Purpose
Online shopping has continued to grow in popularity, and the advance of internet technology has enhanced customers’ experiences. One technology online retailers have been using to increase ...sales is virtual try-on (VTO). The purpose of this paper is to investigate how such technology affects online consumers’ purchase decision process towards purchase intention, especially from an integration of utilitarian, hedonic and risk perspectives, by using advanced partial least square (PLS) approaches.
Design/methodology/approach
This study applied a web-based survey approach for data collection from online apparel retailing websites. The survey instrument was developed by adapting previously validated measurement items. The valid data collected were analysed using PLS with multi-group analyses. Advanced PLS techniques such as examination of discriminant validity using heterotrait-monotrait ratio, tests of out-of-sample prediction performance, and measurement invariance of composite models were applied.
Findings
The results of examining the proposed model reveal that customers’ attitude towards VTO technology can affect their intention to purchase a garment online, which is affected by perceived usefulness, perceived enjoyment and perceived privacy risk. Perceived ease of use is found to affect perceived usefulness and perceived helpfulness. The results also show no significant differences among age groups and genders in terms of the role of VTO technology in the full decision process towards online purchase intention.
Originality/value
This study enhances the understanding of the roles that VTO technology plays in consumers’ online purchase intention by providing an integrative view of its utilitarian value, hedonic value and risk. This study demonstrates the feasibility of applying advanced PLS techniques to investigate online consumer behaviour, particularly in the field of VTO application in online retailing. Implications for online retailers and designers of VTO technology are also derived from the findings.
This study aims to investigate the factors that affect physicians' healthcare service provision behavior on healthcare service platforms. A research model was proposed based on the related literature ...and uses and gratifications theory and self-determination theory. The empirical data were collected from a popular Chinese healthcare service platform, and negative binomial regression was employed to test the proposed research model. The results indicate that competence satisfaction, autonomy satisfaction, and economic benefit have positive impacts on their service provision behavior and that when physicians have a higher level of offline status, they would be less likely to provide consultation service online if they have a higher level of competence satisfaction. This study contributes to the existing literature by integrating intrinsic and extrinsic motivations to investigate how they affect physicians' healthcare service provision behavior online. Findings from this study may derive recommendations for improving the features and design of healthcare service platforms.
With the rapid development of the COVID-19 pandemic, countries are trying to cope with increasing medical demands, and, at the same time, to reduce the increase of infected numbers by implementing a ...number of public health measures, namely non-pharmaceutical interventions (NPIs). These public health measures can include social distancing, frequent handwashing, and personal protective equipment (PPE) at the personal level; at the community and the government level, these measures can range from canceling activities, avoiding mass gatherings, closing facilities, and, at the extreme, enacting national or provincial lockdowns. Rather than completely stopping the infectious disease, the major purpose of these NPIs in facing an emerging infectious disease is to reduce the contact rate within the population, and reduce the spread of the virus until the time a vaccine or reliable medications become available. The idea is to avoid a surge of patients with severe symptoms beyond the capacity of the hospitals' medical resources, which would lead to more mortality and morbidity. While many countries have experienced steep curves in new cases, some, including Hong Kong, Vietnam, South Korea, New Zealand, and Taiwan, seem to have controlled or even eliminated the infection locally. From its first case of COVID-19 on the 21 January until the 12 May, Taiwan had 440 cases, including just 55 local infections, and seven deaths in total, representing 1.85 cases per 100,000 population and a 1.5% death rate (based on the Worldometer 2020 statistics of Taiwan's population of 23.8 million). This paper presents evidence that spread prevention involving mass masking and universal hygiene at the early stage of the COVID-19 pandemic resulted in a 50% decline of infectious respiratory diseases, based on historical data during the influenza season in Taiwan. These outcomes provide potential support for the effectiveness of widely implementing public health precaution measures in controlling COVID-19 without a lockdown policy.
Purpose
The purpose of this paper is to explain how enterprise resource planning (ERP) implementation evolves by cloud computing in different industries with different delivery models of cloud ERP. ...This paper also investigates infrastructure as a service (IaaS) as a delivery approach for cloud ERP. Case research on IaaS is rarely found in the literature. In addition, this paper intends to reveal how this transformation from on-premises to the cloud would influence the ERP implementation process.
Design/methodology/approach
A multiple-case study is conducted to identify the different deployed models of cloud ERP systems in the implementation projects. The influences of emerging cloud computing technology on ERP implementation are investigated by interviewing consultants related to the projects.
Findings
The findings illustrate that not only software as a service (SaaS) but also IaaS and platform as a service cloud computing services are widely applied in cloud ERP implementation. This study also indicates that certain technical limitations of cloud ERP might have a positive effect on the outcome of ERP implementation.
Originality/value
This study investigates how cloud computing influences ERP implementation from different aspects. The result identifies both SaaS and IaaS as two different approaches widely adopted in cloud ERP implementation. Besides, this study has discussed in-depth and analyzed these two cloud ERP paradigms in five factors, including functionality, performance, portability, security, cost and customization. The classification and suggestions are original to the literature.
Purpose
– Extant research on supply chain integration defines integration in different ways, and mainly discusses a limited number of integration elements. The purpose of this paper is to develop a ...conceptual integration model which consists of comprehensive elements that are important to academic research and industrial practices.
Design/methodology/approach
– Key literature survey with drawing threads of existing practices together for developing a systematic referential model and then verify the model with a real case.
Findings
– Developed a model consisting of integration elements residing at the strategic, managerial, operational, and fundamental levels (bottom line). Based on the benefit alignment, the total integration requires supply chain partners to integrate resource flows (material, information, knowledge, and finance), processes and organization, planning and control activities and strategy.
Research limitations/implications
– The research is based on secondary data and a case study illustration. Further empirical research is required.
Practical implications
– The normative model can guide managers to integrate resources and activities in their efforts for an effective supply chain management. It supplements the Supply Chain Operations Reference Model developed by the Supply Chain Council with an interface description, which may guide the development of information systems for supply chain integration.
Originality/value
– The comprehensive model provides a more inclusive and integrated perspective of supply chain integration. It is expected that the consensus of supply chain integration could be achievable based on this model. The conceptual framework will assist the researchers to determine integration variables of supply chain.
Purpose
This paper aims to investigate the value of big data investments by examining the market reaction to company announcements of big data investments and tests the effect for firms that are ...either knowledge intensive or not.
Design/methodology/approach
This study is based on an event study using data from two stock markets in China.
Findings
The stock market sees an overall index increase in stock prices when announcements of big data investments are revealed by grouping all the listed firms included in the sample. Increased stock prices are also the case for non-knowledge intensive firms. However, the stock market does not seem to react to big data investment announcements by testing the knowledge intensive firms along.
Research limitations/implications
This study contributes to the literature on assessing the economic value of big data investments from the perspective of big data information value chain by taking an unexpected change in stock price as the measure of the financial performance of the investment and by comparing market reactions between knowledge intensive firms and non-knowledge intensive firms. Findings of this study can be used to refine practitioners’ understanding of the economic value of big data investments to different firms and provide guidance to their future investments in knowledge management to maximize the benefits along the big data information value chain. However, findings of study should be interpreted carefully when applying them to companies that are not publicly traded on the stock market or listed on other financial markets.
Originality/value
Based on the concept of big data information value chain, this study advances research on the economic value of big data investments. Taking the perspective of stock market investors, this study investigates how the stock market reacts to big data investments by comparing the reactions to knowledge-intensive firms and non-knowledge-intensive firms. The results may be particularly interesting to those publicly traded companies that have not previously invested in knowledge management systems. The findings imply that stock investors tend to believe that big data investment could possibly increase the future returns for non-knowledge-intensive firms.
PurposeThis research proposes a decision framework for using non-financial measures to define a replenishment policy for perishable health products. These products are perishable and substitutable by ...nature and create complexities for managing inventory. Instead of a financial measure, numerous measures should be considered and balanced to meet business objectives and enhance inventory management.Design/methodology/approachThis research applies a multi-methodological approach and develops a framework that integrates discrete event simulation (DES), analytic hierarchy process (AHP) and data envelopment analysis (DEA) techniques to define the most favourable replenishment policy using non-financial measures.FindingsThe integration framework performs well as illustrated in the numerical example; outcomes from the framework are comparable to those generated using a traditional, financial measures-based, approach. This research demonstrates that it is feasible to adopt non-financial performance measures to define a replenishment policy and evaluate performance.Originality/valueThe framework, thus, prioritises non-financial measures and addresses issues of lacking information sharing and employee involvement to enhance hospitals' performance while minimising costs. The non-financial measures improve cross-functional communication while supporting simpler transformations from high-level strategies to daily operational targets.
A nanobody targeting the LIN28 Yu, Chunxiao; Wang, Longfei; Rowe, R. Grant ...
Proceedings of the National Academy of Sciences - PNAS,
03/2020, Letnik:
117, Številka:
9
Journal Article
Recenzirano
Odprti dostop
The LIN28:pre-let-7:TUTase ternary complex regulates pluripotency and oncogenesis by controlling processing of the let-7 family of microRNAs. The complex oligouridylates the 3′ ends of pre-let-7 ...molecules, leading to their degradation via the DIS3L2 exonuclease. Previous studies suggest that components of this complex are potential therapeutic targets in malignancies that aberrantly express LIN28. In this study we developed a functional epitope selection approach to identify nanobody inhibitors of the LIN28:pre-let-7:TUT4 complex. We demonstrate that one of the identified nanobodies, Nb-S2A4, targets the 106-residue LIN28:let-7 interaction (LLI) fragment of TUT4. Nb-S2A4 can effectively inhibit oligouridylation andmonouridylation of pre-let-7g in vitro. Expressing Nb-S2A4 allows maturation of the let-7 species in cells expressing LIN28, highlighting the therapeutic potential of targeting the LLI fragment.
Background & Aims Biliary atresia (BA) is a rare and most severe cholestatic disease in neonates, but the pathogenic mechanisms are unknown. Through a previous genome wide association study (GWAS) on ...Han Chinese, we discovered association of the 10q24.2 region encompassing ADD3 and XPNPEP1 genes, which was replicated in Chinese and Thai populations. This study aims to fully characterize the genetic architecture at 10q24.2 and to reveal the link between the genetic variants and BA. Methods We genotyped 107 single nucleotide polymorphisms (SNPs) in 10q24.2 in 339 Han Chinese patients and 401 matched controls using Sequenom. Exhaustive follow-up studies of the association signals were performed. Results The combined BA-association p -value of the GWAS SNP (rs17095355) achieved 6.06 × 10−10 . Further, we revealed the common risk haplotype encompassing 5 tagging-SNPs, capturing the risk-predisposing alleles in 10q24.2 p = 5.32 × 10−11 ; odds ratio, OR: 2.38; confidence interval, CI: (2.14-2.62). Through Sanger sequencing, no deleterious rare variants (RVs) residing in the risk haplotype were found, dismissing the theory of “synthetic” association. Moreover, in bioinformatics and in vivo genotype-expression investigations, the BA-associated potentially regulatory SNPs correlated with ADD3 gene expression (n = 36; p = 0.0030). Remarkably, the risk haplotype frequency coincides with BA incidences in the population, and, positive selection (favoring the derived alleles that arose from mutations) was evident at the ADD3 locus, suggesting a possible role for the BA-associated common variants in shaping the general population diversity. Conclusions Common genetic variants in 10q24.2 can alter BA risk by regulating ADD3 expression levels in the liver, and may exert an effect on disease epidemiology and on the general population.
Introduction: Bacteremia is a common but life-threatening infectious disease. However, a well-defined rule to assess patient risk of bacteremia and the urgency of blood culture is lacking. The aim of ...this study is to establish a predictive model for bacteremia in septic patients using available big data in the emergency department (ED) through logistic regression and other machine learning (ML) methods. Material and Methods: We conducted a retrospective cohort study at the ED of National Cheng Kung University Hospital in Taiwan from January 2015 to December 2019. ED adults (≥18 years old) with systemic inflammatory response syndrome and receiving blood cultures during the ED stay were included. Models I and II were established based on logistic regression, both of which were derived from support vector machine (SVM) and random forest (RF). Net reclassification index was used to determine which model was superior. Results: During the study period, 437,969 patients visited the study ED, and 40,395 patients were enrolled. Patients diagnosed with bacteremia accounted for 7.7% of the cohort. The area under the receiver operating curve (AUROC) in models I and II was 0.729 (95% CI, 0.718–0.740) and 0.731 (95% CI, 0.721–0.742), with Akaike information criterion (AIC) of 16,840 and 16,803, respectively. The performance of model II was superior to that of model I. The AUROC values of models III and IV in the validation dataset were 0.730 (95% CI, 0.713–0.747) and 0.705 (0.688–0.722), respectively. There is no statistical evidence to support that the performance of the model created with logistic regression is superior to those created by SVM and RF. Discussion: The advantage of the SVM or RF model is that the prediction model is more elastic and not limited to a linear relationship. The advantage of the LR model is that it is easy to explain the influence of the independent variable on the response variable. These models could help medical staff identify high-risk patients and prevent unnecessary antibiotic use. The performance of SVM and RF was not inferior to that of logistic regression. Conclusions: We established models that provide discrimination in predicting bacteremia among patients with sepsis. The reported results could inspire researchers to adopt ML in their development of prediction algorithms.
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