Shahriar Akter

Trustworthiness in mHealth information services: An assessment of a hierarchical model with mediating and moderating effects using partial least squares (PLS)

The aim of this research is to advance both the theoretical conceptualization and the empirical validation of trustworthiness in mHealth (mobile health) information services research. Conceptually, it extends this line of research by reframing trustworthiness as a hierarchical, reflective construct, incorporating ability, benevolence, integrity, and predictability. Empirically, it confirms that partial least squares path modeling can be used to estimate the parameters of a hierarchical, reflective model with moderating and mediating effects in a nomological network. The model shows that trustworthiness is a second‐order, reflective construct that has a significant direct and indirect impact on continuance intentions in the context of mHealth information services. It also confirms that consumer trust plays the key, mediating role between trustworthiness and continuance intentions, while trustworthiness does not have any moderating influence in the relationship between consumer trust and continuance intentions. Overall, the authors conclude by discussing conceptual contributions, methodological implications, limitations, and future research directions of the study.

Development and validation of an instrument to measure user perceived service quality of mHealth

The role of service quality in fostering the growth of mHealth services has gained much attention in the academic and practitioner communities. However, empirical research in this area has been beset by inadequate conceptualization and the lack of a validated scale. This study addresses these limitations by theoretically conceptualizing and empirically validating a multidimensional service quality scale in the mHealth context. The findings show that mHealth service quality is a hierarchical, multidimensional, and reflective construct, which consists of three primary dimensions and eight subdimensions. The results also confirm that the mHealth service quality scale is more effective at predicting satisfaction and continuance in a nomological network.

Service quality of mHealth platforms: development and validation of a hierarchical model using PLS

Advancing research on service quality requires clarifying the theoretical conceptualizations and validating an integrated service quality model. The purpose of this study is to facilitate and elucidate practical issues and decisions related to the development of a hierarchical service quality model in mobile health (mHealth) services research. Conceptually, it extends theory by reframing service quality as a reflective, hierarchical construct and modeling its impact on satisfaction, intention to continue using and quality of life. Empirically, it confirms that PLS path modeling can be used to estimate the parameters of a higher order construct and its association with subsequent consequential latent variables in a nomological network. The findings of the study show that service quality is the third-order, reflective construct model with strong positive effects on satisfaction, continuance intentions and quality of life in the context of mHealth services. Finally, the study discusses the implications of hierarchical service quality modeling in electronic markets and highlights future research directions.

Big data analytics in E-commerce: a systematic review and agenda for future research

There has been an increasing emphasis on big data analytics (BDA) in e-commerce in recent years. However, it remains poorly-explored as a concept, which obstructs its theoretical and practical development. This position paper explores BDA in e-commerce by drawing on a systematic review of the literature. The paper presents an interpretive framework that explores the definitional aspects, distinctive characteristics, types, business value and challenges of BDA in the e-commerce landscape. The paper also triggers broader discussions regarding future research challenges and opportunities in theory and practice. Overall, the findings of the study synthesize diverse BDA concepts (e.g., definition of big data, types, nature, business value and relevant theories) that provide deeper insights along the cross-cutting analytics applications in e-commerce.

mHealth Technologies for Chronic Diseases and Elders: A Systematic Review

mHealth (healthcare using mobile wireless technologies) has the potential to improve healthcare and the quality of life for elderly and chronic patients. Many studies from all over the world have addressed this issue in view of the aging population in many countries. However, there has been a lack of any consolidated evidence-based study to classify mHealth from the dual perspectives of healthcare and technology. This paper reports the results of an evidence-based study of mHealth solutions for chronic care amongst the elderly population and proposes a taxonomy of a broad range of mHealth solutions from the perspective of technological complexity. A systematic literature review was conducted over 10 online databases and the findings were classified into four categories of predominant mHealth solutions, that is, self-healthcare, assisted healthcare, supervised healthcare and continuous monitoring. The findings of the study have major implications for information management and policy development in the context of the Millennium Development Goals (MDGs) related to healthcare in the world.

Continuance of mHealth services at the bottom of the pyramid: the roles of service quality and trust

Continued usage of information systems (or, IS continuance) has proven to be a critical success parameter for ICT implementation at the top of the global economic pyramid. However, there are few studies which have explored continued IS usage at the bottom of the economic pyramid (BOP) though it represents the majority of the world’s population. To fill this knowledge gap, this study develops an mHealth continuance model at the BOP framing the impact of two post adoption expectation beliefs (i.e., perceived service quality and perceived trust). This study extends ECM (expectation confirmation model) perspective synthesizing the extant literature on continued IS usage, service quality and consumer trust. The proposed model was empirically tested within the context of mHealth (mobile health) services at the BOP, applying PLS (partial least squares) under a cross sectional study. The findings confirm that both perceived service quality and perceived trust have significant explanatory power under an integrated ECM providing superior prediction of continuance intentions. The study concludes by discussing conceptual contributions, practical implications, limitations and future research directions.

Modelling quality dynamics, business value and firm performance in a big data analytics environment

Big data analytics have become an increasingly important component for firms across advanced economies. This paper examines the quality dynamics in big data environment that are linked with enhancing business value and firm performance (FPER). The study identifies that system quality (i.e. system reliability, accessibility, adaptability, integration, response time and privacy) and information quality (i.e. completeness, accuracy, format and currency) are key to enhance business value and FPER in a big data environment. The study also proposes that the relationship between quality and FPER is mediated by business value of big data. Drawing on the resource-based theory and the information systems success literature, this study extends knowledge in this domain by linking system quality, information quality, business value and FPER.

mHealth for Smoking Cessation Programs: A Systematic Review.

mHealth transforms healthcare delivery around the world due to its affordability and right time availability. It has been used for delivery of various smoking cessation programs and interventions over the past decade. With the proliferation of smartphone usage around the world, many smartphone applications are being developed for curbing smoking among smokers. Various interventions like SMS, progress tracking, distractions, peer chats and others are being provided to users through smartphone applications. This paper presents a systematic review that analyses the applications of mobile phones in smoking cessations. The synthesis of the diverse concepts within the literature on smoking cessations using mobile phones provides deeper insights in the emerging mHealth landscape.

mHealth for Influenza Pandemic Surveillance in Developing Countries

Influenza pandemics caused millions of deaths and massive economic losses worldwide in the last century. The impact of any future pandemic is likely to be greatest in developing countries as a result of their limited surveillance and healthcare resources. eHealth facilitates the detection and reporting of potential pandemic strains by using digital data transmitted, sorted and retrieved electronically both at the local site and at a distance. The implementation of eHealth is resource costly but developing countries have limited financial and technical resources. This adversely affects access to eHealth applications. Mobile communication technologies hold great promise in improving access to and affordability of eHealth services even to the poorest areas. This paper illustrates how a mobile phone SMS-based application can be applied to mHealth, potentially facilitating influenza pandemic surveillance in developing countries.

Modelling the impact of mHealth service quality on satisfaction, continuance and quality of life

Understanding the impact of service quality on economic and social outcomes is critical to extend the focus of IT service research. This study evaluates the impact of quality on both these dimensions in mHealth using a cross disciplinary approach. The conceptual model is rooted in the traditional cognition–affective–conation chain but explicitly incorporates convenience, confidence, cooperation, care and concern as the primary dimensions of mHealth quality. The model is validated in the context of a business-to-consumer mHealth services using partial least squares path modelling. The results confirm that service quality has both direct and indirect impact on continuance intentions (i.e. economic outcome) and quality of life (i.e. social outcome). In this relationship, satisfaction plays the key mediating role, whereas service quality does not have any moderating effect. Research implications point to scale and sustain this new healthcare paradigm by linking service quality to satisfaction, continuance intentions and quality of life.