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Article
Publication date: 25 May 2018

Qiong Tao and Yingjiao Xu

Fashion subscription service is a newly emerged retailing model that provides an innovative way of shopping to meet consumers’ fashion needs. From the perspective of innovation…

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Abstract

Purpose

Fashion subscription service is a newly emerged retailing model that provides an innovative way of shopping to meet consumers’ fashion needs. From the perspective of innovation adoption, the purpose of this paper is to provide an insight of consumers’ perceptions as well as adoption intention of this innovative retailing format.

Design/methodology/approach

This research is qualitative in nature, utilizing focus group study approach. In this paper, content analysis was applied to analyze the data.

Findings

While possessing varying degrees of knowledge about fashion subscription retailing, the participants shared the following perceptions of relative advantages, including convenience, personalization, consumer excitement, opportunities to try new styles, and opportunity to better manage their apparel budget. Concerns mainly focused on missing social shopping experiences and the hassle in the cancellation process. The overall adoption intention was high.

Research limitations/implications

Due to the nature of this research, the sample size was limited and results may not be generalized. This research paid less attention to individual differences, in terms of demographic and psychographic characteristics.

Practical implications

Future marketing could focus more on educating consumers about the attributes of the services they provide. Retailers can strategically leverage the positively perceived advantages in their marketing communications to enhance consumers’ adoption intention of their services.

Originality/value

The paper fills a gap in the literature on consumer behavior toward fashion subscription retailing and sheds light for companies in their endeavors to excel in this new retailing venue.

Details

Journal of Fashion Marketing and Management: An International Journal, vol. 22 no. 4
Type: Research Article
ISSN: 1361-2026

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Article
Publication date: 11 November 2024

Qiwei Zhou, Qiong Wu, Yuyuan Sun and Kathryn Cormican

Shared leadership has received significant empirical and theoretical attention in the project management literature. However, a dearth of studies reveals how shared leadership…

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Abstract

Purpose

Shared leadership has received significant empirical and theoretical attention in the project management literature. However, a dearth of studies reveals how shared leadership promotes project performance. Drawing on the theory of conservation of resources, this research proposes a serial mediation model that investigates the relationship between shared leadership and project performance through team failure learning and team resilience.

Design/methodology/approach

A field study was conducted that surveyed 79 project teams in various industries (comprising 380 project team members and 79 project managers) using a multisource, time-lagged survey design.

Findings

Our findings show that shared leadership has a positive impact on project performance. More importantly, team failure learning and team resilience play sequential mediating roles in the relationship between shared leadership and project performance.

Practical implications

This research offers new ways for project managers to manage project performance effectively. Project managers are encouraged to recognize the benefits of shared leadership. To do this, they should facilitate team failure learning and improve team resilience, which serves to boost project performance.

Originality/value

This research provides a novel perspective on how shared leadership influences project performance. To the best of our knowledge, we are among the first to explore the serial mediating effects of team failure learning and team resilience on the relationship between shared leadership and project performance.

Details

International Journal of Managing Projects in Business, vol. 18 no. 1
Type: Research Article
ISSN: 1753-8378

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Article
Publication date: 4 June 2018

Sujata Swain and Rajdeep Niyogi

This study aims to discuss a context-aware system, SmartMedicist, which can recommend an alternative medicine from a set of available medicines present at a patient’s home for an…

231

Abstract

Purpose

This study aims to discuss a context-aware system, SmartMedicist, which can recommend an alternative medicine from a set of available medicines present at a patient’s home for an unavailable medicine. The system is applied to the chronic disease patients only. The system requires only a smartphone, and provides a reminder to the patient to take medicine at appropriate times and to procure medicines from drug store. The system discusses the output method for the physically challenged patient. Although there are existing systems that can remind a patient for taking medicines, the authors are not aware of any such system that has the capability to recommend an alternative medicine for the prescribed medicine.

Design/methodology/approach

The study developed a pharmacology knowledge base that consists of a representation of a set of diseases, according to family, type and medicines, in a k-ary tree. An alternative medicine is recommended based on the set of available medicines and knowledge base.

Findings

We considered four diseases: Hypertension, Gastritis, Alzheimer’s disease, and Parkinson; and performed several experiments for each disease for the different number of available medicines. The execution time to find an alternative medicine (if any) in each case is around four seconds.

Originality/value

The proposed system is cost effective and affordable for most families in India. Although the proposed system is not a substitute of a doctor, this system will enhance the safety golden period for a patient to consult a doctor in the emergency exhaustion of the prescribed medicines.

Details

International Journal of Pervasive Computing and Communications, vol. 14 no. 2
Type: Research Article
ISSN: 1742-7371

Keywords

Available. Content available
Book part
Publication date: 23 September 2019

Yi-Ming Wei, Qiao-Mei Liang, Gang Wu and Hua Liao

Abstract

Details

Energy Economics
Type: Book
ISBN: 978-1-83867-294-2

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Article
Publication date: 1 April 2022

Qiong Jia, Ying Zhu, Rui Xu, Yubin Zhang and Yihua Zhao

Abundant studies of outpatient visits apply traditional recurrent neural network (RNN) approaches; more recent methods, such as the deep long short-term memory (DLSTM) model, have…

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Abstract

Purpose

Abundant studies of outpatient visits apply traditional recurrent neural network (RNN) approaches; more recent methods, such as the deep long short-term memory (DLSTM) model, have yet to be implemented in efforts to forecast key hospital data. Therefore, the current study aims to reports on an application of the DLSTM model to forecast multiple streams of healthcare data.

Design/methodology/approach

As the most advanced machine learning (ML) method, static and dynamic DLSTM models aim to forecast time-series data, such as daily patient visits. With a comparative analysis conducted in a high-level, urban Chinese hospital, this study tests the proposed DLSTM model against several widely used time-series analyses as reference models.

Findings

The empirical results show that the static DLSTM approach outperforms seasonal autoregressive integrated moving averages (SARIMA), single and multiple RNN, deep gated recurrent units (DGRU), traditional long short-term memory (LSTM) and dynamic DLSTM, with smaller mean absolute, root mean square, mean absolute percentage and root mean square percentage errors (RMSPE). In particular, static DLSTM outperforms all other models for predicting daily patient visits, the number of daily medical examinations and prescriptions.

Practical implications

With these results, hospitals can achieve more precise predictions of outpatient visits, medical examinations and prescriptions, which can inform hospitals' construction plans and increase the efficiency with which the hospitals manage relevant information.

Originality/value

To address a persistent gap in smart hospital and ML literature, this study offers evidence of the best forecasting models with a comparative analysis. The study extends predictive methods for forecasting patient visits, medical examinations and prescriptions and advances insights into smart hospitals by testing a state-of-the-art, deep learning neural network method.

Details

Industrial Management & Data Systems, vol. 122 no. 10
Type: Research Article
ISSN: 0263-5577

Keywords

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Book part
Publication date: 20 July 2012

Lihua Wang

Purpose – Informed by Chinese mothers from four villages, the purpose of this chapter is to address the old issue of feminization of family survival, but situated within the…

Abstract

Purpose – Informed by Chinese mothers from four villages, the purpose of this chapter is to address the old issue of feminization of family survival, but situated within the landscape of neoliberalism. This study investigates the interplay between Chinese patriarchal values and neoliberal ideas that have shaped the Happiness Project – Action to Aid Impoverished Mothers – an official population control program that has been combined with poverty reduction “Action.”

Methodology – This research began in 2001 in Sichuan Province, Southwest China. Over a period of three years I interviewed 48 women who were participants in the Happiness Project.

Findings – The goal of the Happiness Project is to bring “happiness” to poor mothers through the introduction of microcredit, literacy programs, and the improvement of reproductive health. Three maternal aspects of the Happiness Project, as the study indicates, coincide with three particular patriarchal values. These include an official construction of a good mother image, targeting women's bodies as objects of the state's population control, and reinforcing gender stereotypes through market activity. The findings of this research suggest that feminization of family survival coincided with achieving the goal of the Project. Mothers thus have carried a double burden on behalf of the Chinese state and their families: the goals of declining fertility and increasing family prosperity.

Social implications – Based on this outcome, the study not only calls for reevaluating this “women-only” economic development model, but also calls into question whether bringing Chinese women into public production/market activity is a path to women's emancipation under neoliberalism.

Details

Social Production and Reproduction at the Interface of Public and Private Spheres
Type: Book
ISBN: 978-1-78052-875-5

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Article
Publication date: 25 March 2021

Jing Jian Xiao, Chengyang Yan, Piotr Bialowolski and Nilton Porto

The relationship between debt and happiness is an emerging research topic with significant implications for both theory and practice in economics and business. In China, where the…

980

Abstract

Purpose

The relationship between debt and happiness is an emerging research topic with significant implications for both theory and practice in economics and business. In China, where the consumer credit market is at an early stage of development, the topic remains under-investigated and the evidence on the debt–well-being link is scarce. The purpose of this study is to examine the association between debt holding and happiness and the moderating role of income in it.

Design/methodology/approach

Data used in the study were from three waves (2013, 2015 and 2017) of the China Household Finance Survey. Fixed-effect regressions on panel data were used for data analyses.

Findings

The results show that any type of debt holding is negatively associated with happiness. Among seven specific types of debts, four types show negative associations with happiness, which in the order from higher to lower associations, are medical, education, other and housing debt. In addition, negative associations between debt holding and happiness vary among income groups. The results suggest that any debt holding potentially decreases happiness for low- and middle-income consumers only. In addition, holdings of three specific types of debts (medical, education and housing debt) may decrease happiness for both low- and middle-income consumers, and holding two types of debts (business and other debt) may decrease happiness for middle-income consumers only.

Research limitations/implications

Data used in this study originate from one country only. It limits the generalizability of findings to other countries with different institutional backgrounds and different socio-economic characteristics of populations. The results have implications for researchers who study consumer debt behavior and business practitioners who do businesses with Chinese companies and consumers.

Practical implications

China is an emerging economy that is at the early stage of credit market development. The results of this study provide helpful information and insights for business practitioners to explore credit markets and serve credit product clients with various income levels in China.

Social implications

The results of this study are informative for public policies. When introducing credit market-related policies, policymakers should pay attention to people's happiness and to differential welfare effects of holdings of different types of debts and among consumers with various levels of incomes.

Originality/value

Unique contributions of this study include using data from the most recently available waves of the China Household Finance Survey (2013, 2015 and 2017) to study the associations between debt holding and happiness. In addition, the findings of this study enrich the literature of debt and happiness by adding evidence from China, the largest emerging economy in the world, which is helpful for future theory building and business practice on the relationship between debt holding and happiness.

Details

International Journal of Bank Marketing, vol. 39 no. 5
Type: Research Article
ISSN: 0265-2323

Keywords

Available. Open Access. Open Access
Article
Publication date: 15 July 2022

Susanne Leitner-Hanetseder and Othmar M. Lehner

With the help of “self-learning” algorithms and high computing power, companies are transforming Big Data into artificial intelligence (AI)-powered information and gaining…

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Abstract

Purpose

With the help of “self-learning” algorithms and high computing power, companies are transforming Big Data into artificial intelligence (AI)-powered information and gaining economic benefits. AI-powered information and Big Data (simply data henceforth) have quickly become some of the most important strategic resources in the global economy. However, their value is not (yet) formally recognized in financial statements, which leads to a growing gap between book and market values and thus limited decision usefulness of the underlying financial statements. The objective of this paper is to identify ways in which the value of data can be reported to improve decision usefulness.

Design/methodology/approach

Based on the authors' experience as both long-term practitioners and theoretical accounting scholars, the authors conceptualize and draw up a potential data value chain and show the transformation from raw Big Data to business-relevant AI-powered information during its process.

Findings

Analyzing current International Financial Reporting Standards (IFRS) regulations and their applicability, the authors show that current regulations are insufficient to provide useful information on the value of data. Following this, the authors propose a Framework for AI-powered Information and Big Data (FAIIBD) Reporting. This framework also provides insights on the (good) governance of data with the purpose of increasing decision usefulness and connecting to existing frameworks even further. In the conclusion, the authors raise questions concerning this framework that may be worthy of discussion in the scholarly community.

Research limitations/implications

Scholars and practitioners alike are invited to follow up on the conceptual framework from many perspectives.

Practical implications

The framework can serve as a guide towards a better understanding of how to recognize and report AI-powered information and by that (a) limit the valuation gap between book and market value and (b) enhance decision usefulness of financial reporting.

Originality/value

This article proposes a conceptual framework in IFRS to regulators to better deal with the value of AI-powered information and improve the good governance of (Big)data.

Details

Journal of Applied Accounting Research, vol. 24 no. 2
Type: Research Article
ISSN: 0967-5426

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Article
Publication date: 2 January 2025

Modish Kumar and Santosh Kumari

This paper aims to evaluate the available research to identify the factors contributing to the delays in road construction projects. The primary goals of this study are to…

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Abstract

Purpose

This paper aims to evaluate the available research to identify the factors contributing to the delays in road construction projects. The primary goals of this study are to determine the critical elements that cause delays in road projects, and to investigate the appropriate corrective actions suggested to lessen the delays in road projects. The study also assesses the theoretical background, methodology, limitations and future research prospects suggested in relevant research works related to causes for delays in road construction.

Design/methodology/approach

This study adopted systematic literature review in three steps: collecting relevant literature, descriptive analysis and content analysis. This study used keyword analysis and thematic content analysis on some relevant selected studies. NVivo 12 was used for thematic content analysis utilising description-focused coding, the text was thematically analysed, three other software: MS Excel, VOSviewer and Mendeley were also used for analysis in this study.

Findings

The findings revealed that road projects around the world experienced delays and the reasons for delays are many. After the analysis of literature, number of factors causing delays in road projects were identified, which were then divided into seven broad groups using thematic content analysis. The investigation shows that variations in design and inefficient management of project by contractor including inadequate planning and scheduling are the top two factors of delay. The most frequent suggested corrective measure to reduce delay was employing technically competent employees and contractor should conduct thorough survey on his part, rather than just accepting the survey report at face value.

Research limitations/implications

This review paper is addressing the issues related to delays in road construction projects and suggests remedial measure to reduce them. The paper will be useful for researchers, industry professionals, academician and policy makers concerned with the road construction projects. The study conducted the review of selected relevant articles related to causes of delay in road construction projects for qualitative analysis. The research articles using quantitative methods and studies conducted on other types of infrastructure projects were not included; however, findings from this study may be applicable to other construction projects as well.

Practical implications

The findings of this paper are useful in the fields of economy, industry, academia and public policies. The paper thoroughly examined the factors causing delays in highway projects, offering insights for practitioners to identify best practices and mitigation strategies. These findings can guide investment and policy decisions for highway infrastructure projects, promoting a holistic approach to development. Additionally, this paper can help enhance research methods in studies about delays in road infrastructure projects.

Originality/value

The literature review in the paper used a qualitative method. The causes of road project delays, remedial action, context, methodology and theoretical foundation were all examined in this paper.

Details

Journal of Financial Management of Property and Construction, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1366-4387

Keywords

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