13%) and the lack of IT facilities and support (13%).

Lack of familiarity is more than telling as a barrier to serious gaming adoption. To analyse the data further, barriers because of familiarity is distinguishable under five related themes. The themes are game perceptions, the lack of promotion of serious gaming, the need for proven cases, unfamiliarity with the technology, and unaware of the concept of serious gaming. Refer to Table 4 distribution of these themes across the various participants. Half the number of participants, i.e., 50% were unaware of the concept of serious games. These participants were unable to identify other barriers to adopting serious gaming because they were uninformed of this concept, its requirements, and limitations: "I don't know much about the field…I need to get more information before I can comment" (Participant C). The other half of the participants had some amount of awareness of the concept of serious games. This informed 50% of the sample; all mentioned the lack of promotion of serious gaming (75%) and/or called for the need for publicizing cases of serious gaming implementations (50%). Calls for promotion of serious games in corporate and demand for public cases that had a serious games implementation. Participant G, who was not positive towards serious gaming, hinted at the power of successful case studies: -Participant G Three participants mentioned issues relating to a lack of familiarity with the technology involving serious gaming. However, the accuracy of these issues is questionable as the statements were speculative and vague: "…there's also stuff around tech-savviness, you know…" (Participant G), "I'll leave that up to our IT departments who actually do that…" (Participant F), Participant A was the only participant to suggest that negative perceptions of games, that games are easy and do not add value, among the decision makers would affect the company's adoption of serious gaming.

Only one participant (13%) described financial barriers for adopting serious gaming:

"…to set up something like that is always costly to start with and then you realise the benefits of the learning but they don't give it quite the chance because most of us operate on the low cost operating model, so initial setup is always difficult."

-Participant D

The use of serious gaming was considered impractical firstly because of the nature of the business itself: "Our environment…doesn't lend itself well to gaming" (Participant A); and "It's not an easy fit for the kind of business we are" (Participant G). Secondly, serious gaming is impractical for the type of people the company employs: "The profile of employee and customer we have are probably not your target market for that typically" (Participant G). Thirdly, the absence of the skills needed to implement serious gaming, is why it may consider it as impractical. As explained here "I think it can be done I just don't know how it can be done" (Participant F); and "I think it's a very specialist set of expertise that know how to really utilize the serious gaming or the gamification concepts in the right way. We probably don't have that here" (Participant G).

Participant A was the only one (13%) to mention the lack of IT facilities and support as a barrier to adoption of serious gaming. This observation conflicts with the finding of Azadegan et al (2012) who identified that 45% of companies in the United Kingdom experienced barriers related to their IT facilities and support. Given the low level of serious gaming awareness, this inconsistency is likely to be the result of insufficient awareness regarding the IT requirements of serious gaming (as with the case of financial barriers). Data obtained suggests that there is interest in serious gaming, but possibly not enough interest for companies to embark on serious games. The call for greater promotion of serious gaming and successful case studies reflects an appeal for either a driver of serious gaminganother corporate or a vendor of serious games.

Only one participant (13%) mentioned that the perception of games might have a negative impact on their company. This observation is lower than Azadegan (18%), which is a positive indication for the future of serious gaming in South Africa.

Practicality barriers identified relate to the lack of skills for serious gaming, or the limitations of serious games. Scarcity of serious gaming skills is due to widespread lack of awareness and the adoption. The more companies adopt serious gaming, the more people would acquire the skills necessary to teach and learn the use of serious games. Considering the low level of serious gaming awareness, companies may already possess the skills for using serious gaming that is yet unrecognized by them.

The inability of most participants to identify barriers in terms of finance and IT facilities and support is a further indication of low awareness of serious gaming. South Africa presents numerous relevant IT challenges, such as the high cost of internet bandwidth [START_REF] Gillwald | Between two stools: broadband policy in South Africa[END_REF]. Azadegan et al (2012) found that 45% of companies identified IT facilities and support barriers, compared with 13% in this study. This to mean that participants' inability to identify these barriers indicates a low level of readiness to adopt serious gaming in South Africa. Analysis carried out on the use of technologies related to serious gaming for each participant. This examination assists in knowing the extent of each participant's technology profile and inclination to use technologies like serious gaming. The technologies of interest are electronic learning, collaborative tools, and simulation tools. For the result of that summarize the analysis, refer to Table 5 Seven participants (88%) reported that they currently use two or more of the related technologies in their corporations. Five participants (63%) currently use all three technologies (E-learning, collaborative tools and digital simulations). Participant H is the only participant that does not use any related technologies.

Digital simulations were used by 88% of participants, and 38% also used physical simulations. The purpose of the simulations was to teach system usage or to simulate a business process as part of training. The extensive use of related technologies by the participants demonstrates their awareness of the technologies and they had the capabilities for implementing them. This implies the participants have the willingness, budget, and skills to implement technologies like serious gaming. The participants with the least use of related technologies are Participant C and Participant H, both of which are in the construction industry. This result may be an indication that the construction industry in general is averse to the related technologies, or that the technologies are impractical in the construction industry. The former is more likely to be true considering the potential of serious gaming for improving construction site safety [START_REF] Connolly | A systematic literature review of empirical evidence on computer games and serious games[END_REF] and visualizing landscapes and architecture [START_REF] Herrlich | A Tool for Landscape Architecture Based on Computer Game Technology[END_REF].

On the potential for Serious Gaming in South Africa and based on the feedback from participants, there appear to be various opportunities for the use of serious gaming in South Africa. A benefit of serious gaming that is relevant to the participants is its ability to assemble groups of geographically dispersed people. These virtual gatherings are beneficial for corporations because they enable collaboration and training on a large scale without the associated travel and lodging expenses. Data suggests that serious gaming may be useful for dealing with geographically dispersed employees. This observation supports the finding of [START_REF] Ives | APC Forum: Business Implications of Virtual Worlds and Serious Gaming[END_REF] who identified the benefits by using serious games to connect dispersed people in a virtual world. The data indicates a demand for technology that will improve access to knowledge and reduce operating costs. [START_REF] Connolly | A systematic literature review of empirical evidence on computer games and serious games[END_REF] found that serious gaming improves knowledge acquisition, which suggests that the participants will be more inclined to adopt serious gaming if it is not more expensive than their current training methods.

Conclusion

The researchers show that none of the participating corporations had used serious gaming and only one participant (13%) was aware of the concept. Familiarity barriers were the most common reason for not adopting serious gaming (100%), highlighting the scarcity of serious gaming knowledge. A key finding was the demand for greater promotion of serious gaming and publicised cases of serious gaming implementations. The majority of participating corporations were interested in serious gaming, although previously unaware of it, and sought more information on the topic. This could represent an opportunity for a serious gaming vendor to enter the South African market and drive the adoption of serious gaming. Another key finding to emerge from the data was the widespread use of e-learning, collaborative tools, and simulation tools. By providing an outline of the current state of South African corporations, this study forms the foundation for future research into the adoption and usage of serious games. This research may be of particular interest to South African corporate considering the use of serious gaming, as well as serious games vendors.

"

  …if we could get some practical, tangible case studies and examples of businesses like ours who are utilising it in certain spheres, [we] might find that there's more opportunity than we think. I might change my mind".

  [START_REF] Susi | Serious games -An Overview[END_REF]. Games offer a simulated environment in which training exercises can be performed, much like real-life training simulations[START_REF] Graafland | Systematic review of serious games for medical education and surgical skills training[END_REF][START_REF] Susi | Serious games -An Overview[END_REF]. There are benefits of using serious games over traditional forms of training. Serious games present a safe environment for

	conducting
	training in a simulated environment; (2) as a platform for collaboration; and (3) as a
	tool for demonstrations and education (Fernandes et al., 2012; Herrlich, 2007; Ives &
	Junglas, 2008; Levin, 2010; Michael & Chen, 2006).
	Training conducted with serious games, especially in simulated environments is
	prevalent (Michael & Chen, 2006; , 2012). The MUVEs provide a virtual
	environment that players can communicate and collaborate to jointly achieve their goals
	(Fernandes et al., 2012). Collaboration enables people in different locations to
	collaborate effectively without needing to travel or for expensive teleconferencing
	technologies to be purchased (Bozanta et al., 2012; Fernandes et al., 2012; Levin,

performing training

[START_REF] Graafland | Systematic review of serious games for medical education and surgical skills training[END_REF][START_REF] Oliveira | Serious games in Security: A Solution for Security Trainees[END_REF]

. The simulation of a real life activity allows skills to be fine-tuned through practice in a risk-free environment without consequence

(Graafland et

al., 2012; Oliveira et al., 2012). Serious games can also be deployed as a collaborative platform among multiple people (Bozanta, Kutlu, Nowlan, & Shirmohammadi, 2012; Fernandes et al., 2012; Oliveira et al., 2012). Using the internet as a communication medium enables serious games to provide Multi-User Virtual Environments (MUVEs) in the form of virtual worlds (Bozanta et al.

  The primary research question asks, "What is the state of use of serious games by South African corporations in a business context?" Secondary questions asked include:[START_REF] Azadegan | Serious games Adoption in Corporate Training[END_REF] What is the level of awareness of serious games within South African corporates?[START_REF] Azadegan | Serious games Integration in Companies: A Research and Application Framework[END_REF] What uses for serious games are South African corporates embracing? (3) What barriers are preventing the adoption of serious games by South African corporates?

	terms of the practicality of serious games (practicality barriers), and the level of Infor-
	mation Technology facilities and support (IT facilities and support barriers) (Azadegan
	et al., 2012)
	3	Materials and Methods
		Azadegan et
	al., 2012). Companies which are unaware of serious games will not adopt them, and
	those which are aware of the concept, but not of the benefits are equally unlikely to
	adopt serious games (Azadegan et al., 2012). Perceptions of employees and managers
	towards games heavily influence the likelihood of adoption (Azadegan et al., 2012; Ives
	& Junglas, 2008). Games perceived as easy and not contributing to training or promot-
	ing the company's purpose, will not be adopted (Azadegan, Riedel & Hauge, 2012;
	Ives & Junglas, 2008). Based on the work by Azadegan et a. (2012) in the area of seri-
	ous game adoption in businesses, four categories of barriers are identified: barriers with
	familiarity about serious games (familiarity barriers), financial barriers, barriers in

Table 1 :

 1 Overview of Participants

	Name	Organizational Role	Industry
	Participant A	Training Manager	Financial Services
	Participant B	Executive Manager: Learning and Devel-opment	Retail
	Participant C	Skills Development Manager	Construction
	Participant D	Learning and Growth Partner	Retail
	Participant E	Human Resources Programs Manager	Insurance
	Participant F	Training and Methodology Manager	Financial Services
	Participant G	Executive Head of Training	Insurance
	Participant H	General Manager	Construction

Table 2 :

 2 Awareness of Serious Gaming Concepts

		Participant
				%
	Area of Awareness	A B C D E	F G H
	Concept Awareness	No No No Yes No No No No	13%
	Partial Concept Awareness	Yes No No No No No Yes No	25%
	Benefits Awareness	Yes No No Yes No No Yes No	38%
	Partial Benefits Awareness	No No Yes No No No No No	13%
	Limitations Awareness	Yes Yes No Yes No Yes Yes No	63%

cater more to individuals."

	like something you'll do it over and over again, you would probably be learning much
	more."
	-Participant D
	"…introducing a gaming element provides an experience that people almost learn while
	they play kind of thing. So I think if you're looking to
	-Participant A
	pany."
	-Participant C
	"If you continuously use gaming I think you are able to learn concepts faster without even
	realising that you are, you know, by the very repetitive nature of gaming, because if you

"…you're able to engage more as a learner…I think one of the big advantages is you can learn alone, you don't always have to rely on group learning. One of the disadvantages of group learning is that you sometimes have to go at the pace of the average learner, so your slower learners need more attention and your quicker learners actually get quite impatient.

So when you're able to engage with technology, you can "It could even be used in our company which is a construction company and it could be used in simulation for our [crane] operators which could be very beneficial to the com-

drive up knowledge and skill levels, using gaming techniques can help do that in the business context other

	than, sort of,
	traditional training methods."

Table 3 :

 3 Barriers to Adoption

		Participant
	Type of Barrier	A B C D E	F G H	%
	Familiarity Barriers	Yes Yes Yes Yes Yes Yes Yes Yes 100%
	Financial Barriers	No No No Yes No No No No 13%
	Practicality Barriers	Yes No No No No Yes Yes No 38%
	IT Facilities & Support Barriers	Yes No No No No No No No 13%

Table 4 :

 4 Breakdown of Familiarity Barriers

				Participant
	Theme	A	B	C	%

Table 5 :

 5 The use of Related Technologies

					Participant
	Technology	A	B	C	D	E	F	G	H	%
	E-

Learning Yes Yes No Yes Yes Yes No No 63% Collaborative Tools Yes Yes Yes Yes Yes Yes Yes No 88% Digital Simulations Yes Yes Yes Yes Yes Yes Yes No 88% Physical Simulations No No No No Yes Yes Yes No 38%