Digital data and management accounting: why we need to rethink research methods

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  • Published: 14 February 2020
  • Volume 31 , pages 9–23, ( 2020 )

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  • Alnoor Bhimani   ORCID: 1  

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Digitalisation is having profound effects on how enterprises function. Its impact on accounting research is growing as the rise of the internet, mobile technologies and digital economy tools generate depth, breadth and variety of data that far exceed what researchers have had access to in the past. But whilst social scientists interested in organisational issues are starting to question conventional methodological approaches to the study of contexts where digital data forms are drawn upon, little such concern has been voiced in the management accounting literature. This paper seeks to explore the continued applicability of conventional methodological thinking when carrying out investigations within digital data environments to inform management accounting studies. It considers why digitalisation impacts methodological precepts, identifies how descriptive and explanatory modes of questioning which management accountants have conventionally opted for need rethinking, discusses ways in which digital data characteristics alter what can be drawn from empirical studies, and points to the potential offered within digitalised settings for methodological advance. It concludes by highlighting the necessity, where digitalisation exists, to question modes of posing questions and to reconsider the applicability of methodological precepts deployed by management accounting researchers to date.

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1 Introduction

Fifty years ago, the American Accounting Association defined accounting as: “The process of identifying, measuring and communicating economic information to permit informed judgements and decisions by users of the information” (AAA 1966, p. 1). Accounting scholars have since come to regard economic information as just a subset of information relevant to decision making. In relation to management accounting systems, there is widespread documentation that their design and modes of operation are influenced by social, institutional, and other organisational factors and that in different contexts, they deal with much more than just economic information or quantified metrics. Today, this is further changing. Digitalisation is having profound effects on how enterprises function particularly in the production and analysis of big data as part of control systems. The impact on accounting research is palpable as the rise of the internet, mobile technologies and digital economy tools generate depth, breadth and variety of data that far exceed what researchers have had access to in the past.

Social science researchers interested in organisational control dimensions are undertaking an increasingly broad set of investigations given the widened data sources in existence today (Hage 2018 ; Johns 2017 ). It is probably “…without question, social media data have changed the research landscape for social scientists.” (Davis and Love 2019 : 639). All the while, questions over the applicability of conventional methodological presumptions in these emerging research literatures are also being asked (Cade 2018 ; Miller and Skinner 2015 ; Yang and Liu 2017 ). Scholars with an interest in “datafication”, that is the development of activities which can be traced digitally with extreme scale and accuracy and which is reshaping lives and experiences (Lycett 2013 ; Mayer-Schönberger and Cukier 2013 ), show more and more concern with how such investigations should be undertaken (Ausserhofer et al. 2017 ; Dourish and Gómez Cruz 2018 ; Van Es et al. 2018 ; Van Dijck 2014 ). Outside management-focused research, digitisation and datafication are seen to present important practical and theoretical research challenges and opportunities (Gattiglia 2017 ; O’Halloran et al. 2019 ; Qiu et al. 2018 ; Wesson and Cottier 2014 ). The need to be “aware of the limitations of any methodology” and to be “more analytical and less omnipotent” (Boullier 2018 : 11) in the application of epistemological and ontological perspectives drawn from analogue world studies within digital data environments is being expressed.

Just as in the social sciences generally, accounting research has seen many advances in tools of investigation including the use of both quantitative and qualitative computer-based methods to help assess field notes and complex numerical relationships. But as Davis ( 2017 : 2) notes “… innovations in qualitative and quantitative research are all, more or less, linear progressions. Big data is a move in a new direction. Big data isn’t just about answering particular questions better , but about asking questions we didn’t even know we had”. Within the management accounting research literature, what we might seek to conceptualise, how we might do so and whether to question modes of posing questions themselves in the face of the rise of new digital data forms has not been the subject of much discussion. The intention of this paper is to expand the debate on whether management accounting researchers as social scientists now need to question the propriety of continuing to apply conventional methodological precepts in investigating digital data contexts.

The paper first considers how digitalisation impacts management accounting research. It then discusses descriptive versus explanatory research and approaches to methodological positioning. The third section of the paper addresses questions to be asked about digital data. Fourth, the paper looks at how digitalisation enhances research possibilities in management accounting after which some conclusions are drawn.

2 Why digitalisation affects accounting research

New data contexts in which to examine research questions continually arise. Big data is a recent phenomenon that is deeply connected to what was an idea that has “…become the largest sociotechnical assemblage in human history in a little under 30 years” and which affects “… the lives, livelihoods and life chances of over half the world’s population already, and connecting many more every day” (Staab et al. 2019 : 74). It is now the case that we live in an era almost all human activity including organisational life can be recorded digitally (Alvarez 2016 ; Nagle 2017 ). The major mechanisms driving digitalisation today include digital technology innovations such as embedded internet of things devices, cloud computing, digitised supply chains and enterprise ecosystems and social media platforms among others (Blazquez and Domenech 2018 ; Hausberg et al. 2019 ). They give rise to data growth through management information systems processes and the proliferation of social networks, blogs, political discourse, company announcements, digital journalism, mobile messaging, home entertainment, online gaming, online financial services, online shopping, social advertising, and social commerce among others (Bhimani 2020 ; Chang et al. 2014 ). Digitalisation within firms has created very large quantities of data which are continuing to grow at an accelerating pace whilst also becoming more diverse in form making big data forever bigger, wider and more rapidly growing. Accounting academics have in this light recognised and highlighted the many accounting investigation possibilities where datafication prevails or is growing (Applebaum et al. 2017a ; Cockcroft and Russell 2018 ; Gepp et al. 2018 ; Mancini et al. 2017 ; Moll and Yigitbasioglu 2019 ; Raffoni et al. 2018 ; Salijeni et al. 2019 ; Vasarhelyi et al. 2015 ; Warren et al. 2015 ).

There is little doubt that across enterprises and organisational platforms the rise of big data and their impact on management accounting controls and information as well as on decision making is reshaping the managerial reliance placed on more traditional information (Agarwal and Nijhawan 2016 ; Applebaum et al. 2017b ; Bredmar 2017 ; Dagilienė and Klovienė 2019 ; Drew 2018 ). Big data and novel modes of analysis associated with the rise of digital technologies present organisational participants opportunities to utilise both structured and unstructured information for control purposes. Action based on such new information displays an important difference from the reliance on information systems output reflecting sequential and linear linkages that are part of pursued enterprise strategies and operations and attendant decision making that have guided the work of accountants in the past. There is now increased recognition that corporate strategy, organisational arrangements and information systems structures defy conventional ties traditionally seen to have connected them as greater appeal is made to big data based analyses and insights (Bhimani 2015 ; Krahel and Titera 2015 ). Moreover, costing architectures themselves have altered as links between data, information and knowledge have evolved (Al-Htaybat et al. 2017 ; Arnaboldi et al. 2017 ; Bhimani and Willcocks 2014 ; Căpușneanu et al. 2020 ; Richins et al. 2017 ; Rikhardsson and Yigitbasioglu 2018 ; Schneider et al. 2015 ; Troshani et al. 2019 ; Warren et al. 2015 ). Information outputs in organisations have transformed so much that few if any dimensions of business or management control processes today remain divorced from digital technology applications. Certainly, virtually all industrial sectors including manufacturing, transportation, health care, defence, energy, service and public sector activities are affected across economies (Vasarhelyi et al. 2015 ).

The rate at which organisations convert data insights into actions and the pliancy shown toward using heterogeneous data forms derived from diverse economic and social sources as well as the flexibility toward intermingling economic, operational, structured, unstructured, qualitative and numbers-based information has reached unparalleled heights. Enterprises today exercise data reach and plurality of information usages to inform enterprise action and guide operational processes of an order of magnitude never witnessed before in the history of organisational information systems usage. As such, accounting activities reliant only on pre-designed information inputs relating primarily to economic transactions with some coupling with non-financial information pools represents a fraction of control information deployment in digitalised enterprises. All dimensions of managerial action that can be influenced by datafication possibilities can be expected to open up novel control possibilities also.

The argument has been made that the vastness of new data forms does not elevate the rationality of decision making and indeed, that access to more digital data within enterprises “will make people take wrong decisions much more quickly than before” (Quattrone 2016 : 120). What is clear is that scholarly studies in accounting will increasingly explore novel digital data forms, types and usages. As they do, accounting researchers will need also to reflect on the adequacy of the methodological approaches they adopt since their focus on widened data sources perforce embeds epistemological conditions that can alter the object of their investigations and place at risk their ability to develop tenable arguments. The next section identifies two forms of traditional accounting research concerns which have laid the premise for specific methodological presumptions which need to be reconsidered in investigating digitalised contexts.

3 Asking ‘what’ and ‘why’ in management accounting research

One view of information is that its use helps deal with the management of uncertainty (Jauch and Kraft 1986 ). Many management accounting activities in enterprises seek to produce information that lends greater clarity to managerial decision making and that enhances the perception of certainty of actions taken. In organisational environments where complexities grow, the general reaction of management accounting formality has been to re-structure information to enable its continued potential for uncertainty reduction and to aid management decision making. In instances where information structures have been challenged because of a perceived need to enhance organisational decision making clarity, the reaction has been to advance accounting techniques that adopt new formatting, novel structures or altered technical rationales. Managerial action and organisational transformations have reflected environmental changes such as for instance, growing production flexibility, product range increases and deeper and more rapid competitor shifts among others. Increased complexities between business objectives, operational processes and decision making has been responded to by novel management accounting approaches (such as activity based costing, target costing, balanced scorecards, standard costing systems etc.) which have become formalised management control measures in many enterprises. Management accounting changes have thus tended to encompass the adoption of standardised enterprise controls that reflect new information production and exchange needs. As organisational interconnections and risks have grown, new applications have been implemented to aid the management of uncertainty resulting in greater systemic homogeneity of management accounting approaches.

For management accounting scholars, such changes in accounting controls have presented many research opportunities. Some have engaged in descriptive investigations of management accounting techniques take-up by enterprises. Such investigations report on standard techniques usage identifying similarities and differences in adoption rates across firms, industrial sectors and geographies without necessarily seeking to explicate the basis for the reported differences. The descriptive management accounting practices literature has reported on numerous standard techniques in use in companies such as variable and full costing, choice of cost allocation bases, budgetary control practices, variance analysis and standard costing usage, pricing techniques, capital budgeting approaches, transfer pricing methods, activity-based costing applications, as well as balanced scorecards, life-cycle costing, and strategic accounting tools among others (Bhimani et al. 2019 ).

The concern with how techniques show differences and similarities across firms has been complemented by other scholarly studies that investigate why accounting outcomes are what they are. Explanatory research in management accounting attempts to identify causal factors and to offer rationales for the underlying reported differences. Most of these studies tend to posit deductive explanations based on other empirical studies previously undertaken in comparable contexts and/or drawing upon specific conceptual reference frames to demarcate propositions. To take an example, the contingency theory of management accounting has been regarded by some management accounting scholars as offering a theoretical frame for explaining the basis for similarities and difference in modes of organisational control implementations (Chapman 1997 ; Chenhall 2007 ; Gerdin and Greve 2004 ; Otley 2016 ). Some scholars posit an emic rather than an etic approach to contingency based management accounting research (Granlund and Lukka 2017 ) and others critique the determinism grounded in the contingency perspective (Fried 2017 ). Still, the generalist argument advanced within the contingency perspective has been built on the premise that control systems deployment in enterprises is linked to the existence of supra-national forces of change whereby firms become more alike as economies converge over time (Donaldson 1995 ; Hickson et al. 1974 ). So differences become suppressed as homogenising factors inform the architecture of controls within firms (Mueller 1994 ). Scholars who adopt a contingency argument to explain similarities and difference have identified broad environmental factors such as for instance the manner in which managerial hierarchies are structured vis-as-vis the stage within a notional trajectory of industrialisation which an economy finds itself in. Under this perspective, economic transformation drives market, technical, and organisational dependencies which compel firms to arrange their internal structures by reference to a set of functional control possibilities (Otley 2016 ).

Another stance adopted by some scholars is the “political economy” perspective which focuses on contradictions within capitalism that mobilise broadly similar trends in the management and structuring of the labour process. Profit seeking organisations are viewed to exhibit similarities in managerial controls to oversee the conduct of work and the standardisation of tasks (Armstrong 1987 ; Cooper and Hopper 1990 ; Roslender 1996 ; Thompson and Smith 2010 ). The notion that imperatives (either contingency or labour-process based) prevail across social, economic, or political systems and that mould organisational controls within a trajectory of progression enables explanations as to specific functioning modes implemented by organisations and the formal controls they ultimately operationalise. The argument advanced within this conceptual perspective rests on the contention that structural changes over time follow a specific path of evolution and that organisations in the settings under study manifest corresponding likeness.

The premise within both contingency and political economy perspectives is that organisational contexts follow a trajectory that overarches the particularity of enterprise characteristics. As such, advances accord organisations likeness of control approaches that echo the homogenising effects of industrial change. Converging influences manifest whereby technological, market, strategic, labour and other contextual variables exhibit replicating interdependencies in relation to organisational structuring which underpin control changes. Such scholarly explanations as to organisational control operationalisations rest on argumentation that presumes the stability of relationships between environmental characteristics and organisational features and processes including management accounting approaches.

Management accounting research resting on notions of converging influences tied to presumptions of industrial evolution are, within digitalised settings, in need of qualitative re-assessment. The stability of relationships cannot be assumed of emerging business models in the fast transforming digital economy (Wadan et al. 2019 ). The time is also now to questions the applicability of quantitative approaches that have been deployed in studying analogue organisational settings whose information systems are linearly arranged and to ponder their continued appropriateness given the altered process structures of digitalised enterprise contexts. The issue goes beyond the paradigmatic legitimacy of using quantitative research norms drawn from the pure sciences to qualitative investigations (Aguinis et al. 2017 ; Denzin 2010 ; Pratt et al. 2019 ).

As scholars pose research questions, opting for either descriptive or explanatory routes in relation to the study of digitalised enterprise controls, they need to also ponder whether the data from such can be subsumed within traditional methodological conceptions of data inquiry. It may be that the transition from analogue to digital has ushered in different parameters of evolutionary enterprise control structuring which need to be explored. By the same token, it is difficult to contest that digital technologies associated with the production of big data can lead to inferences that “covertly or overtly, consciously or inadvertently” (Robertson and Travaglia 2018 : 2) support specific ideologies. In other words, both quantitative and qualitative methodologies deployed within established management accounting research efforts embed epistemological, ontological and ideological preconceptions that need elaboration. Possibly, “… the change from a largely analogue small data environment to a foundationally digital one has not undermined the pervasive ideologies that the small data paradigm produced and institutionalised” (Ibid.). It becomes therefore essential for management accounting researchers to ponder what conceptions of research become imported into new realms of analyses that rest on vastly different data forms and sources and whether what is interpreted about the new data is aided or obfuscated by past norms of research propriety. The paper turns now to discussing data specific implications of management accounting research focussing on digital contexts.

4 Questions about data that can change the questions we pose

Accounting scholars will continue to explore accounting structures and what underpins their functioning. The underlying forces that tie contextual factors to accounting however are changing and a need exists to reflect on how appropriate it is to adopt conventional research precepts in exploring accounting issues within digitalising environments. A number of issues associated with the nature of data resulting from digitalisation suggest that such reflection has become essential. First, a marked change is in evidence whereby the presumed connections between action and control systems input and their consequences in conventional accounting usage settings have altered. The evolution of digital technologies has upended the sequential linearity which has traditionally directed organisational activities. The pursuit of specific defined organisational strategies can, in some instances, give rise to particular management controls but that logic cannot be assumed to reside in digitalised enterprises. The notion that sequential and traceable paths of effects are present where in fact new inter-dependencies associated with digitalised platform based organisational control models and altered data creation and exchanges are in play no longer hold (Willcocks et al. 2014 ). Contingency reasoning resting on the idea that enterprise strategies sponsor technological responses which yield specific accounting control outcomes has to be questioned since the sequential agency baked into conventional control mechanisms is seemingly absent in digitalised settings (Bhimani and Willcocks 2014 ). Information relevance and the linear sequencing of control information and action drawn upon for information analysis by decision makers is not an essential part of digitalised enterprise activity. Consequently, it is essential to acknowledge that ways in which accounting controls in digitalised organisations differ from traditional settings as data forms and flows have altered. This needs to be reflected in revising the research questions we ask.

Second, datafication has altered the premise on which management accounting justifies its raison d’être . Whilst the objective to provide financial and non-financial decision-making information to managers may seem laudable as management accounting’s primary pursuit, this prescriptive view confines the field to the application of solutions and a focus on data that are no longer hold primacy in many digitalised enterprises. Aside from formal financial data and operational records of processes or economic transactions, digitalised enterprises produce “exhaust data” or “trace data” which are part of the digital records of activities and events that engage information technologies such as data from clickstreams, sensor data, and social media updates. Such data bypasses capture by traditional accounting information systems since they lack any direct link to verifiable economic impact. However, digitalised organisational platforms produce at least some elements of trace as part of log files, documents or communication trails which culminate in data perceived to be of relevance to controls and viewed as a desirable source of business intelligence. Appeal to such additional forms of data, structured and unstructured, have implications for researchers. Different investigatory questions may be posed and studies may benefit from redefinition of scale and scope in the light of more diverse data types. Digitised data may for instance be seen to lag or lead the direction captured by formal data and operational information. They may signify reinforcement or upending of articulated organisational pursuits. Such data, given their abundance and speed of production, may lead researchers to redefine the depth and time focus of their investigations.

Third, digitalised enterprises may exhibit pathways to organisational changes that do not accord with established management theories. This then could confound inference-focused methodologies adopted by accounting scholars. It may be that research methods could be widened drawing from the data sciences (George et al. 2016 ). To take an example, suppose that enterprises reveal that engagement in big data analysis leads to the identification of patterns giving rise to new organisational strategies. This then opens up room for questioning the premise upon which strategic management theorising rests in relation to strategy formulation and formation (Furrer and Goussevskaia 2008 ; Langfield-Smith 1997 , 2006 ; Sminia 2009 ) and the conventional predictions that can be derived from the prior literature (Grattan 2016 ). If it is apparent that new enterprise visibilities based on research data collected can lead to altered strategies that overarch any reference to traditional conceptions of strategic engagement, then one must interrogate whether prior studies supporting linkages between strategy and accounting and the methods adopted therein can reasonably guide research endeavours that rely on data which defy traditionally perceived patterns of flow.

Fourth, research in digitalised organisations, can reveal useful data sources that are ‘found’ rather than produced by design. These can aid enterprise decision making but in contrast to formalised systems derived information that have purposefully ‘generated’ data with specific intents, their provenance is circumstantial. Moreover, trace data are different from many other common forms of social science data in that they are usually “event-based” records of activities and transactions. Additionally, trace data are ordinarily longitudinal and time-stamped sequences of activities. Further still, they may not be cross-sectional and thereby serve a number of alternative and possibly novel research purposes. Recognition that digital data can be a by-product of activities instead of data generated for the purpose of either organisational control or indeed for the research enterprise is important to acknowledge. Importantly, the specific characteristics and properties of digitalisation derived data makes for potentially extremely significant advances in academic research. This is further discussed in the next section.

5 Can digitalisation widen the research potential?

Scholarly claims must align with norms of legitimacy in accounting research. Deviating from these can derail investigations if established research robustness pre-conditions are sidestepped (Creswell 2003 ; Frade 2016 ; McFarland and McFarland 2015 ). But there must also be recognition that approaches to data, method and theorising can be altered and expanded as researchers engage with novel bases of empiricism. Investigations using data from digitalised organisations, whether financial, structured and formally produced or non-financial, unstructured and trace-derived, have the potential to make insightful claims about the technical, organisational and social characteristics of accounting. Digitalisation therefore offers immense opportunities in this respect but requires safeguards to maintain traditionally desirable parameters of research integrity. This has to be balanced with the potential of conceptualisations from research that could not be had by too closely remaining wedded to past ideologies of research integrity. To take an example, within explanatory management accounting research, the tendency has been to demarcate between deductive versus inductive research. Digital data forms enable emancipatory departures from this research divide than before.

The availability of trace data can enable inductively generated novel theorising to emerge. Still, as with the edicts of conventional research legitimacy, one cannot overreach in yielding conclusions from empirics when the data source does not permit. It is important therefore to be mindful that trace data tend not to be generalisable outside of the platforms from which the data originate. This is particularly so when trace data links into social media bases. Participation on digitalised platforms that generate such data is not usually universally representative of the wider population that interacts with an organisation or industrial sector within the object of study. These data sets may also be demographically biased. Access to data or to platforms that create such data may further be infra-structurally constrained. Organisationally linked media data are partial, demographically skewed, and not always consistently available. Consequently, empirical generalisability may not be attainable and theoretical generalisability must not be inappropriately posited. As Davis and Love ( 2019 : 637) warn, researchers must bear in mind that: “Through a mask of objectivity, claims about ‘social life’ derived from social media data present the partial and the skewed as general and universal”.

Trace data assessment can buttress conventional hypothetic-deductive methods but also can lead scholars to build and elaborate theory by subjecting the data to extensive analysis. Importantly, the availability of different data forms that have not been available to researchers before offer the possibility to inductively engage such data within a grounded theoretical frame (Charmaz 2014 ; Glaser and Strauss 1967 ) rather than to pursue hypotheses propositions and testing aligned with deductive methodological convention. Grounded theory that seeks to develop theoretical concepts and relationships can become viable where digitalised data forms, because of their scale and variety and the data characteristics noted above, offer prospects for delving beyond deduction.

Big data analytics using focused computational methods that prioritise speculative data mining to highlight pattern recognition and unexpected correlations can inform the accounting research domain (Appelbaum et al. 2017a , b ; Geppa et al. 2018 ; Schneider et al. 2015 ). Pitfalls nevertheless exist in that simple mining for insights overlooks questions that could be more theoretically informed and to some, the value of such investigations “remains very much open to question” (Goldthorpe 2016 :81). The importance of and the possibilities open to qualitative researchers to “… conduct ‘big qual’ analysis while retaining the distinctive order of knowledge about social processes” remains (Davidson et al. 2019 : 264). There certainly can be continuity in data enabled by the combination of qualitative and quantitative methods in the digital world (Venturini et al. 2017 ). Indeed, Halford and Savage ( 2017 : 1133) suggest that researchers might take a ‘symphonic’ approach to big data analysis where “recurring descriptive motifs woven together within a complex temporal narrative” are made visible. They advocate a perspective that combines rich theoretical awareness with data that can address wide questions rather than simply mobilising the ad hoc mining of large data sets in search of inductive patterns where “hermeneutic and critical analysis” are displaced. A precaution is for the data set assessed not to be short period collections of say purchasing patterns and production activities over limited time and context spans but wider ranges of points over extended time frames. The intent should not be to have the data infer associations based purely on detected correlations but to use concepts and theorising that connect to recurring motifs such that there emerges a broader narrative. Certainly, studies must not abandon traditionally important considerations of social science research including data representativeness and sampling biases and it is important that conclusions that relate to a whole population are not based on results gathered from partial analyses reliant on narrow data sets (Hargittai 2018 ; Lazer et al. 2009 , 2014 ). The preferred approach should then be to intertwine sound theoretical understanding with wide ranging data that reveal recurring motifs.

Methodologically, some steps that are long established in social science research are important to adhere to. Halford et al. ( 2018 ) advance the need for high transparency as to the data being used. In other words, extreme diligence is required in reporting the way in which data are harvested. This could mean keeping tabs and records of principal metrics that relate to the data set or streams. The possibility of transparency must therefore remain. It is likewise important to understand the limits of the data in terms of what it could reveal and what not. Moreover, the construction of data is important to explain as researchers often organise the data to be analysed to enable a particular questioning slant to be operationalised such as for instance, deliberately biasing the population set to evince more information about an under-represented management control characteristic. This avoids making inferences that supersede the specificity of the data set. The questions to be asked should, in other words, guide the approach and the claims should align with the data selected for analysis.

Whilst methodological fundamentals typical of empirical analyses using data sets for investigation of traditional or big data contexts may have parallels, the availability of digitalised data affords more flexibility to deviate from common research points of departure. In effect, rather than make distinct the starting point of a research endeavour in relation to engaging in deductive or inductive reasoning, what may be sought is abductive reasoning from the outset where tools and data are engaged in within a critical process of interrogation which may change during the investigatory stage. Certainly, “…emic-level empirical analysis at the core of interpretive research is connected to etic-level analysis and knowledge” (Lukka ( 2014 : 561), but in relation to digitalised enterprise contexts, primacy can be given to the “unfolding interplay between data, method and theory and with regard to their co-constitution” (Halford and Savage 2017 : 1143).

Some scholars have argued that digital data has done “nothing less than to revolutionise the social sciences” and is “challenging established paradigms” (Berente et al. 2018 :2). Accounting research is not exempt. The case for re-thinking how legitimate it is to apply conventional methodological precepts in investigating digital data contexts to inform management accounting studies cannot be made too strongly. The paper has discussed digitalisation as having led to massive data growth both from non-formal structures as well as from management information systems producing and processing economic and new forms of data that are structured and unstructured. The impact of digitalisation on management accounting research is growing as we gain access to greater depth, breadth and variety of data. This is creating an investigatory landscape offering exponentially growing qualitative and quantitative research domains. The focus on digitalised data raises issues of method for accounting research given that organisational information platforms now encompass the analysis of data not conventionally part of management control research. Digital data characteristics embed features that can challenge established paradigms about data and lead to altered ontological notions of the informational nature of data. The growth of analysable data, structured and unstructured, as well as formally intended and circumstantial, alters the premise upon which researchers can design their investigative work and the methodological precepts they adopt or indeed, devise.

It might be said that digitalisation within enterprises offers researchers an epochal opportunity to investigate what has not been possible in the history of management accounting investigations. This is because digital data are “more evenly distributed across the span of collective existence of which they therefore offer a more continuous appraisal” (Rogers 2013 : 4). Management scholars have pointed to the handling of big data and how analytical tools provided by data science can be adapted and altered to not only seek better answers to existing questions but also for posing new questions (George et al. 2016 ; Kuo and Kusiak 2019 ; Mikalef et al. 2018 ; Spanaki et al. 2018 ; Tonidandel et al. 2018 ). What may be derived from research using larger volumes of data that emerges faster than ever before and which is more varied in structure whilst also offering specific characteristics such as time-stamping and chronology, goes beyond what has been empirically available to us. Features that characterise digital data alter the potential of investigations in relation to the limits and possibilities of digital empiricism. Along with an unprecedented array of new data, digitalisation has brought with it novel options for how to and what to research, as well as a need to re-assess our conventional conceptions of methods legitimacy and ultimately, what we regard as having scholarly rigour.

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Users' attitude and intention to use mobile financial services in Bangladesh: an empirical study

South Asian Journal of Marketing

ISSN : 2719-2377

Article publication date: 3 August 2021

Issue publication date: 23 September 2021

While the usage of mobile financial services (MFSs) is increasing rapidly in developing countries, research on users' attitudes and behavioral intention to adopt MFS is limited. Thus, this study aims to investigate customers' attitudes and intentions to adopt MFS from a Bangladeshi perspective.


A mixed research design was employed to conduct this study. Data of 196 respondents were analyzed using partial least squares (PLS) path modeling. For the quantitative part, data collection was conducted using non-probability sampling through a structured survey questionnaire. A focus group discussion with ten MFS users from divergent backgrounds was conducted to validate the quantitative findings.

This paper integrated both the technology acceptance model (TAM) and innovation resistance theory (IRT) to validate the results. The authors found that perceived usefulness (PU), perceived ease of use (PEOU) and perceived trust (PT) positively contribute to customers' attitudes toward MFS adoption. Besides, barriers to acceptance had unfavorable effects on users' attitudes and usage intentions. Furthermore, a focus group discussion revealed valuable insights on the constructs used in this study.

Practical implications

The study results have implications for both MFS providers and researchers. The outputs and recommendations presented in this paper will encourage the MFS practitioners to stimulate users' attitudes and behavioral intentions by ensuring useful, easy to use, credible and risk-free mobile payment platforms.


This is one of the very few studies in Bangladesh that have taken a contemporary and emerging research topic, providing theoretical, methodological and practical contributions regarding the determinants and consequences of attitude toward using MFSs.

  • Intention to use
  • Mobile financial service (MFS)
  • Technology acceptance model (TAM)
  • Innovation resistance theory (IRT)

Himel, M.T.A. , Ashraf, S. , Bappy, T.A. , Abir, M.T. , Morshed, M.K. and Hossain, M.N. (2021), "Users' attitude and intention to use mobile financial services in Bangladesh: an empirical study", South Asian Journal of Marketing , Vol. 2 No. 1, pp. 72-96.

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Copyright © 2021, Md. Tanvir Alam Himel, Shahrin Ashraf, Tauhid Ahmed Bappy, Md Tanaz Abir, Md Khaled Morshed and Md. Nazmul Hossain

Published in South Asian Journal of Marketing . 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 may be seen at


Over the years, the advancement of the Internet and mobile phones as a medium of transactions has been a global trend, resulting in a rising acceptance of mobile commerce (m-commerce) throughout the world ( Rosa and Malter, 2003 ; Kumar et al. , 2019 ). Mobile financial service (MFS), one of the prominent aspects of m-commerce, provides financial assistance to the users, enabling them to transfer and collect funds, make deposits, or pay bills using mobile devices or software ( Al Saedi et al. , 2020 ). This system, thus, has brought about a convenient, trustworthy, easy to use and secure transaction method for clients and agents alike ( Chen, 2008 ).

Hence, studies on the predictors of MFS/m-banking user attitude and behavior have recently gained momentum in the academic and business community because such research can assist MFS marketers to devise and implement better strategic decisions required for customer acquisition and retention ( Malik et al. , 2013 ; Saleh and Mashhour, 2014 ; Slade et al. , 2015 ; Abdinoor and Mbamba, 2017 ; Cui et al. , 2020 ; Manchanda and Deb, 2020 ). Using technology acceptance model (TAM) ( Davis et al. , 1989 ) and other related behavioral theories, several past studies identified numerous crucial predictors, such as perceived usefulness (PU)/relative advantage/performance expectancy, perceived ease of use (PEOU)/complexity/effort expectancy, subjective norms, perceived functional and emotional benefits, consumer innovativeness, demographics, perceived risk, facilitating conditions and many more that can influence users' attitude and intention to use m-commerce/m-payment/MFS ( Yang, 2005 ; Hsu et al. , 2011 ; Yen and Wu, 2016 ; Chi, 2018 ; Gupta and Manrai, 2019 ; Al-Saedi et al. , 2020 ; Jung et al. , 2020 ; Manrai and Gupta, 2020 ).

Nevertheless, most of these studies have been conducted from digitally advanced contexts, such as Singapore, India, China, Taiwan, or USA, where digital ecosystem is conducive to the adoption of MFS platforms ( Sampaio et al. , 2017 ; Koh et al. , 2018 ; World Bank, 2019 ). In contrast, customers' digital behavior in a least developed country like Bangladesh is not as penetrated as in other neighboring, western or Southeast Asian contexts ( Babar, 2017 ). Statistics suggest that in Bangladesh approximately 102.80 million customers are registered with several MFS service providers, such as bKash, Nagad, Rocket, Tcash, Ucash, to name a few ( Bangladesh Bank, 2021 ). However, among them, only 34.64 million are active clients ( Bangladesh Bank, 2021 ). Presently, only 1% of the daily payment is happing through digital methods/MFS, whereas the rate is around 60% in the developed countries ( Digital Finance Forum BD, 2021) . In addition, the country lags behind its major South Asian counterparts in terms of smartphone use ( The Daily Star, 2021 ). Thus, MFS industry insiders in the country claimed that although registered MFS users in Bangladesh is increasing rapidly, the rate of inactive users is still high because of lack of user trust, network issues, users' fear of fraudulence, lack of interoperability, lack of digital literacy, to name a few ( Yesmin et al. , 2019 ; Rashid, 2020 ). Therefore, the marketers are still somewhat unclear about their customers' attitude and usage intention ( Rahman et al. , 2019 ). Although, scholars, such as Khan et al. (2021) , recently attempted to explain M-banking App usage behavior in Bangladesh, it only focused on the trustworthiness ignoring several other relevant determinants of attitude and behavioral intent. Hence, there is a recognized need for further context-specific empirical prediction of users' attitude and MFS usage intention as the existing studies falls short of providing adequate direction to the practitioners regarding MFS consumer behavior.

To this end, the authors of this study planned to integrate an extended version of original TAM with innovative resistance theory ( Ram and Sheth, 1989 ). There are several rationales for using these models in this study. Firstly, although TAM is one of the most parsimonious and dominant theories in understanding the technology usage behavior ( Venkatesh et al. , 2003 ), but the original model ignores how trust and barriers to acceptance affect the target variables of this study. Therefore, TAM was extended in this paper by employing the construct “perceived trust” (PT) because a recent paper argued that when Bangladeshi M-banking app users' show trust on the ability, benevolence and integrity of this system, their usage behavior is significantly and positively affected ( Khan et al. , 2021 ). Secondly, to the best of researchers' knowledge, there is a dearth of study which investigated the relationship between acceptance barriers and their subsequent role on MFS users' attitude and behavioral intention, particularly from a digitally backward country like Bangladesh. Consequently, the authors believe that an integration of TAM with innovation resistance theory (IRT) can provide comprehensive evidence on the antecedents and consequence of attitude toward using MFS in Bangladesh.

Furthermore, this study addressed a methodological gap in the extant studies concerning MFS consumer behavior. It has been noticed that most previous studies on MFS customer attitude and behavior are either purely qualitative or purely quantitative in nature but research employing mixed methods is scarce. Thus, this study followed a mixed research method (both quantitative and qualitative) because it enables the researchers to harmonize the conflicting findings of the past studies on MFS customers' attitudinal and behavioral patterns.

Considering these gaps, the purpose of this paper is to investigate four research questions: (1) what are the antecedents of attitude toward using MFS? (2) What are the roles of user attitude and acceptance barriers in influencing MFS acceptance intention? (3) Do the predictors used in our research model affect MFS acceptance intention through attitude? (4) Are the quantitative results of the six constructs used in this study consistent with the insights extracted from focus group discussion?

The paper has been structured as follows: first, the authors have conducted a literature review to lay down this study's theoretical basis and to formulate the hypotheses. In the subsequent section, the researchers have discussed the research methodology in detail. Afterward, findings and discussion have been outlined, followed by implications of this study. Finally, the study ended with a description of this study's limitations followed by future directions.

Literature review

Theoretical foundation.

Any hypothesized relationship in an empirical study should receive supports from prior theories or well-established models ( Colquitt and Zapata-Phelan, 2007 ). The present study predicts Bangladeshi MFS users' attitudes and behavioral intentions through the TAM ( Davis et al. , 1989 ). Inspired by the theory of planned behavior ( Ajzen, 1991 ) and theory of reasoned action ( Fishbein and Ajzen, 1975 ), TAM suggests that PU and PEOU of any technology or information system determine users' attitude, which further amplifies their behavioral intention ( Davis et al. , 1989 ).

In this context of the present study, PU signifies how much users find it useful to adopt MFSs, while PEOU connotes how much they consider using MFS to be effortless. Furthermore, attitude indicates users' positive or negative beliefs or evaluations toward adopting MFS, while intention implies the probability that a user will accept MFSs.

However, the original TAM received numerous criticisms from several scholars in the past ( Ajibade 2018 ). For instance, Legris et al. (2003) argued that TAM 1 and TAM 2 models, together, could not adequately explain the customers' attitude and technology usage intention. Therefore, scholars have always supported incorporating context-specific new determinants in the TAM ( Popy and Bappy, 2020 ).

Since the launch of MFS in Bangladesh, consumers are experiencing numerous barriers that slow down their intention to adopt this payment system ( Vota, 2017 ). There have been several incidents where customers, agents and distributors had experienced thefts and security problems ( Yesmin et al. , 2019 ), which have significantly affected their trust in the system.

Therefore, this study has employed the variables previously used in IRT to comprehend the resistance-based actions of the MFS users ( Ram and Sheth, 1989 ). According to this theory, functional barriers (resulting from the features of the MFS) and psychological barriers (arising from the prevailing beliefs of users regarding mobile payments) can unfavorably influence customers' intention to adopt an innovation ( Kaur et al. , 2020 ). Behavioral incongruity resulting from usage, perceived risks and perceived value of using a new system constitute functional barriers, whereas traditional beliefs and negative images of the innovation represent the psychological barriers.

Since prior studies have used IRT to examine the role of barriers in predicting intention to adopt m-payment ( Jung and Jang, 2018 ; Kaur et al. , 2020 ), the present study has integrated this theory to supplement the traditional TAM. Furthermore, backed by prior studies, this study also conceptualizes that if the MFS users have a greater level of trust toward this system, they will present a higher-level of favorable attitude toward using it, which will further enhance their adoption intention ( Castelfranchi and Falcone, 2010 ; Singh and Sinha 2020 ; Bappy et al. , 2020 ; Khan et al. , 2021 ).

Hypothesis development

Perceived usefulness and attitude toward using mfs.

Perceived usefulness of MFS is positively related to attitude toward accepting MFS.

Perceived ease of use and attitude toward using MFS

Perceived ease of using MFS is positively related to attitude toward accepting MFS.

Perceived trust and attitude toward using MFS

Trust in MFS will have a significant positive effect on attitude toward accepting MFS.

Barriers to acceptance and its consequences

Usage barriers: Difficulty in using and learning MFS ( Laukkanen et al. , 2007 )

Value barriers: Higher costs than benefits ( Kuisma et al. , 2007 )

Risk barriers: Typing bill information incorrectly, paying extra amounts, paying to incorrect receivers ( Kaur et al. , 2020 )

Tradition barriers: Having technology anxiety resulting in apathy to alter the extant behavior ( Meuter et al. , 2003 ), intricacy in communicating with the MFS providers, problems with having the troubles resolved ( Kaur et al. , 2020 )

Image barriers: Negative image or perception that the use of MFS technology is complicated ( Laukkanen, 2016 ).

Barriers of MFS are negatively related to attitude toward using MFS.

Barriers of MFS are negatively related to intention to use MFS.

Attitude toward MFS and intention to adopt

Attitude toward using MFS is positively related to intention to use MFS.

The mediating role of attitude

TAM posits that attitude is the path through which PU and ease of use affect users' behavioral intention ( Davis et al. , 1989 ). Prior studies further showed that consumers' PT positively affects adoption intention through their attitude toward adoption ( Popy and Bappy, 2020 ). To the best of the authors' knowledge, the mediating role of attitude in the relationship between barriers of acceptance and behavioral intention has not been studied adequately in the prior studies.

(a) The positive relationship between perceived usefulness and intention to adopt MFS.

(b) The positive relationship between perceived ease of use and intention to adopt MFS.

(c) The positive relationship between perceived trust and intention to adopt MFS.

(d) The negative relationship between barriers to acceptance and intention to adopt MFS.

Considering the hypotheses of this study, the researchers have proposed the research model demonstrated in Figure 1 .


Research design.

The study followed a mixed method, which incorporated both qualitative and quantitative approaches of research. In this cross-sectional study, the authors utilized a survey questionnaire to obtain quantitative data from the respondents. Besides, a focus group discussion with ten respondents from different age, background and profession provided the researchers with qualitative insights on the six constructs used in this study.


Measurement scales were developed based on the literature of previous studies. The items representing PU and PEOU were adapted from Davis et al. (1989) and Chawla and Joshi (2019) . The three indicators measuring PT were drawn from Ganguly et al. (2009) and Bappy and Chowdhury (2020) . Besides, “barriers to acceptance” was estimated based on six items, among which one represents “value barrier”, two represent “risk barrier”, one item represents “usage barrier”, one represents “tradition barrier" and one represents “image barrier”. This research retained only the best indicators from the several barrier-related constructs used in Kaur et al. 's (2020) study to keep the scale short and straightforward. This practice of upholding the best indicators has been prescribed by Hayduk and Littvay (2012) in their study, claiming that the use of few best items enables researchers to develop conceptually advanced models parsimoniously. Hence, instead of using the total 16 items of Kaur et al. 's (2020) questionnaire, the authors decided to keep six indicators based on the opinion of thirteen mid-level executives from several MFS companies in Bangladesh. These six items represent five types of barriers used in IRT. Furthermore, three indicators evaluating users' attitude toward using MFS was extracted from Hu et al. (1999) . Finally, the four items of the 'intention to use' construct were adapted from Chen and Barnes (2007) .

Pre-testing and pilot survey

A structured questionnaire was used to collect data from respondents. Initially, the questionnaire was pre-tested with five respondents (the MFS users and two executives) to confirm that the questions' wording and sequence are correct, clear and understandable. Based on their feedback, the wordings of the questions were rephrased. Furthermore, the researchers conducted a pilot study with 20 participants (fifteen MFS users and five professionals serving in different MFS companies) to ascertain the research instrument's adequacy, reliability and feasibility ( Teijlingen and Vanora, 2002 ). As per Hill (1998) , this sample size for the pilot study is adequate. Considering the data obtained in the pilot survey, the authors calculated the scale items' internal consistency. The “Cronbach's alpha” scores for all the constructs turned out to be above 0.7 and were satisfactory.

Sampling and data collection

The respondents were scattered all around Bangladesh, but most of them were from Dhaka and Chattogram. The target population size is estimated to be 102.80 million MFS users ( Bangladesh Bank, 2021 ). However, currently, the authors found no sampling frame listing the target group of respondents. A recent study suggests that it is difficult for social science researchers to use random sampling without a sampling frame ( Krause, 2019 ). Hence, a non-probability sampling technique called, snowball sampling, was used for data collection in the main study. This technique was preferred as the data was collected during COVID-19 lockdown when it was hard to collect data using a field survey. Thus, the sampling technique used in this study can be justified.

Subsequently, an online survey questionnaire was used to obtain the opinion of the respondents. First, the online questionnaire was circulated to several people known to the researchers as MFS users. The selected people then shared the questionnaire with their known ones who are currently using MFSs. The questionnaire's link was first circulated on 8 August 2020 and the responses were received till 20 August 2020.

The sample size was calculated with G*power 3.1 ( Faul et al. , 2007 ) software using f 2  = 0.15(moderate), α  = 0.05 and number of predictors = 4 and the power = 80% ( Gefen et al. , 2011 ). The G*power software recommended minimum sample size of 73 to test the model. The researchers obtained 220 responses from the respondents through online referrals, among which 24 responses were omitted during data screening due to straight liners, outliers and missing values. Finally, the sample size was fixed to be 196 to test the model. This sample size is sufficient to conduct partial least squares-structural equation modeling (PLS-SEM) analysis.

Besides, a complementary qualitative study using in-depth interview technique was conducted to obtain additional insights regarding constructs of research model depicted in Figure 1 . As qualitative research works well even with a smaller sample size ( Malhotra and Dash, 2016 ), the authors decided to select ten respondents using the judgmental sampling technique.

Data analysis

The measurement and structural model were evaluated with PLS-SEM technique using SmartPLS 3.2.6 software. PLS-SEM is a handy statistical tool for predictive reasons, works well with non-normal data and smaller sample size. This study's essential purpose was to develop an integrated theory to predict customers' attitudes and behavioral intentions. Therefore, PLS-SEM was preferred over covariance-based SEM. The respondents' demographic profile was analyzed by reporting counts and percentage using SPSS version 23 due to its ease of use.

Results and analysis

Demographic profile.

After filtering 220 responses of the respondents, the study identified 196 reasonable opinions relevant to this study. The demographic characteristics (see Table 1 ) of respondents showed that most of the respondents were female and had an age category between 23 and 27 and are undergraduates. Furthermore, bKash appeared to be the most preferred MFS brand in Bangladesh.

Assessment of multivariate normality

This study ascertained whether the data is normally distributed or not because in case of non-normal data distribution, PLS-SEM should be used for evaluating causal path models. For evaluating multivariate normality, the authors investigated “multivariate skewness and kurtosis” using a statistical tool from a website named Web Power ( WebPower, 2021 ). The outputs revealed that the data obtained in this study were not normally distributed as Mardia's multivariate skewness was β  = 2.954, p  < 0.01, and Mardia's multivariate kurtosis was β  = 30.064, p  < 0.01. Hence, the authors decided to utilize SmartPLS software because it is a “non-parametric” statistical data assessment tool.

Common method bias

The authors used Harman single factor test and the full collinearity test to investigate common method bias (CMB). The justification for choosing Harman single factor test is that it has been one of the easiest and most widely utilized techniques for detecting CMB ( Podsakoff et al. , 2003 ), while full collinearity test has been preferred because it was found to be robust in identifying CMB from the perspective of PLS-SEM ( Kock, 2015 ).

During Harman single factor test, the authors employed an unrotated exploratory factor analysis, which revealed that the first factor accounted for 35.947% variance ( Table A2 ). Besides, using a full collinearity test, the authors observed that the VIF values for all the latent constructs were less than 3.3, indicating that the model was not polluted by CMB ( Kock, 2015 ).

Measurement model evaluation

In this study, the authors performed a confirmatory factor analysis (CFA) to evaluate the convergent and discriminant validity of six constructs: PU, PEOU, PT, barriers to acceptance, attitude and intention to adopt MFS. Since all the constructs showed high inter-item correlations (>0.5) and excellent composite reliability (0.887), they have been treated as reflective constructs in the present study.

Table 2 demonstrates the outputs of CFA, showing satisfactory reliability because the latent constructs' composite reliability values are above 0.7 ( Hair et al. , 2016 ; Bappy et al. , 2020 ). Furthermore, the average variance extracted (AVE) of all the latent constructs are above the recommended cut-off point of 0.5, and item loadings are above 0.7, signifying sufficient convergent validity of all the constructs ( Hair et al. , 2019a , b ).

The authors evaluated the discriminant validity in light of the Fornell-Larcker criterion and HTMT ratio. As per the Fornell-Larcker criterion, “the square root of the AVE of each construct should exceed its corresponding correlation coefficients” ( Fornell and Larcker, 1981 ). Besides, the HTMT ratio is recently being used as the latest standard for evaluating discriminant validity. According to Henseler et al. (2015) , HTMT values of each latent construct should be lesser than 0.85 to ascertain discriminant validity. The outputs of discriminant validity considering the Fornell-Larcker criterion and HTMT ratio are demonstrated in Tables 3 and 4 , signifying satisfactory distinction among this study's latent variables.

Structural model evaluation

The structural model has been used to assess the hypothesized relationships between the constructs of this study. While evaluating the structural model, the authors investigated the VIF, R 2 , the significance of structural paths and the magnitude of the path coefficients.

The authors assessed the multicollinearity using VIF and found that VIF values for all the paths were less than 3.3, indicating no multicollinearity concerns. R 2 values for endogenous constructs, such as attitude toward using MFS and intention to adopt behavioral intention, were 0.502 and 0.395, respectively, revealing a satisfactory degree of in-sample explanatory power in social science research ( Rasoolimanesh et al. 2019 ). Besides, the authors ran the blindfolding procedure using an omission distance of D  = 8 to determine the path model's predictive relevance. To this end, Q 2 values of each endogenous construct (attitude and intention) were computed. As evident in Table 5 , Q 2 values for endogenous constructs, such as attitude and intention, are above zero, indicating predictive relevance regarding the outcome constructs ( Hair et al. , 2016 ).

Besides, the researchers employed bootstrapping with 5000 subsamples to ascertain the statistical significance of the path coefficients. Table 5 and Figure 2 show that the paths from PU to ATT ( β  = 0.258, p  < 0.05), PEOU to ATT ( β  = 0.205, p  < 0.05), PT to ATT ( β  = 0.314, p  < 0.05), barriers to ATT ( β  = −0.154, p  < 0.05), barriers to INT ( β  = −0.218, p  < 0.05) and ATT to INT ( β  = 0.594, p  < 0.05), are statistically significant and in the directions as postulated in the hypotheses. Therefore, H1 , H2 , H3 , H4 , H5 and H6 have been supported in this study. Furthermore, the relative size of the path coefficients as evident in Table 5 indicates that trust contributes most significantly to attitude, followed by PU, PEOU and barriers of adoption.

This study also assessed the indirect effects of PU, PEOU, PT and barriers to acceptance on the intention to adopt MFS through attitude toward using MFS. Table 6 outlines the results of specific indirect effects using the product of the coefficient approach. Table 6 shows statistically significant indirect effects ( p  < 0.05) for all the paths, providing substantial support for mediation ( Preacher and Hayes, 2004 ; Zhao et al. , 2010 ). Furthermore, bias-corrected confidence intervals were used to verify the mediation effect ( Memon et al. , 2018 ). Table 6 shows that zero does not appear between the indirect effects' confidence intervals, providing further empirical evidence for the mediation effect ( Hayes, 2017 ; Popy and Bappy, 2020 ). As a result, H7 (a–d) have been supported.

However, this study did not test the relationships between exogenous constructs and endogenous construct (INT) while testing mediation. The reason is that assessing the significance of exogenous constructs → endogenous construct before or following an intervening effect is an old-fashioned and needlessly restrictive approach ( Memon et al. , 2018 ), which defines the essential rule of parsimony ( Aguinis et al. , 2016 ).

This study also checked the robustness of the structural model by investigating the probable nonlinear relationships according to the guidelines of Svensson et al. (2018) . Studies in the past have highlighted the significance of checking nonlinear effects to ensure that the relationships are not incorrectly deemed to be linear ( Rasoolimanesh et al. , 2017 ; Sarstedt et al. , 2019 ).To test nonlinearity, the authors determined the quadratic effects of 1) PU, PEOU, PT and barriers on ATT and 2) ATT and barriers on INT. The outputs of bootstrapping with 5000 subsamples reveal that none of the nonlinear relationships are statistically significant ( Table 7 ). Hence, it can be stated that the linear relationships of the structural model are robust ( Sarstedt et al. , 2019 ).

Insights from focus group discussion

Do you consider the features and advantages provided by MFS apps beneficial? Why or why not? Does its cost make it a less viable option for more frequent transactions? Do MFS features change your attitude and future usage intention?

Are MFS apps easy to use or are they complicated? Elaborately discuss what difficulties you experience in the process of using MFS apps?

Do you consider MFS to be a safe platform for your regular transactions; especially for medium to large transactions? Why do you feel so?

What barriers might discourage you from using mobile financial services in the future? Is lack of smartphone know how a challenge for the elderly of the family?

Overall, express your attitude and intention to use mobile financial services. What factors are responsible for your current attitude toward MFS and usage behavior?

In response to these queries, the following excerpts are illustrative:

The discussion validated that usefulness and ease of use are still two of the prime reasons for customers' favorable/unfavorable outlook toward MFS system, encouraging/discouraging them to use the system. In response to the questions on PU and ease of use, one participant argued:

Participant 1# “MFS system or apps help me substantially in my daily life activities. I can send/receive money, make payments at the shops, pay utility bills, purchase Internet packages, tickets, pay students ' tuition fees, and many more using MFS apps. Overall, I love the system as it is easy to use and money exchange is secure. However, the cost of spending money is sometimes too high. Suppose, if I have to pay my credit card bills through a MFS service provider called bKash, I have to pay extra 200 plus BDT as charge. Despite that, I would say that the system is reducing my energy and time cost. Hence, there is no big reason why I should stop using the MFS system in the near future.”

The majority of the participants agreed with the aforementioned statement. However, two of the respondents stated that they are experiencing some difficulties while using the MFS platforms. They suggested that their attitude and future usage behavior might be negatively affected if those difficulties are not addressed. For instance, one respondent reported:

Participant 5# “ I use the MFS app of a service provider in Bangladesh for regular transactions. The app was somewhat user-friendly after first installation. However, these days, the app gets stuck on the loading screen more often than not. Sometimes, rebooting my device fixes the problem but other times, nothing helps. No matter how many times I try to log in, despite having no Internet issues, it would not just allow me to log in, which disappoints me a lot. If I regularly face such problems in the future, I would probably not recommend others to use such apps”

This opinion was echoed by another participant who commented:

Participant 6# “ I am using a leading MFS account for more than one year and it was functioning well. But recently, it takes too much time to open. Besides, it wants me to keep the device location on and its QR code scanning facility does not always work. In addition, it cannot sometimes detect the MFS registered SIM card despite being in the first slot. Because of these issues, I have somewhat unfavorable attitude toward this system”

Regarding trust/safety, participants endorsed that when users feel confident about the ability, benevolence and integrity of the MFS platforms to ensure safety, security and privacy of the users, their attitude and intention to use MFS becomes positive. But every participant collectively agreed that MFS providers should protect their clients from fraud gangs. For instance, one respondent mentioned:

Participant 2# “I think MFS platforms can be trusted for transactions. I feel safe about it because I do not have to take out money physically and deliver it. So, I do not have to worry about any mishaps. Another thing is if I am very cautious while typing the phone numbers or bank account numbers, there is no risk of losing my money. But a lot more work needs to be done to aware users about potential mobile money theft. In my opinion, MFS marketers should constantly alert customers about the potential risks of sharing pin codes to anyone”

During discussion, one elderly female respondent, nevertheless, mentioned that she does not trust MFS platforms after hearing news on mobile money thefts Whereas, rest of the members agreed that they have trust on MFS platforms and reiterated their willingness to use it.

In the discussion, when the researchers asked what barriers might cause negative user attitude and future usage behavior, different participants mentioned different obstacles. Some of the noteworthy barriers to acceptance that they reported include: high cash-out charge, low Income of marginal people, lack of digital penetration and digital literacy, conservative policies, fraudulence, lack of support from the ecosystem, lack of Smartphone know how, to name a few.

Subsequently, participants articulated their overall attitude toward using MFS as well as their future usage intention. They also expressed the reasons behind such attitude and behavioral intention. For instance, one informant reported that I have favorable attitude toward MFS platforms because I can send money instantly to any part of Bangladesh with just a few taps on the mobile app or phone. In addition, it is easy to use for payment while purchasing from e-commerce platforms since it does require any paperwork or documentation. Besides, these platforms have reduced the need for carrying a large amount of cash, especially during Eid shopping” .

Similar argument was proposed by another participant who said that “I feel positive about MFS platforms since we can get discounts in restaurants, retail shops, super shops, and ride-sharing platforms by payment through them. Furthermore, they can be used to pay utility bills without standing in a long queue as well as paying university fees”

In contrast, some respondents reported negative attitude. When the researchers asked the reasons behind their negative attitude, one participant replied: “We cannot send money from one MFS platform to another. For example, we cannot send money from a bKash account to a Nagad account”, whereas other informants stated that “ It becomes very problematic to solve the issue of someone sending money to the wrong account as they do not take any prompt actions and requires so many explanations and documents. Moreover, fraud activities are going around by using the brand name of these platforms. Unfortunately, they were not taking any significant measures to stop these kinds of activities.”

In the end, one participant stressed that “Considering all the costs and benefits, I am most likely to use these MFS in the future more significantly as it will be more convenient for me. However, MFS providers should lay more emphasis on solving the fraud issues that have been going on for a while the online payment from these platforms. Without doing that, I am most likely to lose my trust in those MFS platforms, and as a result, I will not keep a large amount of cash and will reduce my transactions levels. All the members of the focus group discussion unanimously agreed with these statements.

Hence, considering the aforementioned excerpts obtained from focus group discussion, it can be stated that PU, PEOU, user trust positively influence MFS users' attitude where barriers negatively affect MFS customers' attitude and future usage intention.

The study aimed to figure out the antecedents and consequences of attitude toward using MFS in Bangladesh by combining two theories, such as TAM and IRT. The facilitator factors influencing MFS users' attitudes include PU, ease of use and trust. The barriers of MFS adoption have been discovered as per IRT.

The outcomes substantiate that PU has a significant favorable influence on consumer attitude toward adopting MFSs in Bangladesh. This result differs from the Rahmiati and Yuannita (2019) but is broadly consistent with earlier studies of Raza et al. (2017) , Tjuk and Hapzi (2017) , and Letchumanan and Muniandy (2013) . These findings confirm our prediction that consumers who believe that using MFSs make their daily financial services effective and efficient and perceive that this contactless transaction will support them to conduct their economic activities smoothly and have a favorable attitude toward its usage. In Bangladesh, MFS platforms are, these days, collaborating with many other enterprises (banks, retail shops, restaurants, banks, e-commerce sites), enabling the users to conduct swift transactions. Besides, electric money is recorded in the app. These records have all the essential information about the transaction; the name of the payer, the name of the receiver, the date, allowing users to access their records at any time of the day. All these advantages lead to positive customer attitude toward using MFS system and vice versa.

The study further approves the hypothesis that PEOU of MFS positively affects consumers' attitudes. This result differs from the findings of Rahmawaty (2012) and Wang and Tseng (2011) but supports the studies of Singh and Srivastava (2018) and Popy and Bappy (2020) . Hence, all being equal, consumers who find MFS's various functions and activities more straightforward and understandable have a positive attitude toward using MFS. Considering this result, the authors of the present study encourage the MFS app developers in Bangladesh to continue their endeavor to make the MFS apps easier to use for the users because our focus group discussion revealed that customers sometimes feel annoyance to type pin code every time during log in. Hence, the authors recommend using biometric support for this app (Face ID or Fingerprints) for speeding up the login process.

Moreover, the link between trust and attitude has been found to be positive and significant in this study. Prior scholars, such as Chemingui and Ben lallouna (2013) , Permatasari and Kartikowati (2018) , found similar relationships in their studies. Thus, it has been verified that consumer attitude is positive toward those MFS provides who make and keep plausible promises and are trustworthy. This research contributes valuable insights from Bangladeshi context to the current literature regarding the relationship between trust and attitude toward using MFS.The focus group discussion, in this study, revealed that currently, in Bangladesh, there is no apparent solution that guarantees full protection from hacking attacks. Hence, one of the most significant drawbacks of MFS in Bangladesh is its vulnerabilities. A mobile device or hardware token can be stolen; voice can be replicated, and iris scanners can be hacked. Moreover, hackers can apply “man-in-the-middle” attacks to intercept SMS to get access to an OTP. These issues should be addressed by the MFS authorities to develop more customer trust to influence their attitude.

Besides, barriers to acceptance were found to have a significant and negative impact on the MFS users' attitude and behavioral intention. Previous scholars, such as Laukkanen et al. , (2007) and Kaur et al. (2020) , echoed the present study's findings. These relationships indicate that a higher degree of obstacles associated with MFS (usage barrier, value barrier, image barrier, risk barrier and many more) will create an unfavorable attitude and behavioral intention among the MFS users in Bangladesh. Presently, there are a number of technical issues in the country that can prevent the users' from adopting the MFS platforms. Internet and server problems, such as poor signal connection, can disable online payment method. In addition to this, some banks in Bangladesh block the international transactions for security. So far, it is not possible to deposit money into bank by using MFS nor is it possible to pay large sum of money using MFS because of the payment limitations imposed by service providers. In short, all these barriers, including the ones analyzed through survey, leads to negative customer attitude and behavioral intention.

Besides, this study demonstrated that whether or not consumers are intended to use MFSs depends on their attitude toward using MFS. This is opposite to what has been found by Wang and Tseng (2011) . Furthermore, the paper established that positive effects of PU, PEOU and trust, and adverse effects of barriers on MFS adoption are mediated by attitude. These results also confirm several antecedent scholarly works of Renny et al. (2013) , Elkaseh et al. (2016) . Hence, MFS service providers should devote their dollars, creativity and energy in forming favorable attitude of the customers toward using MFS technology by solving their complaints and providing them superior user experience.


Theoretical implications.

The study pointed out several theoretical implications. First, the authors modeled the predictors of attitude and intention to use MFSs utilizing an elaborated version of TAM, adding two additional antecedents: barriers and trust. Backed by IRT, this paper shows that barriers associated with using MFS are likely to result in unfavorable user attitudes, leading to a lower degree of MFS adoption intention. Second, the inclusion of new constructs in the original TAM model demonstrated adequate explanatory power and predictive relevance, explaining the attitudes and behavioral intention of Bangladeshi MFS users. Third, while previous studies that used the TAM model mostly evaluated the mediating role of attitude in the relationship for PU and PEOU, and trust with intention, this study provided additional insights regarding the mediating effect of attitude in the negative relationship between barriers to adoption and MFS adoption intention. Thus, this paper integrates the TAM and IRT and adds to the existing knowledge related to technology adoption intention.

Methodological contribution

This paper has employed an advanced statistical tool called SmartPLS 3.2.6 to predict and evaluate a confirmatory model using the PLS algorithm as the collected data were not normally distributed. Previous studies on MFS adoption primarily focused on the quantitative investigation of the causal relationships. However, the present study applied a mixed method (quantitative followed by qualitative approach) to obtain better insights regarding the findings obtained from path model investigation.

Managerial implications

MFS is not a new technology in a developing country like Bangladesh. It has been a decade that the people of Bangladesh are acquainted with the service. The study aimed to determine why the people of Bangladesh accept MFSs so vigorously. On the contrary, the barriers have also been identified to explain its slow growth and potential threats. The first managerial implication is for managers to focus more on the perceived ease of using an MFS technology. If users find it easy to learn and use MFSs, it becomes useful and trustworthy. This finding of the study denotes that the easiness of the technology helps to create trust among consumers. Many participants believe that clear, straightforward, understandable and flexible MFSs grow trust among the MFS users swiftly. The degree of easiness of technology also increases the usefulness dimensions of technology. As per users, if the technology is easy to use and learn, then users increase the usage of that technology in their daily life. So, the development of user-friendly technology (e.g. app, website, or USSD) is a prerequisite to promote PU and trust in MFSs among users.

Besides, every precaution must be taken by the MFSs providers and government to make the service trustworthy among the users. To develop trust among users, MFS providers must keep what they have promised in their value propositions. They must keep users' concerns in their minds whenever they formulate any policy or rule. Barriers are negatively influencing consumer intentions to use MFS. The existing barriers are refraining potential users from accepting the new technology. So, the players of MFSs must work with the government to mitigate impediments as soon as possible. The MFS providers also need to hear the voices of the consumers. Hence, they should come up with some solutions for receiving the complaints and grievances of consumers.

Conclusion, limitations and future research directions

MFSs are proliferating in Bangladesh. This emerging sector is complementing the current financial sectors and acting as a new player in the economic sector of Bangladesh.

In this study, the authors empirically verified the antecedents of users' attitudes toward adopting MFS services and its subsequent effect on their adoption intention. The researchers observed that PU, ease of use and trust contribute positively and significantly to attitude toward using MFS. Besides, barriers to adoption were found to have negative and significant effect on attitude and intention. Finally, mediating role of attitude in the relationship between predictor constructs (PU, PEOU, PT, barriers) and intention to adopt MFS has been established.

Overall, this paper showed theoretical, methodological and practical contributions. The authors believe that the research model tested in this paper will provide the practitioners enhanced insights on Bangladeshi users' attitude and MFS adoption intention, which will further assist the MFS practitioners to execute successful marketing campaigns, conduct appropriate positioning and carry out applied marketing research for the MFS industry.

However, the study contains a number of limitations. First, the sample size was relatively small, and the authors employed a non-probability sampling technique, which can sometimes produce biased results. Further studies should replicate and validate the present study's findings using a probability sampling method and a larger sample size to generalize the findings. Second, this is a cross-sectional study where data has been collected only once during a particular period. In the future, longitudinal studies can be carried out to identify the changes in customer attitudes and intention to use MFSs. Besides, a cross-cultural study might be conducted to ascertain the extent to which MFS adoption rates vary across countries. Third, this study evaluated only the behavioral intention of the users. However, the differences between usage intention and actual usage behavior are well-established in the prevailing academic literature ( Venkatesh et al ., 2003 ). Therefore, future studies should attempt to predict users' actual MFS usage utilizing the constructs employed in this study. Additional constructs, such as perceived enjoyment, perceived experience and system quality, might also be incorporated into the existing model to enrich its predictive power. Fourth, this study tested only the nonlinear effects for detecting the robustness of PLS-SEM results. Future studies should investigate the unobserved heterogeneity, endogeneity in a structural model estimating MFS adoption intention. Besides, empirical test, such as confirmatory-tetrad analysis, can be employed to ascertain whether the constructs are formative or reflective in nature.

Despite having numerous limitations, the authors believe that this study has covered a timely research domain, showing how MFS users' attitudes and behavioral intentions can be influenced. Thus, future researchers might consider this study as an impetus for evaluating consumers' behavior patterns in the MFS industry.

mobile accounting research paper

Research model

mobile accounting research paper

Structural model

Characteristics of respondents

CFA outcomes

Fornell-Larcker criterion

Hypothesis testing (direct effects)

Specific indirect effect

Checking nonlinearity

Scale items adapted from prior studies

Note(s): Extraction method: Principal axis factoring

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Further reading

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The authors thank the anonymous reviewers for their careful reading of our manuscript as well as for their insightful comments and suggestions. We also declare that this research received no specific fund from any funding agency in the public, commercial, or not-for-profit sectors.

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