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Article
Publication date: 23 October 2020

Mallika Srivastava and Madhur Raina

This paper aims to identify and empirically validate the various factors for adoption, usage and intention to recommend e-pharmacy for purchasing medications by consumers.

Abstract

Purpose

This paper aims to identify and empirically validate the various factors for adoption, usage and intention to recommend e-pharmacy for purchasing medications by consumers.

Design/methodology/approach

Based on constructs from well-established theoretical models, the technology acceptance model, extended unified theory of acceptance and use of technology and self-determination theory, a model was proposed for the study. The model was validated with a sample size of 184 respondents using partial least squares method and factor analysis to establish and validate relationships among the various identified constructs.

Findings

The results show that performance expectancy, effort expectancy, social influence and hedonic motivation have a positive co-relation with adoption of e-pharmacy and the intention to recommend. The results depict that gender and educational background have no correlation toward adoption and intention to recommend e-pharmacies for purchasing medicines in India.

Research limitations/implications

This research comes along with a geographic limitation of the sample size. The research was conducted in an urban suburb city of Bengaluru, India.

Practical implications

At an academic level, this research will provide interesting insights for exploring adoption and usage intention of consumers toward e-pharmacy. At a managerial level, this empirically supported study will provide insights into the relationship among the various constructs and the consumers’ motivation toward adoption and usage intention of e-pharmacy.

Originality/value

This research is the first of its form which uses constructs from the technology acceptance model, extended unified theory of acceptance and use of technology and self-determination theory in the online healthcare space to understand consumer usage behavior.

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. 15 no. 2
Type: Research Article
ISSN: 1750-6123

Keywords

Article
Publication date: 5 July 2022

Mahesh Babu Mariappan, Kanniga Devi, Yegnanarayanan Venkataraman and Samuel Fosso Wamba

The purpose of this study is to present a large-scale real-world comparative study using pre-COVID lockdown data versus post-COVID lockdown data on predicting shipment…

Abstract

Purpose

The purpose of this study is to present a large-scale real-world comparative study using pre-COVID lockdown data versus post-COVID lockdown data on predicting shipment times of therapeutic supplies in e-pharmacy supply chains and show that our proposed methodology is robust to lockdown effects.

Design/methodology/approach

The researchers used organic data of over 5.9 million records of therapeutic shipments, with 2.87 million records collected pre-COVID lockdown and 3.03 million records collected post-COVID lockdown. The researchers built various Machine Learning (ML) classifier models on the two datasets, namely, Random Forest (RF), Extra Trees (XRT), Decision Tree (DT), Multi-Layer Perceptron (MLP), XGBoost (XGB), CatBoost (CB), Linear Stochastic Gradient Descent (SGD) and the Linear Naïve Bayes (NB). Then, the researchers stacked these base models and built meta models on top of them. Further, the researchers performed a detailed comparison of the performances of ML models on pre-COVID lockdown and post-COVID lockdown datasets.

Findings

The proposed approach attains performance of 93.5% on real-world post-COVID lockdown data and 91.35% on real-world pre-COVID lockdown data. In contrast, the turn-around times (TAT) provided by therapeutic supply logistics providers are 62.91% accurate compared to reality in post-COVID lockdown times and 73.68% accurate compared to reality pre-COVID lockdown times. Hence, it is clear that while the TAT provided by logistics providers has deteriorated in the post-pandemic business climate, the proposed method is robust to handle pandemic lockdown effects on e-pharmacy supply chains.

Research limitations/implications

The implication of the study provides a novel ML-based framework for predicting the shipment times of therapeutics, diagnostics and vaccines, and it is robust to COVID-19 lockdown effects.

Practical implications

E-pharmacy companies can readily adopt the proposed approach to enhance their supply chain management (SCM) capabilities and build resilience during COVID lockdown times.

Originality/value

The present study is one of the first to perform a large-scale real-world comparative analysis on predicting therapeutic supply shipment times in the e-pharmacy supply chain with novel ML ensemble stacking, obtaining robust results in these COVID lockdown times.

Details

International Journal of Physical Distribution & Logistics Management, vol. 52 no. 7
Type: Research Article
ISSN: 0960-0035

Keywords

Article
Publication date: 12 January 2022

Mahesh Babu Mariappan, Kanniga Devi, Yegnanarayanan Venkataraman, Ming K. Lim and Panneerselvam Theivendren

This paper aims to address the pressing problem of prediction concerning shipment times of therapeutics, diagnostics and vaccines during the ongoing COVID-19 pandemic…

Abstract

Purpose

This paper aims to address the pressing problem of prediction concerning shipment times of therapeutics, diagnostics and vaccines during the ongoing COVID-19 pandemic using a novel artificial intelligence (AI) and machine learning (ML) approach.

Design/methodology/approach

The present study used organic real-world therapeutic supplies data of over 3 million shipments collected during the COVID-19 pandemic through a large real-world e-pharmacy. The researchers built various ML multiclass classification models, namely, random forest (RF), extra trees (XRT), decision tree (DT), multilayer perceptron (MLP), XGBoost (XGB), CatBoost (CB), linear stochastic gradient descent (SGD) and the linear Naïve Bayes (NB) and trained them on striped datasets of (source, destination, shipper) triplets. The study stacked the base models and built stacked meta-models. Subsequently, the researchers built a model zoo with a combination of the base models and stacked meta-models trained on these striped datasets. The study used 10-fold cross-validation (CV) for performance evaluation.

Findings

The findings reveal that the turn-around-time provided by therapeutic supply logistics providers is only 62.91% accurate when compared to reality. In contrast, the solution provided in this study is up to 93.5% accurate compared to reality, resulting in up to 48.62% improvement, with a clear trend of more historic data and better performance growing each week.

Research limitations/implications

The implication of the study has shown the efficacy of ML model zoo with a combination of base models and stacked meta-models trained on striped datasets of (source, destination and shipper) triplets for predicting the shipment times of therapeutics, diagnostics and vaccines in the e-pharmacy supply chain.

Originality/value

The novelty of the study is on the real-world e-pharmacy supply chain under post-COVID-19 lockdown conditions and has come up with a novel ML ensemble stacking based model zoo to make predictions on the shipment times of therapeutics. Through this work, it is assumed that there will be greater adoption of AI and ML techniques in shipment time prediction of therapeutics in the logistics industry in the pandemic situations.

Details

The International Journal of Logistics Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0957-4093

Keywords

Article
Publication date: 11 September 2007

Ali Ahamd Awad Rawabdeh

The purpose of this research is to examine the potential of e‐health by focusing explicitly on the delivery of health care products and services. The examination of…

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Abstract

Purpose

The purpose of this research is to examine the potential of e‐health by focusing explicitly on the delivery of health care products and services. The examination of e‐health activity is guided by one broad research question, “What is the potential for constructing e‐health strategy as an innovative health technology?”. A great amount of attention has been given to e‐health activity in the present day. However important this form of e‐health is, this type of service simply does not face the same constraints that must be addressed by those actually delivering health care services.

Design/methodology/approach

The researchers employed a qualitative data collection technique to formulate more examples and cases to derive lessons for Jordan. Phone interviews in a random sample were conducted with corporate officers in Jordan in order to reveal the internal organizational structure and business trends, interface issues, marketing strategies, as well as comparing and contrasting the online health world to the traditional health care realm.

Findings

Internet‐related projects is a top priority for health care information technology executives in the present day, with a cautious approach toward “e‐health”, as many products have yet to mature, and that the “click and mortar” model may perhaps be the optimal strategy for e‐health in Jordan.

Research limitations/implications

This paper reviews the e‐health trends to demonstrate the tremendous potential for health‐related commercial activity on the internet. However, the researcher examining the barriers facing e‐health to the Jordanian health system also pointed out almost insurmountable challenges.

Practical implications

Despite the apparent promise of e‐health, its instability is measured by its failure so far to systematically penetrate the organization of health care. Beyond the pragmatic negotiation of e‐health in the immediate context of clinical practice, there are wider issues about how the development/implementation of e‐health is funded, about its organization and management at the policy level; and about its potential medico‐legal risks.

Originality/value

It is hoped that the handful of ventures into cyber medicine appears to be coming from a few enterprising physicians who have set up medical practices on the Web.

Details

International Journal of Health Care Quality Assurance, vol. 20 no. 6
Type: Research Article
ISSN: 0952-6862

Keywords

Article
Publication date: 18 November 2020

Md. Mahiuddin Sabbir, Mazharul Islam and Samir Das

This study aims to understand the determinants of online pharmacy or epharmacy adoption among young consumers in Bangladesh using an extended unified theory of acceptance…

Abstract

Purpose

This study aims to understand the determinants of online pharmacy or epharmacy adoption among young consumers in Bangladesh using an extended unified theory of acceptance and use of technology (UTAUT) model.

Design/methodology/approach

A structured Google Docs questionnaire was sent out to 420 respondents using messenger service; 285 useable responses were finally extracted. Data were empirically validated using the two-staged structural equation model (SEM)-neural network analysis approach.

Findings

The robustness of the classical UTAUT model remains intact in the context of online pharmacy adoption. Among the integrated variables, while perceived trust and health literacy were found significant, perceived risk and personal innovativeness were found insignificant in determining consumers’ intention to adopt online pharmacy. The neural network analysis provided further verification of these findings derived from the SEM.

Practical implications

The findings of this study would facilitate in devising better strategies for entering or expanding online pharmacy business in developing countries such as Bangladesh.

Originality/value

The originality of the current study relates to the two-fold contributions of this study. First, while this study extended the classical UTAUT model by incorporating perceived risk, perceived trust, personal innovativeness and health literacy, the inclusion of the following two variables is fresh within the extant online pharmacy literature. Second, by using a two-staged SEM-neural network analysis approach, this study advances the past studies on e-commerce adoption in pharmaceutical settings and provides a general understanding of the customers of developing countries.

Details

Journal of Science and Technology Policy Management, vol. 12 no. 4
Type: Research Article
ISSN: 2053-4620

Keywords

Article
Publication date: 6 September 2021

Bishwajit Nayak, Som Sekhar Sekhar Bhattacharyya, Onkar Kulkarni and Syed Nawaz Mehdi

The purpose of this study is to identify antecedents of adoption and post-adoption switching of online pharmacy applications (OPA) in Indian society. A push-pull-mooring…

Abstract

Purpose

The purpose of this study is to identify antecedents of adoption and post-adoption switching of online pharmacy applications (OPA) in Indian society. A push-pull-mooring (PPM) model was formulated to evaluate the impact of various constructs upon “consumers’ switching intention” (CSI).

Design/methodology/approach

An online questionnaire was sent to 252 users of OPA in India. Hypotheses were generated to examine the push, pull and mooring effects of constructs developed. The relationships between dependent and independent variables were evaluated using structured equation modeling (SEM).

Findings

The study explicated the effect of PPM constructs on CSI in the context of OPA adoption. “Perceived usefulness,” “perceived ease of use” and “alternative attractiveness” had a significant “pull” effect on CSI. “Switching cost” had a “mooring” effect on CSI, whereas the degree of “customer involvement in decision-making” was found to have a “push” effect upon CSI.

Research limitations/implications

This study theoretically established that the constructs of “perceived usefulness,” “perceived ease of use” and “alternative attractiveness” had significant “pull” effect on “consumers’ switching intention.” The construct of “switching cost” had a “mooring” effect on CSI, whereas the degree of “customer involvement in decision-making” was found to have a “push” effect upon CSI.

Practical implications

The study provided valuable insights regarding consumer behavior regarding OPAs. These findings could be applied by managers in framing effective strategies to grow and retain the customer base of OPAs.

Originality/value

To the best of the authors’ knowledge, this was one of the first empirical investigative studies to assess precursors of adoption and post-adoption characteristics of consumer behavior through the PPM model, in the context of Indian OPAs.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 20 November 2009

John Hamilton

The purpose of this paper is to elucidate the pathways that can enhance pharmacy‐to‐customer engagements, and give capacity to build closely aligned customer interface systems.

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Abstract

Purpose

The purpose of this paper is to elucidate the pathways that can enhance pharmacy‐to‐customer engagements, and give capacity to build closely aligned customer interface systems.

Design/methodology/approach

A nationwide, pharmacy and customer, dual survey‐based service value networks (SVNs) approach, analysed using structural equation modelling (SEM), shows significant business‐customer encounter information pathways act between the pharmacy and its engaging customer.

Findings

The complex nature of the business‐customer exchange and its interacting pathways is highlighted. Six front‐end SVNs business cells engaged in this paper have significant direct (and/or indirect) impact on customer perspectives of their pharmacy. Hence, the pharmacy front‐end business model should be fully and intelligently networked.

Research limitations/implications

The SVNs and SEM approach yields a strong robust pharmacy model, and can move pharmacy business management mechanisms to elevated customer‐engaging levels. It can offer customer‐targeted interaction solutions with enhanced perceived satisfaction. This SVNs approach is efficient, understandable, measurable and business specific. It is appropriate for market leaders, innovators or differentiators. Combined with other interface‐related toolkits it can deliver competitive advantage parameters such as understanding the key measures that improve business‐customer alignment.

Originality/value

SVNs developed under SEM offer a new way to better align the business with its customers. They can be applied at the individual community pharmacy or pharmacy chain level. SVNs release the key measures from which pertinent interacting front‐end business‐to‐customer pathways may be adjusted in a quest to strategically build and align the business closely to its customer demands. This win‐win SVNs interface procedure can also be applied within other service industries.

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. 3 no. 4
Type: Research Article
ISSN: 1750-6123

Keywords

Abstract

Details

The Bottom Line, vol. 35 no. 2/3
Type: Research Article
ISSN: 0888-045X

Expert briefing
Publication date: 14 March 2022

The growth of healthtech is led by the private sector and facilitated by the government, which sees the technology as a means to expand health access to all.

Details

DOI: 10.1108/OXAN-DB267920

ISSN: 2633-304X

Keywords

Geographic
Topical
Article
Publication date: 1 December 2004

Jane Mounteney

No one knows what the future holds. Not least for substance use and addictions. Few predicted the psychedelic movement in the 1960s, the crack ‘epidemic’ in the 1980s and…

Abstract

No one knows what the future holds. Not least for substance use and addictions. Few predicted the psychedelic movement in the 1960s, the crack ‘epidemic’ in the 1980s and the ‘E’ generation of the 1990s ‐ all of which had a profound influence on our culture, youth and our health. So what of the Naughties, Teenies and Twenties? With increased globalisation, new technologies, increasing spending power and the scope for increased pleasure‐seeking we are destined for more and new addictions. In this groundbreaking article, Jane Mounteney applies the technique of scenario planning to investigate a future dominated by technology, smart and nanodrugs and an ever‐increasing availability of drugs. With the emergence of the super nerd and groovy geek, who will be there to help the fallen?

Details

Drugs and Alcohol Today, vol. 4 no. 4
Type: Research Article
ISSN: 1745-9265

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