Mariam Humayun and Russell W. Belk
Purpose: In this paper, we focus on the mythic nature of the anonymous Bitcoin creator, Satoshi Nakamoto. Drawing on ideas from Foucault and Barthes on authorship, we analyze the…
Abstract
Purpose: In this paper, we focus on the mythic nature of the anonymous Bitcoin creator, Satoshi Nakamoto. Drawing on ideas from Foucault and Barthes on authorship, we analyze the notion of the absence of the author and how that sustains the brand. Design/methodology/approach: Based on interview data, participant observation, archival data, and a netnography, we examine the discourses that emerge in the wake of multiple Satoshi Nakamoto exposés that serve as both stabilizing and destabilizing forces in the Bitcoin ecosystem. Findings: We analyze the different interpretations of Satoshi Nakamoto through his own text and how his readers interpret him. We identify how consumers employ motifs of myth and religiosity in trying to find meaning in Satoshi’s disappearance. His absence allows for multiple interpretations of how the Bitcoin brand is viewed and adopted by a diverse community of enthusiasts.
Implications: Our findings provide a richer understanding of how, in a period of celebrity brands, Satoshi Nakamoto’s anti-celebrity stance helps sustain the Bitcoin ecosystem.
Originality/value: Our analysis examines the nature of anonymity in our hyper-celebrity culture and the mystique of the anonymous creator that fuels modern-day myths for brands without owners.
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Md. Abdul Moktadir, Syed Mithun Ali, Sachin Kumar Mangla, Tasnim Ahmed Sharmy, Sunil Luthra, Nishikant Mishra and Jose Arturo Garza-Reyes
Managing risks is becoming a highly focused activity in the health service sector. In particular, due to the complex nature of processes in the pharmaceutical industry, several…
Abstract
Purpose
Managing risks is becoming a highly focused activity in the health service sector. In particular, due to the complex nature of processes in the pharmaceutical industry, several risks have been associated to its supply chains. The purpose of this paper is to identify and analyze the risks occurring in the supply chains of the pharmaceutical industry and propose a decision model, based on the Analytical Hierarchy Process (AHP) method, for evaluating risks in pharmaceutical supply chains (PSCs).
Design/methodology/approach
The proposed model was developed based on the Delphi method and AHP techniques. The Delphi method helped to select the relevant risks associated to PSCs. A total of 16 sub risks within four main risks were identified through an extensive review of the literature and by conducting a further investigation with experts from five pharmaceutical companies in Bangladesh. AHP contributed to the analysis of the risks and determination of their priorities.
Findings
The results of the study indicated that supply-related risks such as fluctuation in imports arrival, lack of information sharing, key supplier failure and non-availability of materials should be prioritized over operational, financial and demand-related risks.
Originality/value
This work is one of the initial contributions in the literature that focused on identifying and evaluating PSC risks in the context of Bangladesh. This research work can assist practitioners and industrial managers in the pharmaceutical industry in taking proactive action to minimize its supply chain risks. To the end, the authors performed a sensitivity analysis test, which gives an understanding of the stability of ranking of risks.
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Abdul Wahab Hashmi, Harlal Singh Mali and Anoj Meena
The purpose of this paper is to study the functionality of additively manufactured (AM) parts, mainly depending on their dimensional accuracy and surface finish. However, the…
Abstract
Purpose
The purpose of this paper is to study the functionality of additively manufactured (AM) parts, mainly depending on their dimensional accuracy and surface finish. However, the products manufactured using AM usually suffer from defects like roughness or uneven surfaces. This paper discusses the various surface quality improvement techniques, including how to reduce surface defects, surface roughness and dimensional accuracy of AM parts.
Design/methodology/approach
There are many different types of popular AM methods. Unfortunately, these AM methods are susceptible to different kinds of surface defects in the product. As a result, pre- and postprocessing efforts and control of various AM process parameters are needed to improve the surface quality and reduce surface roughness.
Findings
In this paper, the various surface quality improvement methods are categorized based on the type of materials, working principles of AM and types of finishing processes. They have been divided into chemical, thermal, mechanical and hybrid-based categories.
Research limitations/implications
The review has evaluated the possibility of various surface finishing methods for enhancing the surface quality of AM parts. It has also discussed the research perspective of these methods for surface finishing of AM parts at micro- to nanolevel surface roughness and better dimensional accuracy.
Originality/value
This paper represents a comprehensive review of surface quality improvement methods for both metals and polymer-based AM parts.
Graphical abstract of surface quality improvement methods
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Rupinder Singh, Jasminder Singh Dureja, Manu Dogra and Jugraj Singh Randhawa
This paper aims to focus on the application of multi-attribute decision-making methods (MADMs) to ascertain the optimal machining parameters while turning Ti-6Al-4V alloy under…
Abstract
Purpose
This paper aims to focus on the application of multi-attribute decision-making methods (MADMs) to ascertain the optimal machining parameters while turning Ti-6Al-4V alloy under minimum quantity lubrication (MQL) conditions using Jatropha-curcas oil (JCO) bio-based lubricant.
Design/methodology/approach
The experiments were designed and performed using Taguchi L27 design of experiments methodology. A total of 27 experiments were performed under MQL conditions using textured carbide cutting tools on which different MADMs like Analytic hierarchy process (AHP), Technique for order preference by similarity to ideal solution (TOPSIS) and Simple additive weighting (SAW) were implemented in an empirical manner to extract optimize machining parameters for turning of Ti-6Al-4V alloy under set of constrained conditions.
Findings
The results evaluated through MADMs exhibit the optimized set of machining parameters (cutting speed Vc = 80 m/min, feed rate f = 0.05 mm/rev. and depth of cut ap = 0.10 mm) for minimizing the average surface roughness (Ra), maximum flank wear (Vbmax), tangential cutting force (Fc) and cutting temperature (T). Further, analysis of variance (ANOVA) and traditional desirability function approach was applied and results of TOPSIS and SAW methods having optimal setting of parameters were compared as well as confirmation experiments were conducted to verify the results. A SEM analysis at lowest and highest cutting speeds was performed to investigate the tool wear patterns. At the highest speed, large cutting temperature generated, thereby resulted in chipping as well as notching and fracturing of the textured insert.
Originality/value
The research paper attempted in exploring the optimized machining parameters during turning of difficult-to-cut titanium alloy (Ti-6AL-4V) with textured carbide cutting tool under MQL environment through combined approach of MADMs techniques. Ti-6Al-4V alloy has been extensively used in important aerospace components like fuselage, hydraulic tubing, bulk head, wing spar, landing gear, as well as bio-medical applications.
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Joseph Vivek, Naveen Venkatesh S., Tapan K. Mahanta, Sugumaran V., M. Amarnath, Sangharatna M. Ramteke and Max Marian
This study aims to explore the integration of machine learning (ML) in tribology to optimize lubrication interval decisions, aiming to enhance equipment lifespan and operational…
Abstract
Purpose
This study aims to explore the integration of machine learning (ML) in tribology to optimize lubrication interval decisions, aiming to enhance equipment lifespan and operational efficiency through wear image analysis.
Design/methodology/approach
Using a data set of scanning electron microscopy images from an internal combustion engine, the authors used AlexNet as the feature extraction algorithm and the J48 decision tree algorithm for feature selection and compared 15 ML classifiers from the lazy-, Bayes and tree-based families.
Findings
From the analyzed ML classifiers, instance-based k-nearest neighbor emerged as the optimal algorithm with a 95% classification accuracy against testing data. This surpassed individually trained convolutional neural networks’ (CNNs) and closely approached ensemble deep learning (DL) techniques’ accuracy.
Originality/value
The proposed approach simplifies the process, enhances efficiency and improves interpretability compared to more complex CNNs and ensemble DL techniques.
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Soroush Dehghan Salmasi, Mohammadbashir Sedighi, Hossein Sharif and Mahmood Hussain Shah
Traditionally, the banking and financial sectors have pioneered adoption of new technologies and business models. One important digital banking model that has proven its efficacy…
Abstract
Purpose
Traditionally, the banking and financial sectors have pioneered adoption of new technologies and business models. One important digital banking model that has proven its efficacy in recent times, is Digital-Only Banking (DOB) where consumers interact with their banks through digital channels only. Having detailed knowledge of what actually happens at the consumer level during the adoption of new digital models and technologies is paramount to the success of these technological initiatives. The present study aims to investigate DOB adoption behavior and possible barriers using a quantitative approach at the consumer level. A conceptual model is developed by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) model, incorporating Trust (TR), Perceived Risk (PR) constructs and cultural moderators of Individualism (IDV) and Uncertainty Avoidance (UA).
Design/methodology/approach
For this study, an online survey instrument was created and administered in Iran. The research sample was selected through the application of purposive sampling. Data from 788 respondents were analyzed. The proposed model was tested using Partial Least Square.?.s Structural Equation Modeling (PLS-SEM).
Findings
The results show that DOB adoption is positively influenced by Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC), while PR negatively influences DOB adoption intention. Unexpectedly, the results indicate that TR has no significant impact on DOB usage intention. Additionally, this study demonstrates that with individuals having a low level of IDV, the relationship between PE and BI is stronger, and with individuals having a low level of UA, the impact of SI on BI is stronger. It also reveals that the impact of TR on BI is stronger in low individualistic cultures.
Practical implications
DOB providers should enhance support features of their services or provide facilities that make it simpler for users to accomplish online transactions. Here, in order to improve the UI/UX design of their apps, DOB product managers should carefully observe the technical guidelines of the operating systems of digital devices, such as the Human Interface Guidelines (HIG) for iOS and Material You for Android. Additionally, DOB providers should build partnerships with mega online retailers to provide hassle-free and easy to use payment solutions for consumers.
Originality/value
DOB, as a novel and business model, has been investigated in very few studies, especially regarding any which focus on its adoption. To fill this gap, this research investigates DOB adoption through a modified version of the UTAUT model. The findings of this study suggest that future research regarding DOB should consider sources of TR, types of non-adopters, and context. This study, as the first of its kind in DOB literature, also highlights the significant role played by cultural values in customer behavior regarding DOB adoption.
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Guillermo A. Sandoval, Adalsteinn D. Brown, Walter P. Wodchis and Geoffrey M. Anderson
The purpose of this paper is to investigate the relationship between hospital adoption and use of computed tomography (CT) scanners, and magnetic resonance imaging (MRI) machines…
Abstract
Purpose
The purpose of this paper is to investigate the relationship between hospital adoption and use of computed tomography (CT) scanners, and magnetic resonance imaging (MRI) machines and in-patient mortality and length of stay.
Design/methodology/approach
This study used panel data (2007–2010) from 124 hospital corporations operating in Ontario, Canada. Imaging use focused on medical patients accounting for 25 percent of hospital discharges. Main outcomes were in-hospital mortality rates and average length of stay. A model for each outcome-technology combination was built, and controlled for hospital structural characteristics, market factors and patient characteristics.
Findings
In 2010, 36 and 59 percent of hospitals had adopted MRI machines and CT scanners, respectively. Approximately 23.5 percent of patients received CT scans and 3.5 percent received MRI scans during the study period. Adoption of these technologies was associated with reductions of up to 1.1 percent in mortality rates and up to 4.5 percent in length of stay. The imaging use–mortality relationship was non-linear and varied by technology penetration within hospitals. For CT, imaging use reduced mortality until use reached 19 percent in hospitals with one scanner and 28 percent in hospitals with 2+ scanners. For MRI, imaging use was largely associated with decreased mortality. The use of CT scanners also increased length of stay linearly regardless of technology penetration (4.6 percent for every 10 percent increase in use). Adoption and use of MRI was not associated with length of stay.
Research limitations/implications
These results suggest that there may be some unnecessary use of imaging, particularly in small hospitals where imaging is contracted out. In larger hospitals, the results highlight the need to further investigate the use of imaging beyond certain thresholds. Independent of the rate of imaging use, the results also indicate that the presence of CT and MRI devices within a hospital benefits quality and efficiency.
Originality/value
To the authors’ knowledge, this study is the first to investigate the combined effect of adoption and use of medical imaging on outcomes specific to CT scanners and MRI machines in the context of hospital in-patient care.
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Emmanuel Mogaji, Giampaolo Viglia, Pallavi Srivastava and Yogesh K. Dwivedi
The technology acceptance model (TAM) is a widely used framework explaining why users accept new technologies. Still, its relevance is questioned because of evolving consumer…
Abstract
Purpose
The technology acceptance model (TAM) is a widely used framework explaining why users accept new technologies. Still, its relevance is questioned because of evolving consumer behavior, demographics and technology. Contrary to a research paper or systematic literature review, the purpose of this critical reflection paper is to discuss TAM's relevance and limitations in hospitality and tourism research.
Design/methodology/approach
This paper uses a critical reflective approach, enabling a comprehensive review and synthesis of recent academic literature on TAM. The critical evaluation encompasses its historical trajectory, evolutionary growth, identified limitations and, more specifically, its relevance in the context of hospitality and tourism research.
Findings
TAM's limitations within the hospitality and tourism context revolve around its individual-centric perspective, limited scope, static nature, cultural applicability and reliance on self-reported measures.
Research limitations/implications
To optimize TAM's efficacy, the authors propose several strategic recommendations. These include embedding TAM within the specific context of the industry, delving into TAM-driven artificial intelligence adoption, integrating industry-specific factors, acknowledging cultural nuances and using comprehensive research methods, such as mixed methods approach. It is imperative for researchers to critically assess TAM's suitability for their studies and be open to exploring alternative models or methods that can adeptly navigate the distinctive dynamics of the industry.
Originality/value
This critical reflection paper prompts a profound exploration of technology adoption within the dynamic hospitality and tourism sector, makes insightful inquiries into TAM's future potential and presents recommendations.
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Ji Yu, David J. Pauleen, Nazim Taskin and Hamed Jafarzadeh
The outbreak of COVID-19 is one of the most serious health events in recent times. In the business landscape, its effects may be more detrimental to micro-, small- and…
Abstract
Purpose
The outbreak of COVID-19 is one of the most serious health events in recent times. In the business landscape, its effects may be more detrimental to micro-, small- and medium-sized enterprises (MSMEs) because they tend to have limited financial and human resources to manage the challenges caused by COVID-19. To help MSMEs enhance their resilience, this paper aims to discuss how they can leverage mass collaboration to build social media-based knowledge ecosystems to manage interactions among internal and external stakeholders for knowledge creation and innovation.
Design/methodology/approach
The paper proposes a model for MSMEs to build an online knowledge ecosystem and a standalone text analytics tool to use the advanced data analytics, e.g. topic modeling, to analyze and aggregate collective insights. Design science research methodology is used to develop the model and the tool.
Findings
Through mass collaboration using social media and advanced data analytics technology, MSMEs can generate new business ideas, leading to enhanced resilience to meet the challenges caused by COVID-19 or other unexpected or extraordinary circumstances, such as natural disasters and financial crises.
Originality/value
To the best of authors’ knowledge, this paper is one of the first papers in social media adoption for knowledge creation and innovation research, providing detailed approaches for MSMEs to build a knowledge ecosystem on social media and to use advanced data analytics to mine the meaning of the generated data.