Advertisement

Information Systems Frontiers

, Volume 20, Issue 3, pp 503–514 | Cite as

The Impact of Social Media on Consumers’ Acculturation and Purchase Intentions

  • Hatice KizginEmail author
  • Ahmad Jamal
  • Bidit Lal Dey
  • Nripendra P. Rana
Open Access
Article

Abstract

Social media has emerged as a significant and effective means of assisting and endorsing activities and communications among peers, consumers and organizations that outdo the restrictions of time and space. While the previous studies acknowledge the role of agents of culture change, it largely remains silent on the role of social media in influencing acculturation outcomes and consumption choices. This study uses self-administered questionnaire to collect data from 514 Turkish-Dutch respondents and examines how their use of social media affects their acculturation and consumption choices. This research makes a significant contribution to consumer acculturation research by showing that social media is a vital means of culture change and a driver of acculturation strategies and consumption choices. This study is the first to investigate the role of social media as an agent of culture change in terms of how it impacts acculturation and consumption. The paper discusses implications for theory development and for practice.

Keywords

Social media Language preferences Enculturation Acculturation Purchase intentions 

1 Introduction

The twentieth century has witnessed a significant rise in cultural diversity across the Western world (Coleman 2008; Eurostat 2015; Schwartz et al. 2010) and increasing interdependence and integration throughout the world (Jamal 2005). Accordingly, the marketplace is characterised by market integration and persistent differentiations that are due to ethnic, racial, religious and national interests (Peñaloza and Gilly 1999). Migration and related issues are hotly discussed and debated topics in many Western countries, where ethnic-minority consumers are the fastest-growing segment of the population (Jamal 2005; Schwartz et al. 2010).

A substantial body of research investigates the consumption patterns of immigrant ethnic-minority consumers using an acculturation framework (Askegaard et al. 2005; Jamal et al. 2015; Peñaloza 1994). Acculturation refers to the culture change that takes place as a result of contact with culturally dissimilar people, groups and environments (Berry 1992; Laroche and Jamal 2015), whereas enculturation refers to the process of learning one’s own culture (Kizgin et al. 2017; Schwartz et al. 2010).

Such ethnic-minority consumers have multiple and co-existing identities, as they navigate among heritage, host and global consumer cultures (Askegaard et al. 2005; Jamal 2003; Oswald 1999). In doing so, they face a variety of agents of culture change (e.g., family, friends, schools, religious and cultural institutions, traditional and new media) that impact their acculturation outcomes, especially the extent to which they integrate into the host society or retain their original cultural values and traditions.

While previous research acknowledges the role of agents of culture change (Askegaard et al. 2005; Kizgin et al. 2017; Peñaloza 1994), it largely ignores the role of social media in influencing acculturation outcomes and consumption choices. Social media has emerged as an important and effective means of supporting and promoting activities and interactions among peers, consumers and organizations that transcend the boundaries of time and space (Erkan and Evans 2016; Jin 2012; Sharma et al. 2013; Tang et al. 2015). A range of online communication channels, including interpersonal communication (e.g., Twitter, Facebook), content communities (e.g., Wikipedia) and multimedia platforms (e.g., YouTube, Instagram), offer individuals and businesses the ability to connect, develop and maintain social and business relationships through the exchange of ideas and opinions (e.g., Alalwan et al. 2017; Alryalat et al. 2017; Ellison and Boyd 2013; Ellison et al. 2007; Filieri et al. 2015).

Generally speaking, immigrant ethnic minorities have collectivistic cultural tendencies, and they may use social media as a mechanism for generating social and cultural capital (Li et al. 2004). In such a context, questions emerge concerning whether ethnic-minority consumers prefer to communicate with others on social media in their native language, the impact of such a preference on acculturation and consumption choices, and whether they interact and communicate on social media mainly with people of their own cultural background. This study addresses these questions and makes a significant contribution to consumer acculturation research by demonstrating that social media is an important agent of culture change and a driver of acculturation strategies and consumption choices.

We organize the remainder of this paper into four sections. The first section develops a conceptual framework that is used to identify a number of research hypotheses and then reviews the literature that discusses the relevance of consumer acculturation to social networks on social media. The second section describes the data-collection procedure, the measures adopted, and the results. The final section discusses findings and assesses implications for academics and practitioners.

2 Literature Review

2.1 Consumer Acculturation and Social Networks

Acculturation is the process of learning a new culture, so consumer acculturation refers to acquiring the skills and knowledge that are needed to engage in consumer behaviour in one culture by members of another culture. In the case of immigrants, these lessons include how to buy and consume products and services in a new country and the meanings that they attribute to themselves and others as consumers (Peñaloza 1994).

Social networks like family and friends and institutions like schools, churches and media play important roles in the consumer-acculturation process (Peñaloza 1994), as they facilitate the immigrants’ learning about the new culture. For example, Wamwara-Mbugua et al. (2008) elaborate the extent to which social networks (back home and in the US) act as ‘coping structures’ (Peñaloza 1994) in the consumer-acculturation experiences of newly arrived Kenyan immigrants to the US by means of other immigrants who had already adapted to the US’s new consumption environment. The consumer learning process takes place through such mechanisms as modelling, reinforcement and social interaction (Moschis 1987), through which immigrant consumers learn to decipher new cultural codes and acquire the skills, knowledge and behaviours they need in order to function as consumers.

Once they are in a new cultural environment, immigrants tend to cluster in neighbourhoods with high concentrations of other immigrants, which helps them learn about employment opportunities, affordable housing, government assistance programs and helpful charities and benefit from small enterprises that sell ethnic merchandise (Jamal 2005). After living in the community for some years, they become part of systems of interpersonal relationships through which they can exchange resources and knowledge. However, the more they interact with their own cultural communities, the more embedded they are in their own culture. Those who interact more with members of the mainstream society (e.g., at workplaces and in community centres and neighbourhoods) are more likely to develop preferences for integration or assimilation.

2.2 Social Media and Acculturation

Social media usage has grown exponentially in recent year and it has become an integral part of consumer lifestyle (Muhammad et al. 2017). Social media has been studied with a view to assessing its impact on collecting market information (Baur 2016), behavioural mining (Bulut and Dogan 2017; Manca et al. 2015), analysing political developments (Boerman and Kruikemeier 2016; Lee et al. 2015), co-creation (Cheung and To 2016; See-To and Ho 2014) and co-promotion (Zhou and Wang 2014). Like other technologies, social media can facilitate social change and changes in business practices. The Internet connects people from most parts of the world and enables them to engage and interact with one another (Kapoor et al. 2017), learning and endorsing various phenomena (Dessart et al. 2015) and helping them diffuse their ideas across societies. This is supported by Muhammad et al. (2017) who report social factors especially social interaction to be a key motivation for social media use by consumers. Social media creates the opportunities for sharing knowledge that can be major drivers of social learning, networking and building symbiotic communal relationships on the basis of mutual trust, support and altruism (Rolls et al. 2016). Other drivers of effective social media engagement, such as language, lexical expression (Hilte et al. 2016), and style (Sparks et al. 2013), have been found to influence the building of the communal bonds and relationships that can significantly impact customers’ behavioural intention (Goh et al. 2013; Laroche et al. 2013).

The acculturation scholarship has appraised the importance of social media to the formation of communal identities. When minority consumers frequently interact with other cultural groups via social media, they can construct and reinforce multiple ethnicities in an online context (Lindridge et al. 2015). Scholarly work (e.g., Jamal 2003) argues that ethnicity in a contemporary marketplace is like a bricolage, where a consumer builds his or her self-identity from elements taken from diverse cultural representations and practices. Accordingly, we argue that social media sites are likely to act as bicultural brokers and intermediaries that facilitate minority consumers’ self-representations and presentations of identity (Jafari and Visconti 2015). Support comes from Richey et al. (2017), who argue that self-presentations on social media can be likened to post-modern performances in which the traditional boundaries between actor and audience are intentionally unsettled. As such, social media is a vehicle for an acculturation process that is influenced by multidimensional and multifaceted cultural orientations (Forbush and Foucault-Welles 2016).

However, the influence of specific drivers on social media-led communal engagement and acculturation is an understudied area with strong potential to advance the current scholarship. More specifically, research has not investigated the effects of social media use on ethnic-minority consumers’ acculturation and consumption choices. We do not know whether these consumers prefer to socialise with members of their own cultural groups or with mainstream consumers or to what extent their social networking on social media impacts their acculturation and consumption choices. The present research seeks to fill this gap in the literature.

2.3 Hypotheses Development

Berry’s (1980) seminal work explains four major acculturation strategies that define the bipolar continuum of acculturation: assimilation, integration, separation and marginalisation. Acculturation strategies underlie the preference for and orientation of identification with the dominant culture (Cleveland and Laroche 2007) and the extent to which an immigrant maintains the cultural identity and characteristics of his or her home culture (Kim et al. 2001). Some immigrants may integrate into the host culture and maintain their cultural heritage such that both cultures influence their behaviour, while others completely assimilate into the host culture, and still othershold onto their heritage culture and avoid interaction with other cultures.

Consumer research uses language preference as an indicator of consumer acculturation outcomes. Immigrant consumers who prefer to use their own language (over that of the host culture) while they are with family and friends, at work, watching television, listening to music, reading newspapers and shopping (Hui et al. 1992) are engaging in cultural maintenance and enculturation (Arends-Tóth and van de Vijver 2008; Lee and Tse 1994). Such individuals are likely to show ‘separation’ tendencies (Berry 1980), placing high value on holding onto their heritage culture and avoiding interactions with other cultures. In the context of social media engagement, such individuals may have strong preferences for communicating in their own languages and in networking with people of their cultural backgrounds because they benefit from their ethnic communities’ resources (Quarasse and van de Vijver 2004) that are available on social media. Therefore, our first hypothesis states:
  • H1: Separation in language preference on social media is a) positively associated with enculturation and b) negatively with associated with acculturation.

The ‘assimilation’ strategy defines individuals who do not wish to maintain their cultural identity and instead seek daily interactions with other cultures (Berry 1980). Such an individual is likely to prefer using the host culture’s language over their native language while they are with family and friends, at work and so on, suggesting to others that they have assimilated culturally (Craig and Douglas 2006; Korzenny and Korzenny 2005; Laroche et al. 2009; Phinney 1992; Yagmur 2014). While on social media, such individuals prefer to network mainly with members of the host society and to avoid contact with members of their native culture. Therefore, our next hypothesis states:
  • H2: Assimilation of the host culture’s language on social media is a) negatively associated with enculturation and b) positively associated with acculturation.

An interest in both maintaining one’s heritage culture whilst having daily interactions with other cultural groups is defined as ‘integration’ (Berry 1980). Studies suggest that, in pluralistic societies, and even in relatively mono-cultural societies, integration is the most popular form of adaptation for immigrants (Berry 1997). Migration scholars recognise that many cultural groups maintain their ties to their heritage cultures at the same time that they integrate into new countries and argue that acculturation is not a fixed outcome so much as a process by which the immigrant navigates between cultures and multicultural identities (Oswald 1999).

An immigrant who uses an integration strategy may use his or her own language in a private domain (e.g., with family and friends) and the host culture’s language while in public (e.g., at work, at school, at a community center), allowing space for both their heritage culture and the host culture (Quarasse and van de Vijver 2004; Yagmur 2014; Yagmur and van de Vijver 2012).

Similarly, Schwartz et al. (2010) argue that young Latin American immigrants in the US can be fluent in both Spanish and English and can demonstrate both individualistic and collective cultural values, as they often demonstrate bicultural or blended cultural dispositions. Li and Tsai (2015) find that using social media in English helps Hispanics to develop strong orientation toward the mainstream American culture, while social media consumption in Spanish reinforced their ethnic cultural identification (i.e., enculturation). Therefore, we propose the following hypothesis:
  • H3: Integration in an immigrant’s language preference on social media is positively associated with a) enculturation and b) acculturation.

Research reports an association of ethnic and mainstream culture identification with purchase intentions (e.g., Bercerra and Korgaonkar 2010; Khairullah and Khairullah 1999). Consumers’ purchase intentions are influenced by their cultural orientations, which are affected by the information they use (Wang et al. 2012). Therefore, acculturation and enculturation affect purchase intentions, informing the following hypothesis:
  • H4: Enculturation and acculturation are positively associated with purchase intentions.

3 Research Method

3.1 Sample and Data Collection

The data used in this study considers the largest non-Western Turkish-Dutch ethnic group in the Netherlands. The survey respondents were recruited from a large panel via Markteffect, a leading company that specialises in survey sampling. The panel was a representative sample of 514 people from the Netherlands who participate in surveys and who claimed to have a Turkish background. Of the respondents, 54.1% were male and 45.9% female. The sample selected demonstrates a spread in terms of age, occupation, education and location within the Netherlands.

3.2 Survey Instrument and Measures

The measurement of language preferences on social media is based on Kaplan and Haenlein’s (2010) framework and Mendoza’s (1989) Cultural Life Style Inventory (CLSI). The CLSI measures the degree and type of acculturation to categorize individuals based on their maintenance of their heritage culture and acquisition of their host culture. Applied to the social media context, the individual items were used to segment the respondents into the separation, assimilation or integration categories. The response options for the items include (a) Turkish only, (b) mostly Turkish, (c) in Turkish and Dutch about equally, (d) mostly Dutch only and (e) Dutch only. An individual’s acculturation category in terms of his or her language preferences on social media is determined by summing the individual’s responses in each category and dividing the total by the number of his or her responses in all categories. For example, a respondent with three ‘separation’ responses, two ‘assimilation’ responses and one ‘integration’ response would have scores of 50% in the separation category, 33% in the assimilation category, and 17% in the integration category and would be categorized as belonging in the separation category. The three acculturation categories (i.e. separation, integration and assimilation) are compared statistically with z scores to identify each participant’s acculturation pattern (DeLeon and Mende 1996; Mendoza 1989).

Consumer acculturation of the host culture and enculturation of the heritage culture were measured using twenty items. The questions are based on Arends-Tóth and van de Vijver’s (2007) “two-statement method,” in which one first assesses the respondent’s cultural orientation in relation to the host culture (e.g., “I spend most of my social time with Dutch people”) and then assesses the respondent’s behaviour as it relates to his or her own ethnic heritage (e.g., “I spend most of my social time with Turkish people”). Each item was scored on a 7-point Likert scale ranging from “1 = strongly disagree” to “7 = strongly agree.”

Purchase intention was measured using four items adopted from Coyle and Thorson (2001). Each item was scored on a 7-point Likert scale ranging from “strongly disagree” to “strongly agree”.

4 Results

4.1 Acculturation Categories

Following Mendoza (1989, 1994), respondents were assigned to one of three acculturation categories (i.e., separation, integration or assimilation) in relation to their use of social media. Coding was determined by dividing participants’ responses on the social media items into the number of items answered in a Turkish-oriented, Dutch-oriented or multicultural-oriented acculturation pattern. For social language preferences, 17.5% of the respondents belong to the separation category, 29.8% to the integration category and 52% to the assimilation category.

4.2 Confirmatory Factor Analysis (CFA)

Confirmatory Factor Analysis (CFA) and Structural Equation Modelling (SEM) were used to test the theoretical framework presented in Fig. 1. The CFA showed that all of the items loaded highly on their corresponding factors and provided strong empirical evidence of their validity. The high factor loadings (i.e. > 0.5) suggested convergent validity (Kline 2011). Further assessment of convergence validity using Average Variance Extracted (AVE) and composite reliability (CR) for each construct indicated validity. Based on the results provided by the three assessment criteria (standardized factor loading, AVE and reliability scores) (Fornell and Larcker 1981), there is enough evidence to confirm the measurement model’s validity. The standardized loadings, along with critical ratios (C.R.) and AVE, are presented in Table 1 and the corresponding construct correlations are shown in Table 2.
Fig. 1

Structural equation model

Table 1

Item loadings

Construct

Standardized loadings

C.R.

Social Media Language preferences (α = 0.910, Composite reliability = 0.893, AVE = 0.583)

 I like to read online news.

0.718

fixed

 I like to post/use social networking sites.

0.745

16.013

 I like to participate in online content communities.

0.728

15.667

 I like to read online collaborative projects.

0.753

16.194

 I tend to post/read online blogs.

0.827

17.728

 I like to be in virtual social worlds.

0.805

17.284

Enculturation (α = 0.938, Composite reliability = 0.937, AVE = 0.598)

 I spend most of my social time with Turkish people.

0.793

fixed

 I very often ask for help/advice from Turkish students/colleagues.

0.797

20.079

 I frequently eat with Turkish friends/colleagues.

0.814

20.620

 I very often participate in Turkish public celebrations.

0.763

15.375

 My preference is to speak the Turkish language most of the time.

0.824

18.305

 I very often speak in the Turkish language with my Turkish friends.

0.783

19.406

 I very often speak in the Turkish language with my parents and family members.

0.700

17.249

 I very often attend Turkish cultural performances (e.g., theatres and concerts).

0.755

15.743

 I very often watch Turkish movies.

0.759

15.757

 I very often listen to Turkish music.

0.737

13.815

Acculturation (α = 0.918, Composite reliability = 0.917, AVE = 0.527)

 I spend most of my social time with Dutch people.

0.785

fixed

 I often ask for help/advice from Dutch students/colleagues.

0.759

20.126

 I frequently eat with Dutch friends/colleagues.

0.835

20.704

 I very often participate in Dutch public celebrations.

0.653

19.014

 My preference is to speak in the Dutch language most of the time.

0.754

21.014

 I very often speak in the Dutch language with Turkish friends.

0.789

19.640

 I very often speak in the Dutch language with my parents and family members/

0.726

17.016

 I very often attend Dutch cultural performances (theatres and concerts).

0.664

18.737

 I very often watch Dutch-language movies.

0.665

18.852

 I very often listen to Dutch music.

0.594

18.157

Purchase intentions (α = 0.898, Composite reliability = 0.906, AVE = 0.707)

 It is very likely that I will buy the product/service.

0.864

fixed

 I will purchase the product/service next time I need the product/service.

0.829

22.189

 I will definitely try the product/service.

0.839

22.516

 I will recommend the product/service to my friends.

0.832

19.749

Table 2

Construct correlation

Construct

SML

ACC

ENC

PI

Social Media Language Preferences (SML)

0.764

   

Acculturation (ACC)

0.342

0.726

  

Enculturation (ENC)

−0.480

−0.207

0.773

 

Purchase Intentions (PI)

−0.107

0.279

0.357

0.841

Chi-square values are affected by sample size, so incremental and absolute fit indices are used (Hu and Bentler 1999; Schumacker and Lomax 2004). The measurement model indicated a good overall fit (parsimony fit χ2/df = 2.535 comparative fit index (CFI) =0.939; incremental fit index (IFI) = 0.939; root mean square error of approximation (RMSEA) = 0.05 and standardized root mean square residual (SRMR) = 0.05).

4.3 Structural Model Testing

Structural equation analysis assessed the relationships among the latent variables using AMOS 22 (see Fig. 1 and Table 3). The analysis confirmed that the factor structure is an appropriate representation of the underlying data. The goodness-of-fit statistics show a good fit, given the large sample size of 514 (Hair et al. 2010) (parsimony fit χ2/df = 2.526, CFI = 0.939, IFI = 0.940, RMSEA = 0.05 and SRMR = 0.05). The structural model accounts for 28% of the variance in respondents’ purchase intentions.
Table 3

Structural model estimates

H# Structural Path

Estimates

Std. Error

C.R.

p

St. Estimates

H1a SML Separation ➔ Enculturation

0.976

0.164

5.948

0.000

0.270

H1b SML Separation ➔ Acculturation

−0.828

0.156

−5.320

0.000

−0.241

H2a SML Assimilation ➔ Enculturation

−0.371

0.041

−8.966

0.000

−0.404

H2b SML Assimilation ➔ Acculturation

0.168

0.040

4.231

0.000

0.193

H3a SML Integration ➔ Enculturation

0.326

0.068

4.775

0.000

0.217

H3b SML Integration ➔ Acculturation

−0.014

0.065

−0.208

0.836

−0.010

H4a Enculturation ➔ Purchase Intentions

0.453

0.050

9.148

0.000

0.431

H4b Acculturation ➔ Purchase Intentions

0.405

0.050

8.053

0.000

0.365

Goodness-of-fit statistics of the model:

Chi square = 995.168

degrees of freedom (df) 5394 p = 0.000

χ2 /df = 2.526

Comparative Fit Index (CFI) = 0.939

Incremental Fit Index (IFI) = 0.940

Root Mean Square Error of Approximation (RMSEA) = 0.055

Standardized RMR = 0.052

A review of the structural parameter estimates (Table 3) shows that, except for the relationship of language preference on social media with integration and acculturation, all remaining paths are significant. The analysis reveals a significant positive influence of a separation language preference on social media on enculturation (β = 0.27, p = 0.000) and a significant negative influence of a separation language preference on social media on acculturation (β = −0.24, p = 0.000). Therefore, H1a and H1b are supported.

An assimilation language preference on social media has a significant positive influence on acculturation (β = 0.19, p = 0.000) and a significant negative influence on enculturation (β = −0.40, p = 0.000). Therefore, H2a and H2b find support.

An integration language preference on social media has a positive significant influence on enculturation (β = 0.22, p = 0.000) but is non-significant and negatively associated with acculturation (β = −0.01, n.s.). These findings support H3a but not H3b.

Enculturation and acculturation both have a positive and significant influence on purchase intentions (β = 0.37, p = 0.000 and β = 0.43, p = 0.000) respectively. These findings provide support for H4a and H4b.

5 Discussion

Social media has emerged as an effective tool for supporting and promoting activities and interactions among peers, consumers, and organizations (Erkan and Evans 2016; Jin 2012; Kapoor et al. 2017; Sharma et al. 2013; Tang et al. 2015). The present research investigates the extent to which immigrant consumers show a preference for using either their own or the host culture’s language when they engage with others on social media, and the extent to which such preferences impact their preferences related to acculturation and enculturation (e.g., social interaction and language use with family members and friends, participation in celebrations) and purchase intentions.

In doing so, the study covers language preferences in a broad spectrum of online communication channels, including interpersonal communication, content communities, multimedia platforms, and news-reading (e.g., Ellison and Boyd 2013), because language and social interactions are key drivers of acculturation outcomes in offline contexts (e.g., Arends-Tóth and van de Vijver 2008; Hilte et al. 2016; Korzenny and Korzenny 2005; Yagmur 2014). Another goal of the study is to determine whether product recommendations made by others on social media networking sites (e.g., Facebook, blogs, and Twitter) can impact purchase intentions. The study is the first to link online communication preferences with offline phenomena like acculturation and enculturation and market choices like purchase intentions. A key finding is that the language preference for social media engagement impacts acculturation outcomes.

5.1 Contribution to Theory

5.1.1 Social Media Language Preferences

This research finds that a majority of respondents’ language preferences on social media are positioned in the assimilation category (52%), followed by integration (29.8%) and separation (17.5%), and that language preferences on social media play an important role in acculturation outcomes. As hypothesized, a separation in language preferences on social media has a significant and positive effect on enculturation and a negative effect on acculturation, suggesting that immigrants’ preferences for their heritage languages online lead to maintenance of heritage cultures in offline contexts. Therefore, the relationship between the online communication channels investigated in this study and maintenance of the heritage culture is significant and positive. This finding is in line with previous findings in acculturation research that language in traditional social networks and conventional media is a critical force in enculturation (Arends-Tóth and van de Vijver 2008; Hui et al. 1992; Lee and Tse 1994). The result echoes van Holst (2006), who states that the Turkish-Dutch population has a stronger interaction with Turkish media (e.g., television, newspapers and magazines) than it does with Dutch media. Our findings also support Li and Tsai (2015), who report that the use of Spanish social media sites reinforces Hispanics’ identification with their heritage culture. In short, immigrants in the separation category place value on maintaining their heritage cultures.

Another finding of our research is that the preference for using an assimilation language on social media has a strong positive effect on acculturation. This result suggests that those who prefer the Dutch language in online networking and communication contexts also prefer to socialize with Dutch friends and colleagues, to listen to Dutch music, and to use the Dutch language in offline contexts. A majority of our participants are in this category and are likely to blend various elements of Dutch culture into their own lifestyles. The research also finds that the preference for using an assimilation language on social media is negatively linked to enculturation, which is in line with the argument of previous acculturation research that immigrants in the assimilation category are less likely than those in other categories to prefer ethnic cultural engagement (Laroche et al. 2009; Korzenny and Korzenny 2005; Yagmur 2014).

The current study finds that the preference for using an integration language on social media positively affects enculturation but does not impact acculturation, which suggests that immigrant consumers do not necessarily lose their attachment to their heritage culture when they adopt the host culture’s language. These individuals take part in their heritage culture based on their preference for their heritage language and are not necessarily as receptive to the host culture as those who are assimilated. This finding requires further exploration, as integrated consumers are expected to show bicultural dispositions that reveal appreciation of the host country’s cultural values and traditions as well as those of their heritage culture (Korzenny and Korzenny 2005; Schwartz et al. 2010).

However, in line with previous research, this study finds that an immigrant’s use of his or her native language supports maintenance of the heritage culture, while use of the host culture’s language helps the immigrant to acculturate (i.e., assimilate) (e.g., Lee and Tse 1994; Moon and Park 2007; van Holst 2006). As such, the results find support for the effects of social media on cultural orientation.

5.1.2 Enculturation and Acculturation

Our results show that the use of a preferred language on social media relates to enculturation and acculturation and impacts purchase intentions. The extant research reports on the relationship between enculturation and consumption (e.g., Jamal 2003, 2005) such that social networks and institutions are aligned with ethnic immigrants’ consumer cultures, a finding that suggests that immigrants would also engage in their own ethnic consumer cultures online. Our study investigated the extent to which participants considered information about products and services that their friends shared on social media networks and the extent to which the participants were willing to purchase such products and services. The current study finds that offline enculturation and acculturation have a positive relationship with consumption-related influences on behavior through online social networks.

Acculturation research suggests that the process of consumers’ learning and socialization underpins the phenomena of cultural maintenance and cultural adaptation (Peñaloza 1994). A high degree of cultural adaptation to the host culture is influenced by the learning process, which entails interactions with education systems, friends, and the media (Askegaard et al. 2005; Deshpande et al. 1986). The present study finds that adaptation to the host culture has a positive relationship with purchase intentions, suggesting that immigrants rely and are influenced by their online social networks.

The role of social networking has a strong impact on immigrants’ maintenance of their heritage cultures and adaptation to their host cultures. An original contribution of the present study is the finding that the language preferences and purchase intentions that are exhibited in social networking are key forces in whether the individual chooses to consume products and services that are associated with their heritage cultures or that of the host country. Social networking also creates social relationships by providing tools with which to engage in social interactions (e.g., photo-sharing on Facebook) (Rolls et al. 2016).

This study also enriches current research on social media by identifying social media as a vehicle for intra-community and inter-community communication. While the extant literature (Dessart et al. 2015; Rolls et al. 2016) delineates the inherent nature of social media-led communal bonding that is characterized by trust, support, and altruism, there is little empirical work on social media’s influence on consumer acculturation. This paper’s findings address this deficiency and augment empirical evidence and theory on social media-led acculturation. It is noteworthy that dominant theories of information systems and/or technology adoption such as unified theory of acceptance and use of technology (Dwivedi et al. 2017a; Dwivedi et al. 2017b; Rana et al. 2016; Rana et al. 2017; Venkatesh et al. 2003; Williams et al. 2015), technology acceptance model (Davis 1989; Rana and Dwivedi 2016), theory of reasoned action (Alryalat et al. 2015; Fishbein and Ajzen 1975), social cognitive theory (Rana and Dwivedi 2015) and innovation diffusion theory (Kapoor et al. 2015) are less widely used in social media research.

Recent forecasts indicate that Europe’s populations will become more ethnically diverse and that the current indigenous population will soon be a numerical minority in some countries (Eurostat 2015). Although the current study is conducted for a particular ethnic group (Turkish-Dutch), it has theoretical and practical implications for wider contexts, and the model can be replicated with other ethnic communities in the Netherlands and other countries.

This study focuses on purchase intentions, as immigrants’ purchasing power and internet use are increasing. Given that online advertising and purchase intentions are related to cultural identification (Becerra and Korgaonkar 2009), future research should consider the influence of web advertising on immigrants’ consumption patterns.

5.2 Managerial Implications

Like consumers, profit and not-for-profit businesses have a strong interest in connecting with a range of stakeholders via social media through content promotion and knowledge dissemination surrounding products and services, making social media platforms the backbone of digital marketing (Aswani et al. 2017). Social media sites are now an enormous part of marketing tactics, as firms seek to develop relationships with users with certain backgrounds (Kapoor et al. 2017). Our research responds to this goal by providing a framework for connecting with immigrant consumers in Western societies. Kapoor et al. (2017) conduct a substantial review of the literature and point to the significant role of community structure and structural patterns in using social media for marketing purposes. They also argue that the success of marketing on social media platforms depends on identifying customer segments and targeting the customers they want based on demographic patterns and similar interests. We advance this scholarly work by arguing that public and private firms can profile and segment immigrant consumers based on the extent to which they prefer to use their own language or the mainstream language while engaging with social media sites. Given that the majority of our participants preferred assimilation in language use and showed a preference for acculturation in offline contexts, mainstream and ethnic-minority businesses in the Netherlands can target such consumers in English. Such consumers may believe that the mainstream culture and society value and reward hard work and promote justice, safety, and equality for all (Kizgin et al. 2017). Accordingly, businesses can use message strategies that incorporate mainstream cultural values while seeking to connect with their target customers via digital marketing.

Our findings in relation to assimilation and integration in language preference suggest that businesses can adopt an ethnic marketing approach (Jamal et al. 2015) to win the trust of such consumers on social media sites. Scholarly work reports that such consumers are likely show collectivist tendencies (e.g. Jamal and Shukor 2014; Jamal et al. 2015), so an emphasis on collectivist values and ethnic cultural traditions is likely to win the hearts of such consumers on social media sites. Digital marketers should create a positive online context with such communities by developing a rapport with, understanding of, and familiarity with immigrant consumers through continued engagement in the online communities such consumers use.

Businesses are also interested in identifying influencers for the purpose of digital marketing (Aswani et al. 2017). Based on our findings, we argue that businesses use product/service endorsers that resonate with immigrant consumers’ language preferences and acculturation/enculturation tendencies. For customers with assimilation tendencies, businesses are better off using mainstream opinion leaders in their digital marketing efforts, while experts and opinion leaders from the immigrant communities should be used when connecting with those that have separation and integration tendencies. Targeting immigrant consumers via digital marketing requires a great deal of insight into the personal preferences and cultural values of such consumers, to which research has contributed by providing a framework for targeting immigrant consumers.

6 Conclusion

Marketers will particularly find these implications useful in designing branding and marketing communication strategies. Ethnic brands such as Patak’s and Tilda basmati rice have used a combination of South Asian languages such as Hindi/Urdu/Bengali and nuances along with English linguistic expression to cater the dual cultural dispositions of South Asian diaspora in Europe, North America and Australia. Wing Yip, a successful oriental supermarket in the UK, provides detail product information in Cantonese language. With regard to social media use, the success of Wechat can be attributed to the linguistic convenience provided to Chinese diaspora across the world. Hence, businesses and brands both in the online and offline worlds can have stronger business prospects by reflecting on ethnic communities’ linguistic preferences.

While this study has created some headway for future research, it is not without limitations. First, the variance explained by the model in purchase intentions is only 28%. Future research can incorporate some additional constructs (e.g. attitude) along the proposed model to see if the variance for the model can be improved. Second, this study did not include the strength of social ties as a moderating variable. Future research will benefit from including the moderating effect of social ties for understanding ethnic consumers’ behaviour. Finally, this research focuses on purchase intentions rather than actual behaviour. Future research could examine how social media language preferences and cultural orientation affect online consumer behaviour.

Nevertheless, the current study can provide motivation for future research on the nature of and reasons for acculturation and enculturation of ethnic communities in multinational environments. Social media based interactions in particular could be further investigated to assess the inter- and intra-community interactions within and beyond national boundaries.

References

  1. Alalwan, A. A., Rana, N. P., Dwivedi, Y. K., & Algharabat, R. S. (2017). Social Media in Marketing: A review and analysis of the existing literature. Telematics and Informatics, 34(7), 1177–1190.CrossRefGoogle Scholar
  2. Alryalat, M., Rana, N. P., & Dwivedi, Y. K. (2015). Citizen’s adoption of an e-government system: Validating the extended theory of reasoned action (TRA). International Journal of Electronic Government Research, 11(4), 1–23.  https://doi.org/10.4018/IJEGR.2015100101.CrossRefGoogle Scholar
  3. Alryalat, M., Rana, N. P., Sahu, G. P., Dwivedi, Y. K., & Tajvidi, M. (2017). Use of social Media in Citizen-Centric Electronic Government Services: A literature analysis. International Journal of Electronic Government Research, 13(3), 55–79.  https://doi.org/10.4018/IJEGR.2017070104.CrossRefGoogle Scholar
  4. Arends-Tóth, J. V., & van de Vijver, F. J. R. (2007). Acculturation attitudes: A comparison of measurement methods. Journal of Applied Social Psychology, 37(7), 1462–1488.  https://doi.org/10.1111/j.1559-1816.2007.00222.x.CrossRefGoogle Scholar
  5. Arends-Tóth, J. V., & van de Vijver, F. J. R. (2008). Family relationships among immigrants and majority members in the Netherlands: The role of acculturation. Applied Psychology: An International Review, 57(3), 466–487.  https://doi.org/10.1111/j.1464-0597.2008.00331.x.CrossRefGoogle Scholar
  6. Askegaard, S., Arnould, E. J., & Kjeldgaard, D. (2005). Postassimilationist ethnic consumer research: Qualifications and extensions. Journal of Consumer Research, 32(1), 160–170.  https://doi.org/10.1086/426625.CrossRefGoogle Scholar
  7. Aswani, R., Kar, A. K., & Vigneswara Ilavarasan, P. (2017). Detection of spammers in twitter marketing: A hybrid approach using social media analytics and bio inspired computing. Information Systems Frontiers. Available at doi.  https://doi.org/10.1007/s10796-017-9805-8.
  8. Baur, A. W. (2016). Harnessing the social web to enhance insights into people’s opinions in business, government and public administration. Information Systems Frontiers, 19(2), 231–251.CrossRefGoogle Scholar
  9. Becerra, E. P., Korgaonkar, P. K. (2009). Hispanics’ information search and patronage intentions online. Journal of Electronic Commerce Research, 10(2), 76–93.Google Scholar
  10. Bercerra, E. P., & Korgaonkar, P. K. (2010). The influence of ethnic identification in digital advertising: How Hispanic Americans’ response to pop-up, e-mail, and banner advertising affects online purchase intentions. Journal of Advertising Research, 50(3), 279–291.  https://doi.org/10.2501/S0021849910091440.CrossRefGoogle Scholar
  11. Berry, J. W. (1980). Acculturation as varieties of adaptation. In A. M. Padilla (Ed.), Acculturation: Theory, models and some new findings (pp. 9–46). Boulder: Westview Press.Google Scholar
  12. Berry, J. W. (1992). Acculturation and adaptation in a new society. International Migration, 30(1), 69–85.  https://doi.org/10.1111/j.1468-2435.1992.tb00776.x.CrossRefGoogle Scholar
  13. Berry, J. W. (1997). Immigration, acculturation and adaptation. Applied Psychology: An International Review, 46, 5–68.Google Scholar
  14. Boerman, S. C., & Kruikemeier, S. (2016). Consumer responses to promoted tweets sent by brands and political parties. Computers in Human Behavior, 65, 285–294.  https://doi.org/10.1016/j.chb.2016.08.033.CrossRefGoogle Scholar
  15. Bulut, Z. A., & Dogan, O. (2017). The ABCD typology: Profile and motivations of Turkish social network sites users. Computers in Human Behavior, 67, 73–83.  https://doi.org/10.1016/j.chb.2016.10.021.CrossRefGoogle Scholar
  16. Cheung, M. F. Y., & To, W. M. (2016). Service co-creation in social media: An extension of the theory of planned behavior. Computers in Human Behavior, 65, 260–266.  https://doi.org/10.1016/j.chb.2016.08.031.CrossRefGoogle Scholar
  17. Cleveland, M., & Laroche, M. (2007). Acculturation to the global consumer culture: Scale development and research paradigm. Journal of Business Research, 60(3), 249–259.  https://doi.org/10.1016/j.jbusres.2006.11.006.CrossRefGoogle Scholar
  18. Coleman, D. (2008). The demographic effects of international migration in Europe. Oxford Review of Economic Policy, 24(3), 452–476.  https://doi.org/10.1093/oxrep/grn027.CrossRefGoogle Scholar
  19. Coyle, J. R., & Thorson, E. (2001). The effects of progressive levels of interactivity and vividness in web marketing sites. Journal of Advertising, 30(3), 65–77.  https://doi.org/10.1080/00913367.2001.10673646.CrossRefGoogle Scholar
  20. Craig, S. C., & Douglas, S. P. (2006). Beyond national culture: Implications of cultural dynamics for consumer research. International Marketing Review, 23(3), 322–342.  https://doi.org/10.1108/02651330610670479.CrossRefGoogle Scholar
  21. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 318–339.CrossRefGoogle Scholar
  22. Deshpande, R., Hoyer, W. D., & Donthu, N. (1986). The intensity of ethnic affiliation: A study of the sociology of Hispanic consumption. Journal of Consumer Research, 13(2), 214–220.  https://doi.org/10.1086/209061.CrossRefGoogle Scholar
  23. Dessart, L., Veloutsou, C., & Morgan-Thomas, A. M. (2015). Consumer engagement in online brand communities: A social media perspective. Journal of Product & Brand Management, 24(1), 280–242.CrossRefGoogle Scholar
  24. Dwivedi, Y. K., Rana, N. P., Janssen, M., Lal, B., Williams, M. D., & Clement, M. (2017a). An empirical validation of a unified model of electronic government adoption (UMEGA). Government Information Quarterly., 34(2), 211–230.  https://doi.org/10.1016/j.giq.2017.03.001.CrossRefGoogle Scholar
  25. Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2017b). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers.  https://doi.org/10.1007/s10796-017-9774-y.
  26. Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends”: Exploring the relationship between college students’ use of online social networks and social capital. Journal of Computer-Mediated Communication, 12(4), 1143–1168.  https://doi.org/10.1111/j.1083-6101.2007.00367.x.CrossRefGoogle Scholar
  27. Ellison, N. B., & Boyd, D. (2013). Sociality through social network sites. In W. H. Dutton (Ed.), The Oxford handbook of internet studies (pp. 151–172). Oxford: Oxford University Press.Google Scholar
  28. Erkan, I., & Evans, C. (2016). The influence of eWOM in social media on consumers’ purchase intentions: An extended approach to information adoption. Computers in Human Behavior, 61, 47–55.  https://doi.org/10.1016/j.chb.2016.03.003.CrossRefGoogle Scholar
  29. Eurostat. (2015). Migration and migrant population statistics. Available at: http://ec.europa.eu/eurostat/statistics-explained/index.php/Migration-and-migrant-population-statistics, Accessed 4 Dec 2017.
  30. Filieri, R., Alguezaui, S., & McLeay, F. (2015). Why do travelers trust TripAdvisor? Antecedents of trust towards consumer-generated media and its influence on recommendation adoption and word of mouth. Tourism Management, 51, 174–185.  https://doi.org/10.1016/j.tourman.2015.05.007.CrossRefGoogle Scholar
  31. Fishbein, M., & Ajzen, I. (1975). Belief. Attitude, intention and behavior: An introduction to theory and research reading. MA: Addison-Wesley.Google Scholar
  32. Forbush, E., & Foucault-Welles, B. (2016). Social media use and adaptation among Chinese students beginning to study in the United States. International Journal of Intercultural Relations, 50, 1–12.  https://doi.org/10.1016/j.ijintrel.2015.10.007.CrossRefGoogle Scholar
  33. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.  https://doi.org/10.2307/3151312.CrossRefGoogle Scholar
  34. Goh, K. Y., Heng, C. S., & Lin, Z. (2013). Social media brand community and consumer behavior: Quantifying the relative impact of user- and marketer-generated content. Information Systems Frontiers, 24(1), 88–107.Google Scholar
  35. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed.). Prentice-Hall: Upper Saddle River.Google Scholar
  36. Hilte, L., Vanderkerckhove, R., & Daelemans, W. (2016). Expressiveness in Flemish online teenage teenage talk: A corpus-based analysis of social and medium-related linguistic variation. In D. Fiser & M. Beisswenger (Eds.), Proceedings of the 4th Conference on CMC and Social Media Corpora for the Humanities (pp. 30–33). Ljubljana, Slovenia.Google Scholar
  37. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55.  https://doi.org/10.1080/10705519909540118.CrossRefGoogle Scholar
  38. Hui, M., Joy, A., Kim, C., & Laroche, M. (1992). Acculturation as a determinant of consumer behavior: Conceptual and methodological issues. American Marketing Association, 3, 466–473.Google Scholar
  39. Jafari, A., & Visconti, L. (2015). New directions in researching ethnicity in marketing and consumer behaviour: A wellbeing agenda. Marketing Theory, 15(2), 265–270.  https://doi.org/10.1177/1470593114552582.CrossRefGoogle Scholar
  40. Jamal, A. (2003). Marketing in a multicultural world: The interplay between marketing, ethnicity and consumption. European Journal of Marketing, 37(11/12), 1599–1620.  https://doi.org/10.1108/03090560310495375.CrossRefGoogle Scholar
  41. Jamal, A. (2005). Playing to win: An explorative study of marketing strategies of small ethnic retail entrepreneurs in the UK. Journal of Retailing and Consumer Services, 12(1), 1–13.  https://doi.org/10.1016/j.jretconser.2004.01.001.CrossRefGoogle Scholar
  42. Jamal, A., & Shukor, S. A. (2014). Antecedents and outcomes of interpersonal influences and the role of acculturation: The case of young British-Muslims. Journal of Business Research, 67(3), 237–245.  https://doi.org/10.1016/j.jbusres.2013.05.009.CrossRefGoogle Scholar
  43. Jamal, A., Peñaloza, L., & Laroche, M. (2015). Introduction to ethnic marketing, the Routledge companion to ethnic marketing. London: Routledge.Google Scholar
  44. Jin, S. A. (2012). The potential of social media for luxury brand management. Marketing Intelligence & Planning, 30(7), 687–699.CrossRefGoogle Scholar
  45. Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68.  https://doi.org/10.1016/j.bushor.2009.09.003.CrossRefGoogle Scholar
  46. Kapoor, K. K., Dwivedi, Y. K., & Williams, M. D. (2015). Examining the role of three sets of innovation attributes for determining adoption of the interbank mobile payment service. Information Systems Frontiers, 17(5), 1039–1056.  https://doi.org/10.1007/s10796-014-9484-7.CrossRefGoogle Scholar
  47. Kapoor, K. K., Tamilmani, K., Rana, N. P., Patil, P., Dwivedi, Y. K., & Nerur, S. (2017). Advances in social media Research: Past, Present and Future. Information Systems Frontiers. Available at doi:  https://doi.org/10.1007/s10796-017-9810-y.
  48. Khairullah, D. Z., & Khairullah, Z. Y. (1999). Behavioural acculturation and demographic characteristics of Asian-Indian immigrants in the United States of America. International Journal of Sociology and Social Policy, 19(1), 57–80.  https://doi.org/10.1108/01443339910788668.CrossRefGoogle Scholar
  49. Kim, C., Laroche, M., & Tomiuk, M. A. (2001). A measure of acculturation for Italian Canadians: Scale development and construct validation. International Journal of Intercultural Relations, 25(6), 607–637.  https://doi.org/10.1016/S0147-1767(01)00028-1.CrossRefGoogle Scholar
  50. Kizgin, H., Jamal, A., & Richard, M. O. (2017). Consumption of products from heritage and host cultures: The role of acculturation attitudes and behaviors. Journal of Business Research, 82, 320–329.CrossRefGoogle Scholar
  51. Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York: The Guilford Press.Google Scholar
  52. Korzenny, F., & Korzenny, B. A. (2005). Hispanic marketing: A cultural perspective. Burlington: Elsevier Butterworth-Heinmann.Google Scholar
  53. Laroche, M., Pons, F., & Richard, M. O. (2009). The role of language in ethnic identity measurement: A multitrait-multimethod approach to construct validation. Journal of Social Psychology, 149(4), 513–539.  https://doi.org/10.3200/SOCP.149.4.513-540.CrossRefGoogle Scholar
  54. Laroche, M., Habibi, M. R., & Richard, M. O. (2013). To be or not to be in social media: How brand loyalty is affected by social media. International Journal of Information Management, 33(1), 76–82.  https://doi.org/10.1016/j.ijinfomgt.2012.07.003.CrossRefGoogle Scholar
  55. Laroche, M., & Jamal, A. (2015). Models of culture change. In The Routledge companion to ethnic marketing (pp. 17–35). London: Routledge.Google Scholar
  56. Lee, D., Hosanagar, K., & Nair, H. K. (2015). The effect of social media marketing content on consumer engagement: Evidence from Facebook. Working paper: Carnegie Mellon University.Google Scholar
  57. Lee, V., & Tse, D. K. (1994). Changing media consumption in a new home: Acculturation patterns among Hong Kong immigrants to Canada. Journal of Advertising, 23(1), 57–68.  https://doi.org/10.1080/00913367.1994.10673431.CrossRefGoogle Scholar
  58. DeLeon, B., & Mende, S. (1996). Factorial structure of a measure of acculturation in a Puerto Rican population. Educational and Psychological Measurement, 56, 155–165.CrossRefGoogle Scholar
  59. Li, C. L., & Tsai, W. H. (2015). Social media usage and acculturation: A test with Hispanics in the U.S. Computers in Human Behavior, 45, 204–212.  https://doi.org/10.1016/j.chb.2014.12.018.CrossRefGoogle Scholar
  60. Li, C. L., Bernoff, J., & Lonian, A. (2004). Profiles: The real value of social networks. Cambridge: Forrester Research, Inc..Google Scholar
  61. Lindridge, A., Henderson, G. R., & Ekpo, A. E. (2015). (virtual) ethnicity, the internet, and well-being. Marketing Theory, 15(2), 279–285.  https://doi.org/10.1177/1470593114553328.CrossRefGoogle Scholar
  62. Manca, M., Boratto, L., & Carta, S. (2015). Behavioural data mining to produce novel and serendipitous friend recommendations in social bookmarking systems. Information Systems Frontier, 17(5), 1–15.Google Scholar
  63. Mendoza, R. H. (1989). An empirical scale to measure type and degree of acculturation in Mexican American adolescents and adults. Journal of Cross-Cultural Psychology, 20(4), 372–385.  https://doi.org/10.1177/0022022189204003.
  64. Mendoza, R. H. (1994). Cultural life style inventory. Alhambra: California School of Professional Psychology.Google Scholar
  65. Moschis, G. P. (1987). Consumer Socialisation. A Life-cycle Perspective. Lexington. Lexington.Google Scholar
  66. Moon, S., & Park, C. Y. (2007). Media effects on acculturation and biculturalism: A case study of Korean immigrants in Los Angeles’ Koreatown. Mass Communication & Society, 10(3), 319–343.  https://doi.org/10.1080/15205430701407330.CrossRefGoogle Scholar
  67. Muhammad, S. S., Dey, B. L., & Weerakkody, V. (2017). Analysis of factors that influence customers’ willingness to leave big data digital footprints on social media: A systematic review of literature. Information Systems Frontiers, 1-18. Available at doi:  https://doi.org/10.1007/s10796-017-9802-y.
  68. Oswald, L. R. (1999). Culture swapping: Consumption and the ethnogenesis of middle-class Haitian immigrants. Journal of Consumer Research, 25(4), 303–318.  https://doi.org/10.1086/209541.CrossRefGoogle Scholar
  69. Peñaloza, L. (1994). Atravesando Fronteras/border crossings: A critical ethnographic exploration of the consumer acculturation of Mexican immigrants. Journal of Consumer Research, 21(1), 32–54.  https://doi.org/10.1086/209381.CrossRefGoogle Scholar
  70. Peñaloza, L., & Gilly, M. C. (1999). Marketer acculturation: The changer and the changed. Journal of Marketing, 63(3), 84–104.  https://doi.org/10.2307/1251777.CrossRefGoogle Scholar
  71. Phinney, J. S. (1992). The multigroup ethnic identity measure: A new scale for use with diverse groups. Journal of Adolescent Research, 7(2), 156–176.  https://doi.org/10.1177/074355489272003.CrossRefGoogle Scholar
  72. Quarasse, O., & van de Vijver, F. J. R. (2004). Structure and function of the perceived acculturation context of young Moroccans in the Netherlands. International Journal of Psychology, 39(3), 190–204.CrossRefGoogle Scholar
  73. Rana, N. P., & Dwivedi, Y. K. (2015). Citizen's adoption of an e-government system: Validating extended social cognitive theory (SCT). Government Information Quarterly, 32(2), 172–181.  https://doi.org/10.1016/j.giq.2015.02.002.CrossRefGoogle Scholar
  74. Rana, N. P., & Dwivedi, Y. K. (2016). Using clickers in a large business class: Examining use behavior and satisfaction. Journal of Marketing Education, 38(1), 47–64.  https://doi.org/10.1177/0273475315590660.CrossRefGoogle Scholar
  75. Rana, N. P., Dwivedi, Y. K., Williams, M. D., & Weerakkody, V. (2016). Adoption of online public grievance redressal system in India: Toward developing a unified view. Computers in Human Behavior, 59, 265–282.  https://doi.org/10.1016/j.chb.2016.02.019.CrossRefGoogle Scholar
  76. Rana, N. P., Dwivedi, Y. K., Dey, B. L., Williams, M. D., & Clement, M. (2017). Citizens’ adoption of an electronic government system: Toward a unified view. Information Systems Frontiers, 19(3), 549–568.  https://doi.org/10.1007/s10796-015-9613-y.CrossRefGoogle Scholar
  77. Richey, M., Gonibeed, A., & Ravishankar, M. N. (2017). The perils and promises of self-disclosure on social media. Information Systems Frontiers. Available at doi.  https://doi.org/10.1007/s10796-017-9806-7.
  78. Rolls, K., Hansen, M., Jackson, D., & Elliott, D. (2016). How healthcare professionals use social media to create virtual communities: An integrative literature review. Journal of Medical Internet Research, 18(6), 1–19.CrossRefGoogle Scholar
  79. Schumacker, R. E., & Lomax, R. G. (2004). A Beginner’s Guide to Structural Equation Modeling (2nd ed.). Mahwah: Lawrence Erlbaum associates, Inc.Google Scholar
  80. Schwartz, S. J., Unger, J. B., Zamboanga, B. L., & Szapocznik, J. (2010). Rethinking the concept of acculturation: Implications for theory and research. American Psychologist, 65(4), 237–251.  https://doi.org/10.1037/a0019330.CrossRefGoogle Scholar
  81. See-To, E. W. K., & Ho, K. W. (2014). Value co-creation and purchase intention in social network sites: The role of electronic word-of-mouth and trust – A theoretical analysis. Computers in Human Behavior, 31(1), 182–189.  https://doi.org/10.1016/j.chb.2013.10.013.CrossRefGoogle Scholar
  82. Sharma, G., Qiang, Y., Wenjun, S., & Qi, L. (2013). Communication in the virtual world: Second life and business opportunities. Information Systems Frontiers, 15(4), 677–694.  https://doi.org/10.1007/s10796-012-9347-z.CrossRefGoogle Scholar
  83. Sparks, B. A., Perkins, H., & Buckley, R. (2013). Online travel reviews as persuasive communication: The effects of content type, source, and certification logos on consumer behaviour. Tourism Management, 39, 1–9.  https://doi.org/10.1016/j.tourman.2013.03.007.CrossRefGoogle Scholar
  84. Tang, J., Zhang, P., & Wu, P. (2015). Categorizing consumer behavioral responses and artifact design features: The case of online advertising. Information Systems Frontiers, 17(3), 513–532.  https://doi.org/10.1007/s10796-014-9508-3.CrossRefGoogle Scholar
  85. Van Holst, R. (2006). Feiten & Cijfers: Mediagebruik van allochtonen in Nederland. Utrecht: Mira Media.Google Scholar
  86. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.  https://doi.org/10.2307/30036540.CrossRefGoogle Scholar
  87. Wamwara-Mbugua, L. W., Cornwell, T. B., & Boller, G. (2008). Triple acculturation: The role of African Americans in the consumer acculturation of Kenyan immigrants. Journal of Business Research, 61(2), 83–90.  https://doi.org/10.1016/j.jbusres.2007.04.011.CrossRefGoogle Scholar
  88. Zhou, L., & Wang, T. (2014). Social media: A new vehicle for city marketing in China. Cities, 37, 27–32.  https://doi.org/10.1016/j.cities.2013.11.006.CrossRefGoogle Scholar
  89. Wang, X., Yu, C., & Wei, Y. (2012). Social media peer communication and impact on purchase intentions: A consumer socialization framework. Journal of Interactive Marketing, 26(4), 198–208.  https://doi.org/10.1016/j.intmar.2011.11.004.CrossRefGoogle Scholar
  90. Williams, M. D., Rana, N. P., & Dwivedi, Y. K. (2015). The unified theory of acceptance and use of technology: A systematic review. Journal of Enterprise Information Management, 28(3), 443–488.  https://doi.org/10.1108/JEIM-09-2014-0088.CrossRefGoogle Scholar
  91. Yagmur, K. (2014). Intergenerational differences in acculturation orientations of Turkish speakers in Australia. Journal of Social Sciences in the Turkish World, 70, 237–258.CrossRefGoogle Scholar
  92. Yagmur, K., & van de Vijver, F. J. R. (2012). Acculturation and language orientations of Turkish immigrants in Australia, France, Germany, and the Netherlands. Journal of Cross-Cultural Psychology, 43(7), 1110–1130.  https://doi.org/10.1177/0022022111420145.CrossRefGoogle Scholar

Copyright information

© The Author(s) 2017

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.School of ManagementSwansea University Bay CampusSwanseaUK
  2. 2.Cardiff University Business SchoolCardiffUK
  3. 3.Brunel University Business SchoolUxbridgeUK

Personalised recommendations