Abstract
Purpose
This study aims to evaluate cognitive, personal and environmental factors affecting investors’ behavioral intentions (BI) to invest in ṣukūk (Islamic investment certificates) in Pakistan.
Design/methodology/approach
Data from 462 participants were collected through survey-questionnaires by using the convenient sampling technique. Hypothesized proposed relationships among the constructs were examined by applying the structural equation modeling (SEM) technique through smart partial least squares.
Findings
Compatibility, internal influence, external influence and intrinsic motivation were found to be significant predictors of investors’ BI to invest in ṣukūk. In addition, it was found that the religious aspect not only affects investors’ BI positively but also works as a moderator in the relationships between BI and both internal and external influence.
Practical implications
The results are quite helpful for ṣukūk issuers and regulators to consider cognitive, personal and environmental factors that might enhance the adoption of ṣukūk, especially among Muslim investors.
Originality/value
This study is among the few research studies that shed light on investors’ BI to invest in ṣukūk. Using social cognitive theory, the study investigates the cognitive, personal and environmental factors influencing ṣukūk adoption, which were previously unexplored. In addition, this is the first study that unveils the influential factors of ṣukūk adoption in Pakistan, a Muslim-majority country.
Keywords
Citation
Khan, S.U., Khan, I.U., Khan, I., Din, S.U. and Khan, A.U. (2020), "Evaluating
Publisher
:Emerald Publishing Limited
Copyright © 2020, Safeer Ullah Khan, Ikram Ullah Khan, Ismail Khan, Saif Ud Din and Abid Ullah Khan.
License
Published in ISRA International Journal of Islamic Finance. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction
The previous two decades have witnessed accelerated growth in the products of the Islamic finance industry, including Islamic banking, takāful (Islamic insurance) and the Islamic capital market. There has especially been a significant increase in the issuance of ṣukūk (Islamic investment certificates) across the globe, predominantly in Muslim-majority countries (Schmidt, 2019; Mimouni et al., 2019). Najeeb et al. (2017) further describe ṣukūk as one of the fastest-growing products in the Islamic finance industry. The Islamic Financial Services Board’s (IFSB) report (2020) confirms that ṣukūk comprise the second largest investment asset class with US$543.4bn outstanding as at end-2019, thus representing 22.3% of the Islamic finance industry’s total assets of US$2.44tn.
Despite the growth in ṣukūk investment and issuance across the globe, limited research sheds light on the factors that explain and predict investors’ intentions to invest in ṣukūk, especially in Pakistan. The literature indicates that the components of the theory of planned behavior (TPB) – i.e. attitude, subjective norms and perceived behavioral control – influence investors’ intentions to use ṣukūk (Ajzen, 1985; Warsame and Ireri, 2016; Ashidiqi and Arundina, 2017). However, Mathieson (1991) criticizes TPB, stating that it cannot be applied to all individuals and in diverse user contexts. Duqi (2019) highlights some additional factors such as expected return, information and the issuing institution’s reputation that predict investors’ intentions to use ṣukūk. Based on previous literature, the study finds that there is a lack of empirical research focusing on cognitive, personal and environmental factors that might have an influence on investors’ intentions. Khan et al. (2018) note the significant influence of personal and environmental factors on investors’ intentions to invest in stock market securities. In an attempt to close this gap, this study argues that investors’ intentions to invest in ṣukūk are a function of social influence, external influence, compatibility of ṣukūk investment with lifestyle, intrinsic motivation and the religious aspect.
The literature on consumers’ behavioral intentions (BI) reveals the significant positive role of an inclination to invest in Islamic products on individuals’ intentions, especially in Islamic countries (Warsame and Ireri, 2016; Riaz et al., 2017; Duqi, 2019). Ṣukūk and conventional bonds have some shared features, though some characteristics differentiate ṣukūk from conventional bonds. Conventional bonds represent indebtedness of the issuer vis-à-vis the bondholder, while ṣukūk nominally provide an ownership stake to the holder in an underlying asset, which is according to Islamic principles (Fathurahman and Fitriati, 2013). The study investigates ṣukūk investment intentions among individual investors in Pakistan where 96.28% of the total population is Muslims (PBS, 2019). The study maintains that the variable “religious aspect of ṣukūk” will not only influence individuals’ intentions positively but it will also affect the association between the proposed factors and the use of ṣukūk. Therefore, incorporating a religious aspect as a moderator will contribute and strengthen the explanatory power of the proposed model to better explain individuals’ intention to use ṣukūk for investment purposes.
As mentioned earlier, research on investors’ intentions regarding ṣukūk investment has been relying on the use of the TPB, which has been criticized on the grounds that the model has applicability issues in different contexts. Hence, the current study investigates cognitive, personal, environmental and behavioral factors that affect investors’ BI regarding ṣukūk investment. The tenets of social cognitive theory (SCT), developed by Bandura (1986a), reflect cognitive, personal, environmental and behavioral factors that represent individuals’ intentions regarding the adoption of new products. Many studies have validated the SCT because of its adaptive nature and its use in examining the acceptance of various new products such as internet banking (Boateng et al., 2016), internet stock trading (Khan et al., 2020b), e-government (Rana and Dwivedi, 2015) and within the context of organizational management (Wood and Bandura, 1989) and tourism (Font et al., 2016). Therefore, keeping in view the comprehensive nature and relevance of the context, the study proposes a model based on SCT, which according to Bandura (1989) is one of the leading theories of human behavior.
According to SCT, human intention is a function of the interactions between personal, environmental and behavioral factors. Personal factors include age, lifestyle, beliefs and expectations that are associated with BI (Boateng et al., 2016). Environmental factors represent both natural elements and the social environment of an individual (Casper, 2001). Following Mohammadi (2015), the behavioral factor can be defined in terms of intentions or the likelihood that people will use ṣukūk. According to Boateng et al. (2016), an individual’s behavior is shaped by the interaction between these three components. Besides this theoretical contribution, identifying the factor on the basis of which ṣukūk issuers might attract potential investors, the study incorporates the religious aspect of ṣukūk as a moderator and expects that it will modulate the effect of the proposed factors on investors’ BI. In the context of Pakistan, it is a novel idea to probe into and presents solid guidelines for ṣukūk users and policymakers.
The structure of the remaining sections is as follows: the next section presents the theory and the proposed hypotheses. It is followed by the research methodology section which includes the process of data collection. The statistical results of the study are then presented, followed by a discussion of the findings and its implications. Finally, the paper ends with conclusive remarks and highlights the limitations of the study.
Theory and hypotheses
Compatibility
SCT argues that personal factors represent a key component determining individuals’ actions (Bandura, 1986b). Likewise, Lerner (1982) reports that personal factors of individuals such as gender, age and lifestyle interact with environmental factors and affect their behavior. In this connection, Everett (1995) validates that some individuals accept a new product if they perceive that the product is compatible with their lifestyle. In the case of ṣukūk investment, the study expects that compatibility of individuals’ lifestyles with ṣukūk investment is associated with their intention to use ṣukūk.
The current study defines compatibility as the situation in which a person perceives a new product as relevant to their actions, lifestyle and mode of thinking. Njuguna (2018) defines compatibility as investors’ perception that the adoption of a particular financial product is relevant to their needs, lifestyle, past experience and ways of thinking. Similarly, Agarwal and Prasad (1997) state that compatibility is a fundamental factor in the initial stage of adopting a new product or service. Thus, compatibility is one of the key components that have a significant role in the adoption process (Hanafizadeh et al., 2014; Boateng et al., 2016; Gu et al., 2019). Lee-Partridge and Ho (2003) determine significant effects of compatibility on investors’ adoption of stock trading and their behavior. Similarly, compatibility was found to be one of the key determinants of investors’ decisions and intentions (Tornatzky and Klein, 1982). In Muslim-majority countries like Pakistan where people live in accordance with Islamic injunctions, ṣukūk, being based on Islamic principles, would be compatible with their lifestyle (Sayeda, 2019). In this connection, Ahmed et al. (2019) maintain that ṣukūk provide investment opportunities for investors who wish to comply with Sharīʿah (Islamic law) principles. Thus, it is expected that compatibility will affect investors’ intentions in Pakistan. Therefore, it is proposed:
Compatibility has a positive association with investors’ BI to invest in ṣukūk.
Internal (social) influence
One of the fundamental and assimilating elements of SCT is the social environment (Bandura, 1991; Rana and Dwivedi, 2015). People get influenced by their social networks such as family members, peers, friends and relatives to use a product (López-Nicolás et al., 2008). As Khan et al. (2017) state that Pakistani culture is collectivist, it is considered that social influence is positively associated with investors’ intentions to invest in ṣukūk. Similarly, Brown et al. (2008) demonstrate that the community plays an important role in this regard. This idea is also supported by Rana and Dwivedi (2015, p. 3), who define social influence as “the degree to which a person perceives as to how much the people within his/her social circle take into consideration the utility of the product or service.” They further maintain that such thinking considerably influences the adoption of a product or service.
In addition, Tauni et al. (2017) argue that investors usually rely on word-of-mouth communication in their social networks to exchange information about financial market securities. They suggest that not everyone wishes to avail of the costly financial advice of experts; therefore, they mostly rely on word-of-mouth communication with friends, peers, family and relatives. In the same way, Lusardi and Mitchell (2011) and Van Rooij et al. (2011) conclude that most investors are not financially literate, so they follow their social networks for taking financial decisions. Moreover, Madrian and Shea (2001) state that interaction with social networks significantly affects employees’ retirement plan participation decisions as people usually follow their peers’ savings choices. The same findings are also reported by Duflo and Saez (2002, 2003), who state that the patterns of peers’ savings influence others in investment decisions. Likewise, Brown et al. (2008) find more stock market participation among those social groups in which some of the members were previously involved and/or active in such stock trading. Their study suggests that this might be the result of word-of-mouth communication between group members. Campbell et al. (2015) note that the involvement of one member in a social group in the stock market positively influences the market participation of other members of the group. These pieces of evidence suggest that social influence might have an impact on investors’ BI to invest in ṣukūk. Thus, it is hypothesized that:
Internal influence has a positive association with investors’ BI to invest in ṣukūk.
External influence
As discussed earlier, one of the fundamental elements of SCT is the individuals’ environment; i.e. factors external to the individuals. The main focus of SCT is to understand how individuals engage in a specific behavior by interacting with external and internal environmental factors (Chan, 2004). One of the external environmental factors is mass media, which according to Ratten (2013), considerably influences individuals’ adoption intentions. Media represents oral or written communication that works as an information source such as television, radio, newspaper, magazines and social media. In this connection, Rice and Bennett (1998) aver that media communication is an effective source for enhancing desired behaviors. Thus, it is expected that the higher the media communication about ṣukūk, the more people will learn about it, which, in turn, will influence their intentions.
In addition, Abreu and Mendes (2012) state that news from the specialized press has strong effects on investors’ behavior. They also find significant effects of mass media on stock trading behavior. Khan et al. (2020a) determine awareness as being not only a direct predictor but also having an indirect impact (through risks) on stock trading adoption. Significant results of mass media attention on stock returns are also acknowledged by Yu-lei et al. (2010). Similarly, Davis (2006) admits that passive investment mostly relies on the communication environment that creates a herd-like behavior in the market. The empirical results of Deephouse (2000) indicate that mass media has a significant role in the performance of financial markets. The vital role of external influence (media) has been observed as changing individuals’ BI in various contexts such as e-books (Ratten, 2010), mobile banking adoption (Ratten, 2013), information technology (Agarwal and Prasad, 1998) and online purchase intentions (Gunawan and Huarng, 2015). These studies reveal that external influence has a considerable impact on financial securities and individuals’ BI. Accordingly, the study argues that external influence will positively influence investors’ intentions to invest in ṣukūk. Therefore, it is proposed that:
External influence has a positive association with investors’ BI to invest in ṣukūk.
Intrinsic motivation
There are two main types of human motivation i.e. extrinsic and intrinsic motivation. According to SCT, extrinsic motivation is the external determinant and intrinsic motivation is an internal factor of behavior (Bandura and Walters, 1977; Bandura, 1986a). Extrinsic motivation refers to all those incentives that motivate individuals to perform a specific behavior such as money, promotion and rank, whereas intrinsic motivation is related to individuals’ inner satisfaction, which results from taking satisfactory actions (Yoo et al., 2012; Gerhart and Fang, 2015). Moreover, Zamani and Talatapeh (2014) explain the spiritual aspect of intrinsic motivation, which they found to be a more compelling force of individuals’ intentions. It refers to the inner satisfaction that is gained through performing a behavior according to Sharīʿah.
Islam is not just worship. It guides and covers all aspects of human life including ḥalāl (permissible) means of earnings (Qurʾān, 62:10) and avoidance of impermissible sources of earnings like theft (Qurʾān, 5:38) and interest (Qurʾān, 2:276). The sagacious scholar Ibn Qayyim al Jawziyyah states:
Truly, there is a void in the heart that cannot be removed except with the company of Allah. And there is a sadness in it that cannot be removed except with the happiness of knowing Allah and being true to Him. And there is an emptiness in it that cannot be filled except with love for Him and by turning to Him and always remembering Him. If a person were given the entire world and what is in it, it would not fill this emptiness (www.jannah.org/shazia/wordplay.html).
Ṣukūk investment is structured according to Sharīʿah. Based on the aforementioned discussion and prior research studies of Shang et al. (2005), Vallerand (2007), Yoo et al. (2012), who noted that intrinsic motivation is a vital antecedent of individuals’ intentions, this study considers intrinsic motivation as one of the factors of ṣukūk investment intentions. Accordingly, it is proposed that:
Intrinsic motivation has a positive association with investors’ intentions to invest in ṣukūk.
Direct and moderating effects of the religious aspect
Casper (2001) shows that religious principles and practices are key components of the social environment. Thus, it can be argued that the religious aspect of ṣukūk relates to individuals’ intentions in Muslim-majority countries like Pakistan. In this connection, Zainul et al. (2004) maintain that the Islamic perspective of a product is the strongest predictor of individuals’ intentions, especially in Islamic communities. Similarly, Riaz et al. (2017) demonstrate that religious motivation in Islamic products and finance have a considerable influence on individuals’ perceptions in Pakistan. Again, Rahman and Anwar (2016) document a significant positive effect of the religious perspective on banking customers’ satisfaction. Thus, the religious aspect may be determined as a significant predictor of individuals’ intentions to invest in ṣukūk (Ashidiqi and Arundina, 2017; Duqi, 2019).
Muslims believe in Judgment Day, where they will be rewarded if they spend their lives according to Islamic rules or punished otherwise. Islam encourages mankind to opt for any type of business activity that is according to Islamic principles. In the Islamic concept of business, Muslims have to be reliable, honest and God-fearing in business dealings, as narrated by the text of the Holy Qurʾān:
[…] God has permitted trade and forbidden usury. Whoever, on receiving God’s warning, stops taking usury may keep his past gains–God will be his judge–but whoever goes back to usury will be an inhabitant of the Fire, there to remain (2:275).
Muslims believe that on the Day of Judgment the good will be rewarded and the bad will be punished. Therefore, this study argues that the religious aspect of a product will not only influence individuals’ BI positively but will also affect the association of the proposed independent factors on intentions to invest in ṣukūk. As mentioned above, SCT argues that BI is a function of the interaction among cognitive, personal, environmental and behavioral factors. Hence, it is worth arguing that the religious aspect and its interactions with compatibility, social influence, external influence and intrinsic motivation help to predict and explain variations in investors’ intentions to invest in ṣukūk. Based on these grounds, the study postulates the following hypotheses:
Religion has a positive association with investors’ intentions to invest in ṣukūk.
Religion moderates the association between compatibility and investors’ intention to invest in ṣukūk.
Religion moderates the association between social influence and investors’ intention to invest in ṣukūk.
Religion moderates the association between external influence and investors’ intention to invest in ṣukūk.
Religion moderates the association between intrinsic motivation and investors’ intention to invest in ṣukūk.
Methodology
Participants
To collect data, a questionnaire survey was conducted in the capital of Pakistan, Islamabad, from both investors and non-users of ṣukūk. Individual investors constitute the population of the study. Respondents belonging to banks, public offices and universities were contacted randomly to avoid any bias in the sampling. In this regard, a convenient sampling technique was used. Past studies show that primary data gathering through questionnaires has been frequently used and is logical for such type of research questions where Islamic products/certificates are investigated (Warsame and Ireri, 2016; Ahmed et al., 2019; Allah Pitchay et al., 2019; Khan et al., 2019). A printed version of the survey questionnaires was used for gathering the required data. For screening purposes and to reduce the hypothetical response biases, a question “have you heard of ṣukūk before?” was included in the survey questionnaires. A total of 500 questionnaires was circulated among individuals in Islamabad, of which 483 were returned. The data collection process was completed from June to August 2019. Among the returned responses, 13 responses were from those who had never heard of ṣukūk. Moreover, 8 questionnaires were incomplete, so they were excluded. Table 1 represents the respondents’ profile (demographic characteristics) (N-462) whose data was used for the final analysis.
Measures
To test the postulated relationships depicted in the proposed model (Figure 1), a questionnaire survey that incorporates measuring items of all variables of the model was administered. The survey consisted of 19 items and six research constructs. Compatibility, which was measured with three items, was adapted from Boateng et al. (2016). Social influence and external influence were measured with three items that were borrowed from Bhattacherjee (2000) and Song (2014). The three measuring items of intrinsic motivation were taken from Tremblay et al. (2009). In addition, the religious aspect was measured with four items, validated by Riaz et al. (2017) and Duqi (2019). The three items for BI were adapted from Warsame and Ireri (2016). Moreover, the survey items were slightly revised to suit the ṣukūk investment context. Finally, the survey items were anchored on the seven-point Likert scale where “1” represents “strongly disagree” and “7” shows “strongly agree.”
Data analysis
The hypothesized proposed relationships among the constructs were examined by applying structural equation modeling (SEM) through smart partial least squares (PLS). According to Hair et al. (2017), PLS-SEM is commonly used for testing complex statistical analysis in the fields of business and management sciences. The smart-PLS approach was a suitable and appropriate technique for the current study as it is suggested by many notable researchers such as Chin et al. (2003) and Reinartz et al. (2009), who recommend PLS for testing complicated cause-effect associations. Moreover, Chin et al. (2003) consider PLS useful, particularly for testing moderation effects. As the current study intends to test the moderation effects of religion, PLS is considered a technique for data analysis. The study followed the suggested two-stage approach by Hair et al. (2017). At the first stage, the measurement model was confirmed, whereas, at the second stage, the proposed relationships of the variables were examined.
Findings
Normality of data and common method bias
To test the normality of the data, the authors assessed skewness and kurtosis. The results, indicated in Table 2, validate that the data were normal because the skewness and kurtosis values of all the constructs were found within the standard level ±2, as advised by George and Mallery (2010). The data of all the constructs were collected from the same respondents who answered all the questions at the same point in time. Such type of data, according to Podsakoff et al. (2003), might be confronted with a common method bias (CMB) issue. Therefore, to detect the issue of CMB, the authors run Harmon’s one‐factor test, which is the most common approach for testing CMB in prior research studies. Harmon’s one‐factor test shows a 44.15% variance of the first factor which is less than the standard value of 50% recommended by Podsakoff et al. (2003). This indicates that CMB was not a concern in the present study.
Measurement model
To quantify the measurement model of the proposed reflective variables, this study follows the suggested criteria of Hair et al. (2017) by testing internal consistency, convergent validity and discriminant validity. The final values of the composite reliability (CR), indicating internal consistency and reliability, were found between 0.994 and 0.877 of all the constructs, which exceed the cut-off level of 0.70 recommended by Hair et al. (2010). Convergent validity that can be assessed from the values of factor loadings (FL) and average variance extracted (AVE) should be greater than 0.70 and 0.50, respectively (Hair et al., 2010). To this end, Table 2 demonstrates that our results endorse a good convergent validity as the values of FL and AVE fulfill the criteria.
Discriminant validity was assessed by three methods: Fornell and Larcker (1981) suggestions, the cross-loading method advised by Hsu and Lin (2016) and the Heterotrait–Monotrait (HTMT) method suggested by Henseler et al. (2015). According to the first method, we examine the discriminant validity by calculating and comparing the correlation values of the constructs with the AVE’s square root of all the constructs. The results shown in Table 3 demonstrate good discriminant validity as the AVE square root values are greater than the corresponding correlation values of the constructs. Moreover, as shown in the cross-loadings table in the Appendix, the cross-loading values of other variables are lower than the FL values of each construct, indicating good discriminant validity.
The results depicted in Table 4 demonstrate good discriminant validity through the HTMT approach, as HTMT values of all the variables are lower than the threshold level of 0.85 as recommended by Henseler et al. (2015).
Hypotheses results
Table 5 and Figure 2 indicate the structure model results which were obtained by using a bootstrapping process with 2,000 interactions (Hair et al., 2017). The proposed model of the study accounts for 47% of the variance in intentions to invest in ṣukūk. As expected, intentions to invest in ṣukūk are significantly determined by compatibility (ß = 0.095, p < 0.01), internal influence (ß = 0.370, p < 0.001), external influence (ß = 0.149, p < 0.001), intrinsic motivation (ß = 0.134, p < 0.01) and religion (ß = 0.275, p < 0.001). All the proposed constructs were found to have significant effects on the intention to invest in ṣukūk. Therefore, H1, H2, H3, H4 and H5 were supported.
To assess the moderation effects of the proposed hypotheses (H5a, H5b, H5c and H5d), this study followed Yoon and Steege (2013) by applying the product-indicator approach. First, interaction constructs were established by cross-multiplying the measuring items of compatibility and religion, internal influence and religion, external influence and religion and finally, intrinsic motivation and religious aspect. To decrease the possible chances of multicollinearity, the measuring items of all variables were standardized before cross-multiplication (Aiken et al., 1991).
As depicted from Table 6 and Figure 2, it is found that religion moderates the association between internal influence and behavioral intentions (ß = 0.059, p < 0.01), as well as external influence and behavioral intentions (ß = 0.045, p < 0.05). Thus, the proposed moderation hypotheses H5b and H5c were accepted.
Discussion and implications
As mentioned, ṣukūk has recently become popular across financial markets, especially in Islamic countries. However, few research studies have focused on factors of investors’ intentions that motivate investment in ṣukūk. This study examines, through SCT, the effects of cognitive, personal, environmental and behavioral factors on investors’ BI regarding ṣukūk investment in Pakistan. The results reveal that compatibility, internal influence, external influence, intrinsic motivation and religion have a significant positive influence on investors’ BI to use ṣukūk for the purpose of investment. According to the statistical results, the above factors have shown R2 = 47%, the total variance in investors’ BI, which according to Yogesh (2017) is quite an acceptable level.
Among these variables, the internal influence was determined as the strongest predictor of investors’ BI to invest in ṣukūk. Similar results were noted by Van Rooij et al. (2011), Abreu and Mendes (2012), Jamshidi and Hussin (2016) and Tauni et al. (2017). This indicates that internal influence plays a vital role in investors’ decisions on investment in financial products. As there is a collectivist culture in Pakistan, as highlighted by Khan et al. (2017) and ṣukūk constitute a Sharīʿah-compliant investment product, the influence of ṣukūk adoption by individuals on their social network seems evident and reasonable. As expected, compatibility showed a positive and significant association with investors’ BI, which is in line with the previous studies of Wessels and Drennan (2010), Boateng et al. (2016) and Jamshidi and Hussin (2016). Individuals favor and adopt those products and services that suit their lifestyle. As ṣukūk is an Islamic financial instrument, people in Muslim-majority countries like Pakistan consider them compatible with their lifestyle as demonstrated by the significant statistical results.
The results further disclose a significant positive association between external influence and investors’ BI, which are supported by the results of Bhattacherjee (2000), Song (2014) and Khan et al. (2020a). This result implies that the more people know about ṣukūk investment through communication channels such as television, newspapers and social media, the more they are likely to invest in ṣukūk. Likewise, intrinsic motivation exerts a significant impact on investors’ BI, which are similar to the results of Venkatesh (2000) and Zhang et al. (2008). This result implies that Muslims feel inner satisfaction by adopting Islamic financial instruments or products. As mentioned previously, inner satisfaction with adopting Islamic behavior is intrinsic to religion.
The second objective of the current study was to test the interaction effects of the religious aspect along with its direct effects on investors’ BI. As reported by previous research studies of Ashidiqi and Arundina (2017), Mbawuni and Nimako (2017) and Duqi (2019), significant positive effects of the religious aspect were found on investors’ BI. Besides the direct effects, the results demonstrate that religion significantly moderates between internal influence and BI, as well as external influence and BI. As Muslims believe in the system of reward and punishment on Judgment Day, they are naturally inclined toward adopting Islamic financial instruments or products. The latest bulletin issued by the State Bank of Pakistan showed quarterly growth of 7.3% in assets and 9.3% in deposits of Islamic banks from April to June 2019 (SBP, 2019). Such a commendable growth rate shows people’s inclination toward Islamic financial instruments. Therefore, the higher the awareness about ṣukūk from social networks or through the mass media, the higher the chance for investors to invest in ṣukūk.
Theoretically, the current study has several notable contributions to the extant literature. First of all, there are only a few research studies that have tried to investigate the factors that explain and predict investors’ BI for ṣukūk investment. The current study extends the literature by identifying more relevant factors such as external influence, compatibility and internal influence that significantly explain investors’ BI to invest in ṣukūk. Second, the direct effect of religiosity was confirmed by published studies; however, this study identifies that the religious aspect also acts as a moderator. Third, this study enhances our understanding that intrinsic motivation matters in adopting Islamic financial instruments. Moreover, this study is a fresh attempt to investigate intrinsic motivation in the context of Islamic financial instruments such as ṣukūk. Finally, the current study tested SCT in the context of ṣukūk investment intentions and adds fresh evidence of SCT’s applicability to the Islamic instrument. Using SCT to ṣukūk investment intentions is a rich contribution that expounds the environmental and social perspective of ṣukūk acceptance. This will further encourage similar explorations through SCT in the context of Islamic banking instruments and products.
Practically, this study may help the issuers of ṣukūk in enhancing the adoption of ṣukūk among potential individual investors. As shown earlier, the religious perspective of ṣukūk not only affects BI positively but it also acts as a moderator that strengthens the association between internal influence, external influence and BI. This shows that issuers, including the government, can effectively increase investment in ṣukūk by using mass media to promote the religious rationale of ṣukūk to the general public. Individuals opt for an instrument if it fits their lifestyle, as indicated by the results. As the ṣukūk instrument fits with the lifestyle of Muslims because of its inherent Islamic characteristics, Pakistani Muslim investors are more likely to adopt ṣukūk provided they are well aware of ṣukūk investment. Ṣukūk issuers can use existing ṣukūk holders as a tool to enhance the promotion of ṣukūk among potential investors. They can encourage ṣukūk holders to discuss the religious perspective of ṣukūk in their social circles, as is shown by the results.
Conclusion and limitations
Islamic financial instruments/products have received the attention of researchers globally, especially in Muslim-majority countries. Various adoption models and theories are being applied to identify the factors affecting the adoption of Islamic financial instruments or products. However, ṣukūk has received limited research attention compared to other Islamic financial instruments. To fill in the gap, the current study offers a conceptual model based on SCT that focuses on cognitive, personal, environmental and behavioral factors affecting ṣukūk adoption in Pakistan. For empirical testing of the proposed model, the required data was gathered through survey-questionnaires using a convenient sampling technique. The findings exhibit that compatibility, internal influence, external influence, intrinsic motivation and religiosity have positive significant effects on investors’ BI to invest in ṣukūk. In addition, the results reveal that the religious aspect moderates between internal influence and BI, as well as external influence and BI. Moreover, the study not only adds to the existing literature on ṣukūk it will also enable issuers of ṣukūk to understand the motivational factors that enhance the adoption of ṣukūk among potential investors.
This study acknowledges some limitations. First, being cross-sectional in nature, the current study is unable to account for changing human behavior over time. Therefore, future studies can consider longitudinal analysis to determine how temporal changes influence investors’ BI. Second, this research covered only ṣukūk; thus, the results cannot be generalized and applied to other Islamic financial instruments or products. In this connection, future studies could test this model in examining the cognitive, personal and behavioral determinants of other Islamic instruments or products to further the results of the current study. Third, this study did not consider the actual adoption of ṣukūk. According to Boateng et al. (2016), it is the actual usage that depends on the objective of the organization. Therefore, future studies should also consider the actual usage of ṣukūk. Fourth, the study has generalizability issues across Pakistan, as the survey was conducted only in the capital city, Islamabad. Future studies could test ṣukūk investment intentions in other cities of Pakistan. Finally, the current study only investigated the ṣukūk investment intentions of individual investors. It is proposed that institutional perspectives be probed in future studies.
Figures
Figure 1.
Conceptual model
Figure 2.
Model with results
Participants’ demographics
| Demographics | Frequency | (%) | |
|---|---|---|---|
| Gender | Male | 319 | 69 |
| Female | 143 | 31 | |
| Age | <25 | 113 | 24.5 |
| 25–35 | 193 | 41.8 | |
| 35–50 | 109 | 23.6 | |
| >50 | 47 | 10.2 | |
| Education level | <bachelor’s degree | 78 | 16.9 |
| bachelor’s degree | 126 | 27.3 | |
| master’s degree | 207 | 44.8 | |
| >master’s degree | 51 | 11 | |
| Income | <20,000 | 41 | 8.9 |
| 20,000–50,000 | 193 | 41.8 | |
| 50,000–100,000 | 176 | 38.1 | |
| >100,000 | 52 | 11.3 | |
| Ṣukūk investment | No | 274 | 59.3 |
| Yes | 188 | 40.7 |
Measurement model
| Construct | Items | FL | CA | CR | AVE | Skewness | Kurtosis |
|---|---|---|---|---|---|---|---|
| Compatibility (Com) | Com1 | 0.900 | 0.892 | 0.933 | 0.822 | −0.065 | −0.278 |
| Com2 | 0.925 | ||||||
| Com3 | 0.895 | ||||||
| Internal influence (II) | II1 | 0.915 | 0.910 | 0.944 | 0.848 | −0.246 | −0.382 |
| II2 | 0.936 | ||||||
| II3 | 0.911 | ||||||
| External influence (EI) | EI1 | 0.909 | 0.793 | 0.877 | 0.707 | 0.050 | 0.210 |
| EI2 | 0.701 | ||||||
| EI3 | 0.895 | ||||||
| Intrinsic motivation (IM) | IM1 | 0.896 | 0.827 | 0.897 | 0.744 | −0.226 | −0.072 |
| IM2 | 0.810 | ||||||
| IM3 | 0.878 | ||||||
| Religious aspect (RA) | RA1 | 0.859 | 0.846 | 0.899 | 0.691 | −0.127 | −0.109 |
| RA2 | 0.877 | ||||||
| RA3 | 0.889 | ||||||
| RA4 | 0.684 | ||||||
| Behavioral intention (BI) | BI1 | 0.913 | 0.843 | 0.904 | 0.760 | −0.184 | −0.133 |
| BI2 | 0.785 | ||||||
| BI3 | 0.912 |
FL: Factor loading; CR: Composite reliability; AVE: Average variance extracted; the loadings are significant at p < 0.001 level
Correlation values of the constructs
| Constructs | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| 1. BI | 0.872 | |||||
| 2. Com | 0.387 | 0.907 | ||||
| 3. EI | 0.334 | 0.325 | 0.841 | |||
| 4. IM | 0.361 | 0.348 | 0.354 | 0.862 | ||
| 5. RA | 0.485 | 0.248 | 0.135 | 0.174 | 0.831 | |
| 6. II | 0.572 | 0.353 | 0.19 | 0.255 | 0.386 | 0.921 |
Diagonal elements and italics are the square roots of the AVE of each construct
Discriminant validity (HTMT)
| Constructs | 1 | 2 | 3 | 4 | 5 | 6 |
|---|---|---|---|---|---|---|
| 1. BI | ||||||
| 2. COM | 0.436 | |||||
| 3. EI | 0.389 | 0.381 | ||||
| 4. IM | 0.432 | 0.402 | 0.431 | |||
| 5. RA | 0.557 | 0.286 | 0.152 | 0.206 | ||
| 6. II | 0.641 | 0.391 | 0.238 | 0.297 | 0.44 |
Path coefficients and hypotheses testing
| Hypothesis | Relationship | Std. Beta | t-value | p-value | Decision |
|---|---|---|---|---|---|
| H1 | Com ----> BI | 0.095 | 1.984 | 0.047* | Supported |
| H2 | II ----> BI | 0.37 | 7.616 | 0.000*** | Supported |
| H3 | EI ----> BI | 0.149 | 3.989 | 0.000*** | Supported |
| H4 | IM ----> BI | 0.134 | 3.149 | 0.002** | Supported |
| H5 | RA ----> BI | 0.275 | 5.747 | 0.000*** | Supported |
p < 0.5,
p < 0.01,
p < 0.001
Moderating effect
| Hypothesis | Relationship | Std. Beta | t-value | p-value | Decision |
|---|---|---|---|---|---|
| H5a | Com*RA ----> BI | −0.011 | 0.505 | 0.614 | Not supported |
| H5b | II*RA ----> BI | 0.059 | 2.992 | 0.003** | Supported |
| H5c | EI*RA ----> BI | 0.045 | 2.367 | 0.018* | Supported |
| H5d | IM*RA ----> BI | −0.036 | 1.587 | 0.113 | Not supported |
p < 0.5,
p < 0.01,
p < 0.001
Cross loadings
| Items | BI | COM | EI | IM | RA | SI |
|---|---|---|---|---|---|---|
| BI1 | 0.913 | 0.360 | 0.304 | 0.322 | 0.479 | 0.540 |
| BI2 | 0.785 | 0.257 | 0.222 | 0.289 | 0.279 | 0.377 |
| BI3 | 0.912 | 0.377 | 0.333 | 0.334 | 0.475 | 0.552 |
| Com1 | 0.323 | 0.900 | 0.294 | 0.303 | 0.239 | 0.307 |
| Com2 | 0.377 | 0.925 | 0.287 | 0.317 | 0.244 | 0.323 |
| Com3 | 0.348 | 0.895 | 0.305 | 0.325 | 0.191 | 0.329 |
| EI1 | 0.334 | 0.298 | 0.909 | 0.317 | 0.130 | 0.159 |
| EI2 | 0.185 | 0.208 | 0.701 | 0.245 | 0.021 | 0.221 |
| EI3 | 0.295 | 0.301 | 0.895 | 0.324 | 0.160 | 0.130 |
| IM1 | 0.333 | 0.337 | 0.329 | 0.896 | 0.163 | 0.210 |
| IM2 | 0.282 | 0.253 | 0.224 | 0.810 | 0.0900 | 0.261 |
| IM3 | 0.318 | 0.305 | 0.353 | 0.878 | 0.191 | 0.195 |
| RA1 | 0.390 | 0.177 | 0.102 | 0.133 | 0.859 | 0.277 |
| RA2 | 0.401 | 0.214 | 0.099 | 0.161 | 0.877 | 0.297 |
| RA3 | 0.444 | 0.215 | 0.120 | 0.135 | 0.889 | 0.371 |
| RA4 | 0.370 | 0.217 | 0.129 | 0.151 | 0.684 | 0.334 |
| SI1 | 0.531 | 0.323 | 0.149 | 0.222 | 0.357 | 0.915 |
| SI2 | 0.530 | 0.330 | 0.190 | 0.247 | 0.366 | 0.936 |
| SI3 | 0.519 | 0.322 | 0.188 | 0.236 | 0.344 | 0.911 |
Appendix
Survey questionnaire
Compatibility (Boateng et al., 2016):
Investing in ṣukūk would fit my lifestyle.
Investing in ṣukūk would fit well with how I like to do my investment.
Investing in ṣukūk would be compatible with most aspects of my investing activities.
Internal (social) influence (Bhattacherjee, 2000; Song, 2014):
My peers/colleagues/friends thought that I should use ṣukūk for managing investments.
People I knew thought that using ṣukūk was a good idea.
People I knew influenced me to try out ṣukūk for managing investments.
External influence (Bhattacherjee, 2000; Song, 2014):
Media information about ṣukūk influence my adoption decision.
Information from mass media would induce me to try ṣukūk.
Mass media consistently recommend people to use ṣukūk.
Intrinsic motivation (Tremblay et al., 2009):
Because it is part of the way in which I have chosen to live my life.
Because I derive much pleasure from investing and adopting in Islamic products like ṣukūk.
For satisfaction, I am investing in Islamic products like ṣukūk.
Religiosity (Riaz et al., 2017; Duqi, 2019):
Ṣukūk provides a Sharīʿah-compliant alternate to conventional bonds.
I prefer to use ṣukūk due to the Islamic prohibition of ribā (interest).
I like an investment in ṣukūk due to religious motivation.
I prefer to avoid usury investment.
Behavioral intentions (Warsame and Ireri, 2016):
I Intend to invest in ṣukūk at the moment.
I predict I will continue to invest in ṣukūk on a regular basis.
For my investment, I would invest in ṣukūk.
References
Abreu, M. and Mendes, V. (2012), “Information, overconfidence and trading: do the sources of information matter?”, Journal of Economic Psychology, Vol. 33 No. 4, pp. 868-881.
Agarwal, R. and Prasad, J. (1997), “The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies”, Decision Sciences, Vol. 28 No. 3, pp. 557-582.
Agarwal, R. and Prasad, J. (1998), “The antecedents and consequents of user perceptions in information technology adoption”, Decision Support Systems, Vol. 22 No. 1, pp. 15-29.
Ahmed, E.R., Islam, M.A., Alabdullah, T.T.Y. and Amran, A.B. (2019), “A qualitative analysis on the determinants of legitimacy of sukuk”, Journal of Islamic Accounting and Business Research, Vol. 10 No. 3, pp. 342-368.
Aiken, L.S., West, S.G. and Reno, R.R. (1991), Multiple Regression: Testing and Interpreting Interactions, Sage, Newbury Park, CA.
Ajzen, I. (1985), “From intentions to actions: a theory of planned behavior”, in Jkuhl, J.B. (Ed.), Action Control: From Cognition to Behavior, Springer Verlag, New York, NY, pp. 11-39.
Allah Pitchay, A.B., Mohd Thas Thaker, M.A.B., Azhar, Z., Mydin, A.A. and Mohd Thas Thaker, H.B. (2019), “Factors persuade individuals’ behavioral intention to opt for Islamic bank services: Malaysian depositors’ perspective”, Journal of Islamic Marketing, Vol. 11 No. 1, pp. 234-250.
Ashidiqi, C. and Arundina, T. (2017), “Indonesia students’s intention to invest in sukuk: theory of planned behaviour approach”, Int. J. Econ. Res, Vol. 14 No. 15, pp. 395-407.
Bandura, A. (1986a), “Fearful expectations and avoidant actions as coeffects of perceived self-inefficacy”, American Psychologist, Vol. 41 No. 12, pp. 1389-1391.
Bandura, A. (1986b), Social Foundations of Thought and Action: A Social Cognitive Theory, Prentice-Hall, Englewood Cliffs, NJ.
Bandura, A. (1989), “Human agency in social cognitive theory”, American Psychologist, Vol. 44 No. 9, pp. 1175-1184.
Bandura, A. (1991), “Social cognitive theory of self-regulation”, Organizational Behavior and Human Decision Processes, Vol. 50 No. 2, pp. 248-287.
Bandura, A. and Walters, R.H. (1977), Social Learning Theory, Prentice-Hall, Englewood Cliffs, NJ, Vol. 1.
Bhattacherjee, A. (2000), “Acceptance of e-commerce services: the case of electronic brokerages”, IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, Vol. 30 No. 4, pp. 411-420.
Boateng, H., Adam, D.R., Okoe, A.F. and Anning-Dorson, T. (2016), “Assessing the determinants of internet banking adoption intentions: a social cognitive theory perspective”, Computers in Human Behavior, Vol. 65, pp. 468-478.
Brown, J.R., Ivković, Z., Smith, P.A. and Weisbenner, S. (2008), “Neighbors matter: causal community effects and stock market participation”, The Journal of Finance, Vol. 63 No. 3, pp. 1509-1531.
Campbell, K., Tabner, I.T. and Changwony, F.K. (2015), “Social engagement and stock market participation”, Review of Finance, Vol. 19 No. 1, pp. 317-366.
Casper, M. (2001), “A definition of social environment”, American Journal of Public Health, Vol. 91 No. 3, p. 465.
Chan, S-C. (2004), “Understanding internet banking adoption and use behavior: a Hong Kong perspective”, Journal of Global Information Management (Management), Vol. 12 No. 3, pp. 21-43.
Chin, W.W., Marcolin, B.L. and Newsted, P.R. (2003), “A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study”, Information Systems Research, Vol. 14 No. 2, pp. 189-217.
Davis, A. (2006), “The role of the mass media in investor relations”, Journal of Communication Management, Vol. 10 No. 1, pp. 7-17.
Deephouse, D.L. (2000), “Media reputation as a strategic resource: an integration of mass communication and resource-based theories”, Journal of Management, Vol. 26 No. 6, pp. 1091-1112.
Duflo, E. and Saez, E. (2002), “Participation and investment decisions in a retirement plan: the influence of colleagues’ choices”, Journal of Public Economics, Vol. 85 No. 1, pp. 121-148.
Duflo, E. and Saez, E. (2003), “Implications of information and social interactions for retirement saving decisions”, Pension Research Council Working Paper, No. 429, pp. 1-28, available at https://repository.upenn.edu/prc_papers/429
Duqi, A. (2019), “Factors affecting investors’ decision regarding investment in Islamic sukuk”, Qualitative Research in Financial Markets, Vol. 11 No. 1, pp. 60-72.
Everett, R. (1995), Diffusion of Innovations, 3rd ed., Free Press, New York, NY.
Fathurahman, H. and Fitriati, R. (2013), “Comparative analysis of return on sukuk and conventional bonds”, American Journal of Economics, Vol. 3 No. 3, pp. 159-163.
Font, X., Garay, L. and Jones, S. (2016), “A social cognitive theory of sustainability empathy”, Annals of Tourism Research, Vol. 58, pp. 65-80.
Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobservable variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.
George, D. and Mallery, P. (2010), SPSS for Windows Step by Step a Simple Study Guide and Reference (10. Bask, ), Pearson Education Inc., Boston, MA.
Gerhart, B. and Fang, M. (2015), “Pay, intrinsic motivation, extrinsic motivation, performance, and creativity in the workplace: revisiting long-held beliefs”, Annual Review of Organizational Psychology and Organizational Behavior, Vol. 2 No. 1, pp. 489-521.
Gu, D., Khan, S., Khan, I.U. and Khan, S.U. (2019), “Understanding mobile tourism shopping in Pakistan: an integrating framework of innovation diffusion theory and technology acceptance model”, Mobile Information Systems, Vol. 2019, available at https://doi.org/10.1155/2019/1490617 (accessed 12 August 2020).
Gunawan, D.D. and Huarng, K.H. (2015), “Viral effects of social network and media on consumers’ purchase intention”, Journal of Business Research, Vol. 68 No. 11, pp. 2237-2241.
Hair, J.F., Anderson, R.E., Tatham, R.L. and William, C.B. (2010), Multivariate Data Analysis, Pearson, NJ.
Hair, J.F., Jr, Sarstedt, M., Ringle, C.M. and Gudergan, S.P. (2017), Advanced Issues in Partial Least Squares Structural Equation Modeling, Sage Publications, Thousand Oaks, CA.
Hanafizadeh, P., Behboudi, M., Koshksaray, A.A. and Tabar, M.J.S. (2014), “Mobile-banking adoption by Iranian bank clients”, Telematics and Informatics, Vol. 31 No. 1, pp. 62-78.
Henseler, J., Ringle, C.M. and Sarstedt, M. (2015), “A new criterion for assessing discriminant validity in variance-based structural equation modeling”, Journal of the Academy of Marketing Science, Vol. 43 No. 1, pp. 115-135.
Hsu, C.L. and Lin, J.C.C. (2016), “An empirical examination of consumer adoption of internet of things services: network externalities and concern for information privacy perspectives”, Computers in Human Behavior, Vol. 62, pp. 516-527.
Jamshidi, D. and Hussin, N. (2016), “Islamic credit card adoption understanding: when innovation diffusion theory meets satisfaction and social influence”, Journal of Promotion Management, Vol. 22 No. 6, pp. 897-917.
Khan, I.U., Hameed, Z. and Khan, S.U. (2017), “Understanding online banking adoption in a developing country: UTAUT2 with cultural moderators”, Journal of Global Information Management (Management), Vol. 25 No. 1, pp. 43-65.
Khan, S.U., Khan, I.U., Khan, M.H. and Khan, S.U. (2019), “Analyzing the acceptance of Islamic personal financing using extended TRA model: evidence from Khyber Pakhtunkhwa, Pakistan”, Abasyn Journal of Social Sciences, Vol. 12 No. 2, pp. 277-289.
Khan, S.U., Liu, X., Khan, I.U., Liu, C. and Hameed, Z. (2018), “Measuring the effects of risk and cultural dimensions on the adoption of online stock trading: a developing country perspective”, International Journal of Enterprise Information Systems ( Systems), Vol. 14 No. 3, pp. 106-127.
Khan, S.U., Liu, X., Khan, I.U., Liu, C. and Rasheed, M.I. (2020a), “Assessing the investors’ acceptance of electronic stock trading in a developing country: the mediating role of perceived risk dimensions”, Information Resources Management Journal ( Journal), Vol. 33 No. 1, pp. 59-82.
Khan, S.U., Liu, X.D., Liu, C., Khan, I.U. and Hameed, Z. (2020b), “Understanding uncertainty dimensions and internet stock trading service in China from a social cognitive perspective”, Information Technology and People, doi: 10.1108/ITP-02-2019-0062. (accessed 12 August 2020).
Lee-Partridge, J.E. and Ho, P.S. (2003), “A retail investor's perspective on the acceptance of internet stock trading”, in Proceedings of the 36th Annual HI International Conference on System Sciences.
Lerner, R.M. (1982), “Children and adolescents as producers of their own development”, Developmental Review, Vol. 2 No. 4, pp. 342-370.
López-Nicolás, C., Molina-Castillo, F.J. and Bouwman, H. (2008), “An assessment of advanced mobile services acceptance: contributions from TAM and diffusion theory models”, Information and Management, Vol. 45 No. 6, pp. 359-364.
Lusardi, A. and Mitchell, O.S. (2011), “Financial literacy around the world: an overview”, Journal of Pension Economics and Finance, Vol. 10 No. 4, pp. 497-508.
Madrian, B.C. and Shea, D.F. (2001), “The power of suggestion: inertia in 401 (k) participation and savings behavior”, The Quarterly Journal of Economics, Vol. 116 No. 4, pp. 1149-1187.
Mathieson, K. (1991), “Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior”, Information Systems Research, Vol. 2 No. 3, pp. 173-191.
Mbawuni, J. and Nimako, S.G. (2017), “Determinants of Islamic banking adoption in Ghana”, International Journal of Islamic and Middle Eastern Finance and Management, Vol. 10 No. 2, pp. 264-288.
Mimouni, K., Smaoui, H., Temimi, A. and Al-Azzam, MD. (2019), “The impact of sukuk on the performance of conventional and Islamic banks”, Pacific-Basin Finance Journal, Vol. 54, pp. 42-54.
Mohammadi, H. (2015), “A study of mobile banking usage in Iran”, International Journal of Bank Marketing, Vol. 33 No. 6, pp. 733-759.
Najeeb, S.F., Bacha, O. and Masih, M. (2017), “Does a held-to-maturity strategy impede effective portfolio diversification for Islamic bond (sukuk) portfolios? A multi-scale continuous wavelet correlation analysis”, Emerging Markets Finance and Trade, Vol. 53 No. 10, pp. 2377-2393.
Njuguna, P.K. (2018), “Determinants of investment intentions of individual retail stock market investors on the Nairobi securities exchange in Kenya”, PhD thesis, COHRED-JKUAT.
PBS (2019), “Pakistan bureau of statistics report of religion”, available at: www.pbs.gov.pk/content/population-religion (accessed 20 March 2020).
Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y. and Podsakoff, N.P. (2003), “Common method biases in behavioral research: a critical review of the literature and recommended remedies”, Journal of Applied Psychology, Vol. 88 No. 5, pp. 879-903.
Rahman, A. and Anwar, M. (2016), “Customer loyalty toward Islamic and conventional banks; mediator role of customer satisfaction”, SSRN Electronic Journal, Vol. 1 No. 15, pp. 1-23.
Rana, N.P. and Dwivedi, Y.K. (2015), “Citizen’s adoption of an e-government system: validating extended social cognitive theory (SCT)”, Government Information Quarterly, Vol. 32 No. 2, pp. 172-181.
Ratten, V. (2010), “Social cognitive theory and the adoption of e-book devices”, International Journal of E-Business Management, Vol. 4 No. 2, pp. 3-16.
Ratten, V. (2013), “Social cognitive theory in mobile banking innovations”, In Mobile Applications and Knowledge Advancements in E-Business, IGI Global, Hershey, PA, pp. 42-55.
Reinartz, W., Haenlein, M. and Henseler, J. (2009), “An empirical comparison of the efficacy of covariance-based and variance-based SEM”, International Journal of Research in Marketing, Vol. 26 No. 4, pp. 332-344.
Riaz, U., Khan, M. and Khan, N. (2017), “An Islamic banking perspective on consumers’ perception in Pakistan”, Qualitative Research in Financial Markets, Vol. 9 No. 4, pp. 337-358.
Rice, B. and Bennett, R. (1998), “The relationship between brand usage and advertising tracking measurements: international findings”, Journal of Advertising Research, Vol. 38 No. 3, pp. 58-66.
Sayeda, M.Z. (2019), “Factors influencing the community behavioral intention for adoption of Islamic banking: evidence from Pakistan”, International Journal of Islamic and Middle Eastern Finance and Management, Vol. 12 No. 4, pp. 586-600.
SBP (2019), “Islamic banking bulletin”, available at: www.sbp.org.pk/ibd/bulletin/2019/Jun (accessed 12 August 2019).
Schmidt, A.P. (2019), “The impact of cognitive style, consumer demographics and cultural values on the acceptance of Islamic insurance products among American consumers”, International Journal of Bank Marketing, Vol. 37 No. 2, pp. 492-506.
Shang, R.A., Chen, Y.C. and Shen, L. (2005), “Extrinsic versus intrinsic motivations for consumers to shop on-line”, Information and Management, Vol. 42 No. 3, pp. 401-413.
Song, J. (2014), “Understanding the adoption of mobile innovation in China”, Computers in Human Behavior, Vol. 38, pp. 339-348.
Tauni, M.Z., Fang, H.X. and Iqbal, A. (2017), “The role of financial advice and word-of-mouth communication on the association between investor personality and stock trading behavior: evidence from Chinese stock market”, Personality and Individual Differences, Vol. 108, pp. 55-65.
Tornatzky, L.G. and Klein, K.J. (1982), “Innovation characteristics and innovation adoption-implementation: a meta-analysis of findings”, IEEE Transactions on Engineering Management, Vol. EM-29 No. 1, pp. 28-45.
Tremblay, M.A., Blanchard, C.M., Taylor, S., Pelletier, L.G. and Villeneuve, M. (2009), “Work extrinsic and intrinsic motivation scale: its value for organizational psychology research”, Canadian Journal of Behavioural Science/Revue Canadienne Des Sciences du Comportement, Vol. 41 No. 4, pp. 213-226.
Vallerand, R.J. (2007), “Intrinsic and extrinsic motivation in sport and physical activity”, Handbook of Sport Psychology, Vol. 3, pp. 59-83.
Van Rooij, M.C., Lusardi, A. and Alessie, R.J. (2011), “Financial literacy and retirement planning in The Netherlands”, Journal of Economic Psychology, Vol. 32 No. 4, pp. 593-608.
Venkatesh, V. (2000), “Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model”, Information Systems Research, Vol. 11 No. 4, pp. 342-365.
Warsame, M.H. and Ireri, E.M. (2016), “Does the theory of planned behaviour (TPB) matter in sukuk investment decisions?”, Journal of Behavioral and Experimental Finance, Vol. 12, pp. 93-100.
Wessels, L. and Drennan, J. (2010), “An investigation of consumer acceptance of M-banking”, International Journal of Bank Marketing, Vol. 28 No. 7, pp. 547-568.
Wood, R. and Bandura, A. (1989), “Social cognitive theory of organizational management”, Academy of Management Review, Vol. 14 No. 3, pp. 361-384.
Yogesh, D. (2017), “Factors influencing adoption of mobile banking by Jordanian bank customers: extending UTAUT2 with trust”, International Journal of Information Management, Vol. 37 No. 3, pp. 99-110.
Yoo, S.J., Han, S-h. and Huang, W. (2012), “The roles of intrinsic motivators and extrinsic motivators in promoting e-learning in the workplace: a case from South Korea”, Computers in Human Behavior, Vol. 28 No. 3, pp. 942-950.
Yoon, H.S. and Steege, L.M.B. (2013), “Development of a quantitative model of the impact of customers’ personality and perceptions on internet banking use”, Computers in Human Behavior, Vol. 29 No. 3, pp. 1133-1141.
Yu-Lei, R., Die-Feng, P. and Cheng, D-C. (2010), “Does media attention cause abnormal return? – Evidence from china's stock market”, Systems Engineering-Theory and Practice, Vol. 2, pp. 287-297.
Zainul, N., Osman, F. and Mazlan, S.H. (2004), “E-Commerce from an Islamic perspective”, Electronic Commerce Research and Applications, Vol. 3 No. 3, pp. 280-293.
Zamani, A. and Talatapeh, M.B.B. (2014), “Discussion of the motivation in the Islamic and non-Islamic worlds”, Journal of Applied Environmental and Biological Sciences, Vol. 4 No. 4, pp. 68-73.
Zhang, S., Zhao, J. and Tan, W. (2008), “Extending TAM for online learning systems: an intrinsic motivation perspective”, Tsinghua Science and Technology, Vol. 13 No. 3, pp. 312-317.
Acknowledgements
This work was partially supported by the National Natural Science Foundation of China (No. 71901025, 71771024), Humanities and Social Sciences Foundation of the Ministry of Education of China (18YJC790106, 18YJCZH134).
Corresponding author
About the authors
Safeer Ullah Khan received his PhD degree in Management Sciences from the Donlinks School of Economics and Management, University of Science and Technology Beijing, China. Currently, he is working as assistant professor at the Department of Business Administration, IBA, Gomal University, Dera Ismail Khan, KP, Pakistan. He has published several research articles in leading journals with a focus on digital, behavioral and Islamic finance.
Ikram Ullah Khan earned his PhD in Business Administration from the University of Science and Technology of China. Currently, he is a faculty member of the Institute of Management Sciences, University of Science and Technology Bannu, KP, Pakistan. With multiple publications in renowned journals, his research focus is on behavioral and digital aspects of banking and finance.
Ismail Khan is a PhD scholar at the School of Management, Sunway University Business School, Malaysia. His research focus is on corporate governance and Islamic finance.
Saif Ud Din is Assistant Professor at the college of Business-Rabigh, King Abdul Aziz University, Jeddah, Saudi Arabia.
Abid Ullah Khan received a master’s degree in Science in Economics from the Department of Economics, University of Science and Technology Bannu, Bannu, Pakistan. His research focus is on environmental and Islamic economics.