Extending unified theory of acceptance and use of technology with perceived monetary value for smartphone adoption at the bottom of the pyramid

https://doi.org/10.1016/j.ijinfomgt.2019.11.004Get rights and content

Highlights

  • There is scarcity of studies related to technology adoption at the BOP.

  • We propose a framework which extends UTAUT with Perceived Monetary Value (PMV).

  • Factors of UTAUT and PMV are found to impact smartphone adoption at the BOP.

  • Age and Experience moderate a few relationships proposed in the framework.

Abstract

The affluent markets of developed countries have become very competitive. Therefore, companies are trying to explore market opportunities at the segment of low-income people termed as “Bottom of the Pyramid” (BOP). With the proliferation in popularity and reduction in the price of smartphones, there is a potential market opportunity for smartphone producing companies at the BOP segment. The companies need to identify the factors influencing smartphone adoption at the BOP in order to explore this market opportunity. The current study extends the Unified Theory of Acceptance and Use of Technology (UTAUT) with “Perceived Monetary Value” to investigate the antecedents of smartphone adoption at the BOP. Empirical analysis has shown that “Performance Expectancy” (PE), “Effort Expectancy” (EE), “Social Influence” (SI), and “Perceived Monetary Value” (PMV) predict the “Behavioral Intention” (BI), and BI and “Facilitating Conditions” (FC) predict the “Use Behavior” (UB). Findings from this study can be used by the managers of the companies targeting the BOP segment in pricing, marketing, and product-specific decision-making process. The policymakers can also analyze the results of this study for successful implementation and delivery of Information and Communication Technology (ICT) based services for the BOP segment.

Introduction

Researchers have recommended the use of Information and Communication Technology (ICT) for the socio-economic development of the low-income people termed as “Bottom of the Pyramid” (BOP) (Berger & Nakata, 2013). The socio-economic conditions of these low-income people are different from other people (Prahlad, 2004). They are characterized by low literacy, poor health condition, limited access to the media, strive to meet basic needs, and geographical isolation (Prahlad, 2004). They are socially isolated from other segments which induce them to increase the consumption of aspirational products in order to reduce the feeling of isolation (Alwitt, 1995; Hill & Stephens, 1997). A smartphone can act as an aspirational product in the BOP segment due to its growing popularity (Meeker, 2015) and reduced price. Adoption of smartphones and Internet may encourage the BOP people to embrace online systems (Veeramootoo, Nunkoo, & Dwivedi, 2018). In order to increase the usage of smartphones at the BOP, one needs to understand the underlying factors influencing technology adoption in this segment.

The research in the domain of technology adoption has evolved over several years (Williams, Dwivedi, Lal, & Schwarz, 2009), and this evolvement can be attributed to the increasing dependencies of human lives on technology (Koul & Eydgahi, 2017; Kulviwat, Bruner, & Al-Shuridah, 2009). In a review based study, Korpelainen (2011) found that Diffusion of Innovation (DOI) (Rogers, 1962), Theory of Reasoned Action (TRA) (Fishbein & Ajzen, 1975), Theory of Planned Behavior (TPB) (Ajzen, 1991), Technology Acceptance Model (TAM) (Davis, 1986; Davis, Bagozzi, & Warshaw, 1989; Venkatesh & Davis, 1996), and Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh, Morris, Davis, & Davis, 2003) are the most widely cited theories in the domain of technology adoption. Williams, Rana, and Dwivedi, (2015) mentioned that the UTAUT had harmonized the literature related to technology adoption. The UTAUT is developed based on eight popular theoretical frameworks. Though some researchers have criticized UTAUT stating that it has dropped some potential causal relationships (Dwivedi, Rana, Jeyaraj, Clement, & Williams, 2017), a synthesis of UTAUT based research from 2003 to 2014 revealed that the model had been empirically tested in multiple settings (Venkatesh, Thong, & Xu, 2016).

Technology adoption is contextual (Jelinek, Ahearne, Mathieu, & Schillewaert, 2006; Kimberly & Evanisko, 1981) and research related to technology adoption in the context of the BOP people is limited. When this fact is coupled with the potentiality of smartphone penetration at the BOP, it becomes interesting to explore the factors influencing the adoption of smartphones in the BOP segment. Therefore, this study proposes an extended UTAUT based research framework and performs an empirical analysis of the framework for understanding smartphone adoption at the BOP.

This research will enhance the current state of knowledge in the domain of technology adoption by exploring and discussing the adoption of smartphones in the BOP segment in India. The main contributions of this study are twofold. First, we have investigated the effects of the determinants of smartphone adoption at the BOP as suggested in the original UTAUT (Venkatesh et al., 2003) to test the model for different technologies in the context of different types of user groups. Results from such studies help in enhancing the overall generalizability and understanding of the model. Second, we have incorporated a context-specific construct in our proposed research model in order to enrich the understanding of smartphone adoption at the BOP. This is important because the socio-economic conditions of the BOP people are vastly different from other segments of people (Prahlad, 2004). Moreover, the context-specific outcome of our empirical analysis in terms of the moderating effects of gender, age, and experience in smartphone adoption will enhance the current state of knowledge. Literature in the domain of technology adoption in the context of the BOP people are limited (Hasan, Lowe, & Petrovici, 2017) and therefore, the current study will enrich the literature of technology adoption by providing insights on smartphone adoption at the BOP.

Section snippets

Literature review

The literature review of this study can be separated into two parts. The first part will explore the literature associated with the characteristics of BOP, and the second part will review the literature related to smartphone adoption.

Research model

The research model of this study is based on UTAUT. According to UTAUT, “Performance Expectancy” (PE), “Effort Expectancy” (EE), and “Social Influence” (SI) have direct impacts on the “Behavioral Intention” (BI). UTAUT also posits that “Use Behavior” (UB) is determined by “Facilitating Conditions” and “Behavioral Intention”. UTAUT recognized moderating roles of four variables, namely age, gender, experience, and voluntariness of use. The original UTAUT framework is displayed in Fig. 1.

Since the

Data and sample

The current study is specific to the BOP segment. While selecting the respondents, the criterion for defining BOP is set at a monthly household income of Indian Rupees 13,152 or less. In order to ensure that a respondent belongs to BOP category, monthly household income is confirmed to be below INR 13,152 before filling the questionnaire. The respondents were given the questionnaire sheet to fill up in the presence of a trained data collector. Data points were collected both at home and

Empirical analysis

The empirical analysis of this study can be performed in two phases: Measurement Model and Structural Model. The fundamental assumptions of normality, collinearity, outlier analysis, and common method variance (CMV) are found to be satisfied in our dataset. For normality, we have checked the univariate skewness and univariate kurtosis of the observed variables. The maximum univariate skewness observed in the dataset is -0.462, and the maximum univariate kurtosis observed is 2.739. Hancock and

Discussion

The current study has proposed an extended UTAUT based model with constructs suitable for the BOP segment and verifies the model in the context of smartphone adoption at the BOP. Table 8 lists the hypotheses and outcomes of the study.

The empirical results show that “Perceived Monetary Value” is a significant predictor of smartphone adoption at the BOP. The results also confirm that all the primary hypotheses proposed under UTAUT stand true in the current context. The confirmation of these

Theoretical contribution

The extended UTAUT framework proposed in this study enhances the understanding of technology adoption at the BOP. The outcome of the primary hypotheses proposed in our research model is found to be consistent with the UAUT results. It reconfirms the generalizability of the UTAUT model. The context-specific insights received from the current study enrich the current state of knowledge in the domain of technology adoption.

Secondly, this study has included a construct related to the monetary

Practical implications

Empirical outcomes of our investigations have inferences for corporate managers as well as the public policymakers. The empirical result of this study shows that “Perceived Monetary Value” of a smartphone has a strong impact on “Behavioral Intention” to use a smartphone at the BOP. This result implies that the managers should carefully take the decision regarding the pricing of the smartphone targeted for the BOP segment as these people are sensitive to cost due to their limited disposable

Conclusion

The current study proposed an extended UTAUT model and checked its validity in the context of smartphone adoption at the BOP. Using 590 data points from Indian BOP segment, we have found that PE, EE, SI, and PMV of a smartphone usage have positive impacts on BI to use a smartphone. The study established that FC and BI positively impact UB.

Although the technology adoption rate is higher at the top and middle of the economic pyramid, the markets have gradually become saturated in those segments.

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