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1 – 10 of 441
Article
Publication date: 7 July 2023

Xiaojie Xu and Yun Zhang

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important…

Abstract

Purpose

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

Design/methodology/approach

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

Findings

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

Originality/value

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.

Details

Journal of Financial Management of Property and Construction , vol. 29 no. 1
Type: Research Article
ISSN: 1366-4387

Keywords

Article
Publication date: 14 November 2023

Flavian Emmanuel Sapnken, Mohammed Hamaidi, Mohammad M. Hamed, Abdelhamid Issa Hassane and Jean Gaston Tamba

For some years now, Cameroon has seen a significant increase in its electricity demand, and this need is bound to grow within the next few years owing to the current economic…

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Abstract

Purpose

For some years now, Cameroon has seen a significant increase in its electricity demand, and this need is bound to grow within the next few years owing to the current economic growth and the ambitious projects underway. Therefore, one of the state's priorities is the mastery of electricity demand. In order to get there, it would be helpful to have reliable forecasting tools. This study proposes a novel version of the discrete grey multivariate convolution model (ODGMC(1,N)).

Design/methodology/approach

Specifically, a linear corrective term is added to its structure, parameterisation is done in a way that is consistent to the modelling procedure and the cumulated forecasting function of ODGMC(1,N) is obtained through an iterative technique.

Findings

Results show that ODGMC(1,N) is more stable and can extract the relationships between the system's input variables. To demonstrate and validate the superiority of ODGMC(1,N), a practical example drawn from the projection of electricity demand in Cameroon till 2030 is used. The findings reveal that the proposed model has a higher prediction precision, with 1.74% mean absolute percentage error and 132.16 root mean square error.

Originality/value

These interesting results are due to (1) the stability of ODGMC(1,N) resulting from a good adequacy between parameters estimation and their implementation, (2) the addition of a term that takes into account the linear impact of time t on the model's performance and (3) the removal of irrelevant information from input data by wavelet transform filtration. Thus, the suggested ODGMC is a robust predictive and monitoring tool for tracking the evolution of electricity needs.

Details

Grey Systems: Theory and Application, vol. 14 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

Book part
Publication date: 5 April 2024

Ziwen Gao, Steven F. Lehrer, Tian Xie and Xinyu Zhang

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and…

Abstract

Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.

Open Access
Article
Publication date: 15 January 2024

Christine Prince, Nessrine Omrani and Francesco Schiavone

Research on online user privacy shows that empirical evidence on how privacy literacy relates to users' information privacy empowerment is missing. To fill this gap, this paper…

Abstract

Purpose

Research on online user privacy shows that empirical evidence on how privacy literacy relates to users' information privacy empowerment is missing. To fill this gap, this paper investigated the respective influence of two primary dimensions of online privacy literacy – namely declarative and procedural knowledge – on online users' information privacy empowerment.

Design/methodology/approach

An empirical analysis is conducted using a dataset collected in Europe. This survey was conducted in 2019 among 27,524 representative respondents of the European population.

Findings

The main results show that users' procedural knowledge is positively linked to users' privacy empowerment. The relationship between users' declarative knowledge and users' privacy empowerment is partially supported. While greater awareness about firms and organizations practices in terms of data collections and further uses conditions was found to be significantly associated with increased users' privacy empowerment, unpredictably, results revealed that the awareness about the GDPR and user’s privacy empowerment are negatively associated. The empirical findings reveal also that greater online privacy literacy is associated with heightened users' information privacy empowerment.

Originality/value

While few advanced studies made systematic efforts to measure changes occurred on websites since the GDPR enforcement, it remains unclear, however, how individuals perceive, understand and apply the GDPR rights/guarantees and their likelihood to strengthen users' information privacy control. Therefore, this paper contributes empirically to understanding how online users' privacy literacy shaped by both users' declarative and procedural knowledge is likely to affect users' information privacy empowerment. The study empirically investigates the effectiveness of the GDPR in raising users' information privacy empowerment from user-based perspective. Results stress the importance of greater transparency of data tracking and processing decisions made by online businesses and services to strengthen users' control over information privacy. Study findings also put emphasis on the crucial need for more educational efforts to raise users' awareness about the GDPR rights/guarantees related to data protection. Empirical findings also show that users who are more likely to adopt self-protective approaches to reinforce personal data privacy are more likely to perceive greater control over personal data. A broad implication of this finding for practitioners and E-businesses stresses the need for empowering users with adequate privacy protection tools to ensure more confidential transactions.

Details

Information Technology & People, vol. 37 no. 8
Type: Research Article
ISSN: 0959-3845

Keywords

Book part
Publication date: 26 March 2024

Manpreet Kaur and Shivani Malhan

Purpose: Manufacturing has always been considered a backbone for economic growth. It has been considered an imperative sector in the growth of an economy. This study aims to trace…

Abstract

Purpose: Manufacturing has always been considered a backbone for economic growth. It has been considered an imperative sector in the growth of an economy. This study aims to trace the long-term relationship between gross domestic product (GDP) and manufacturing sector in the context of Indian economy.

Need for the study: According to research, the significance of the manufacturing sector is waning over time. This chapter studies the long-term relationship between the GDP, an indicator of growth, and the manufacturing sector. Over the last few decades, the contribution of manufacturing has been stagnant in the GDP of India.

Methodology: The decadal growth of various sectors in the GDP of India is studied using time series analysis. This study used the data released by the Ministry of Statistics and Programme Implementation (MOSPI) from 1950–1951 to 2013–2014. The long-term relationship between the sector of manufacturing and the GDP is examined through the augmented Dicky–Fuller (ADF) test and auto-regressive distributed lag (ARDL) models.

Findings: The findings suggest that in the Indian scenario, there is no relationship for an extended period between the GDP and the manufacturing sector, which calls for further policy implications.

Practical implications: India, while having the world’s fastest-growing economy, must continue to take steps to attain high growth rates and long-term sustainability by reducing obstacles to the expansion of the service sector in addition to manufacturing. Manufacturing-led services are to be boosted through policy interventions.

Details

The Framework for Resilient Industry: A Holistic Approach for Developing Economies
Type: Book
ISBN: 978-1-83753-735-8

Keywords

Article
Publication date: 27 February 2023

Bhabani Shankar Nayak and Nigel Walton

The paper argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by…

Abstract

Purpose

The paper argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by “platforms” and “big data”. Big data platforms are shaping the processes of production, labour, the price of products and market conditions. “Digital platforms” and “big data” have become an integral part of the processes of production, distribution and exchange relations. These twin pillars are central to the capitalist accumulation processes. The article argues that the classical Marxist theory of capitalist accumulation is inadequate to understand new forms of capitalism and their accumulation processes determined by “platforms” and “big data”.

Design/methodology/approach

As a conceptual paper, this paper follows critical methodological lineages and traditions based on non-linear historical narratives around the conceptualisation, construction and transition of the “Marxist theory of capital accumulation” in the age of platform economy. This paper follows a discourse analysis (Fairclough, 2003) to locate the way in which an artificial intelligence (AI)-led platform economy helps identify and conceptualise new forms of capitalist accumulation. It engages with Jørgensen and Phillips' (2002) contextual and empirical discursive traditions to undertake a qualitative comparative analysis by exploring a broad range of complex factors with case studies and examples from leading firms within the platform economy. Finally, it adopts two steps of “Theory Synthesis and Theory Adaptation” as outlined by Jaakkola (2020) to synthesise, adopt and expand the Marxist theory of capital accumulation under platform capitalism.

Findings

This article identifies new trends and forms of data driven capitalist accumulation processes within the platform capitalism. The findings suggest that an AI led platform economy creates new forms of capitalist accumulation. The article helps to develop theoretical understanding and conceptual frameworks to understand and explain these new forms of capital accumulation.

Originality/value

This study builds upon the limited theorisation on the AI and new capitalist accumulation processes. This article identifies new trends and forms of data driven capitalist accumulation processes within platform capitalism. The article helps to understand digital and platform capitalisms in the lens of digital labour and expands the theory of capitalist accumulation and its new forms in the age of datafication. While critiquing the Marxist theory of capitalist accumulation, the article offers alternative approaches for the future.

Details

Information Technology & People, vol. 37 no. 2
Type: Research Article
ISSN: 0959-3845

Keywords

Book part
Publication date: 8 April 2024

Vojtěch Koňařík, Zuzana Kučerová and Daniel Pakši

Inflation expectations are an important part of the transmission mechanism of the inflation targeting regime. As such, central bankers must study the inflation expectations of…

Abstract

Inflation expectations are an important part of the transmission mechanism of the inflation targeting regime. As such, central bankers must study the inflation expectations of economic agents to anchor them close to the level of the inflation target. However, economic agents are affected by the past and current macroeconomic situation when they form their expectations concerning future inflation. Using survey data on inflation expectations in Czechia, we investigate the macroeconomic determinants of Czech analysts' and managers' inflation expectations. We find that both actual and past inflation have a substantial impact on inflation expectations of the agents surveyed. We also identify backward-looking behaviour among these agents: persistence in inflation expectations of up to two quarters was detected. Moreover, financial analysts formed inflation expectations more in line with economic theory, while company managers evinced expectations similar to those of consumers.

Details

Modeling Economic Growth in Contemporary Czechia
Type: Book
ISBN: 978-1-83753-841-6

Keywords

Article
Publication date: 7 March 2024

Abdul Rahman Zahari and Elinda Esa

The purpose of this study is to determine whether COVID-19 had an impact on the brand equity of the Top 100 global brands in the Americas, European and Asian regions over the…

Abstract

Purpose

The purpose of this study is to determine whether COVID-19 had an impact on the brand equity of the Top 100 global brands in the Americas, European and Asian regions over the three years of assessment (2020–2022).

Design/methodology/approach

A secondary data method (document scanning) was used to gather the study’s data from Brand Finance’s Global 500 annual reports from 2019 to 2022. The data for this study was analysed using the IBM Statistical Package for Social Science (SPSS) Statistics for Windows, Version 26.0. The data were subjected to a descriptive test and one-way analysis of variance.

Findings

The findings showed that most of the Top 100 global brands from the Americas, Europe and Asia experienced little or no impact due to COVID-19. Thus, no significant differences were found to exist among the Top 100 global regional brands due to COVID-19 in the years 2020 and 2021. However, there is a significant difference in 2022 due to its small effect size.

Originality/value

The findings of this paper contribute to brand equity literature and global branding literature in the context of COVID-19. This paper innovatively frames brand equity and provides guidelines to help brands sustain their financial-based brand equity during a worldwide crisis.

Details

Journal of Contemporary Marketing Science, vol. 7 no. 1
Type: Research Article
ISSN: 2516-7480

Keywords

Open Access
Article
Publication date: 16 February 2024

Rafael Ravina-Ripoll, Gustavo Adolfo Díaz-García, Eduardo Ahumada-Tello and Esthela Galván-Vela

This study analyses the concept of happiness management based on the empirical validation of the interactions between emotional wage, organisational justice and happiness at work…

Abstract

Purpose

This study analyses the concept of happiness management based on the empirical validation of the interactions between emotional wage, organisational justice and happiness at work. It complements a holistic view of the management models used in recent corporate governance. This perspective explores the dimension’s emotional wage mediating role and influences on organisational justice and happiness at work. The effect of organisational justice on happiness at work is also analysed.

Design/methodology/approach

A quantitative, cross-sectional, descriptive and correlational study is proposed. A sample of 502 workers in the education sector in Costa Rica was selected. A structural equation model (PLS-SEM) was developed to test the proposed theoretical model. The SPSS-AMOS 23 and SmartPLS 4 computer programs are used for this purpose.

Findings

The results show that emotional wage has a positive impact on happiness at work and that it mediates positively between organisational justice and happiness at work. Developing organisational policies to include these variables as necessary resources for corporate governance is recommended.

Research limitations/implications

The first limitation of this study is due to the type of sampling, which was purposive. The kind of population and the time of execution of this study were determining factors when deciding on the mode of application of the instrument. However, an attempt to reduce the bias associated with this element could be made by expanding the sample to as many respondents as possible. The second limitation was that the data were collected within a specific time frame. Longitudinal studies address Thcould. The third limitation stems from the scarcity of literature on happiness management. In this regard, this type of research currently needs to be explored in emerging economies. It makes it difficult to determine whether the empirical results obtained in this paper can be generalised to other territories in the global village. Moreover, the last limitation is that the authors of this research have only explored the moderating role of emotional pay in the relationship between the dimensions of organisational justice and happiness at work. It would be interesting to consider other mediating variables to have a clearer picture of the organisational justice–happiness at work construct from the happiness management approach.

Practical implications

As already indicated throughout this research, emotional wage, organisational justice and happiness at work are constructs that positively drive employee satisfaction, motivation and well-being. Human talent management strategies undertaken by organisations should encourage the adaptation of actions that stimulate employees' quality of life, corporate social responsibility and ethical management practices to be more competitive in today’s markets. It requires implementing the dynamic management models that provide internal customers with a high sense of belonging, job satisfaction and commitment to their professional performance. In other words, this will require robust leadership styles and corporate cultures that stimulate employee creativity, loyalty and innovation. For this reason, management of organisations must implement human resources policies to attract and retain creative talent through happy leadership. It requires, among other things that the philosophy of happiness management becomes a critical strategic resource for companies to promote nonfinancial benefits for employees, including emotional wage (Ruiz-Rodríguez et al., 2023).

Social implications

In the current business environment, there has been a transformation in leadership styles, motivation and the development of a sense of belonging in organisations' human capital. Based on this trend, the study of happiness management becomes a social strategy to improve the conditions, in which the organisations compete to attract highly demanded human capital. It is why this research contributes elements that have an impact on citizenship by proposing the management models based on happiness at work and quality of life.

Originality/value

This study adds to the happiness management literature by including emotional wage, organisational justice and happiness at work in human resources and strategic management. It also contributes to the academic debate on the need to formulate organisational cultures that empower workers in their professional performance based on happiness and positive emotions.

Details

Journal of Management Development, vol. 43 no. 2
Type: Research Article
ISSN: 0262-1711

Keywords

Open Access
Article
Publication date: 20 November 2023

Devesh Singh

This study aims to examine foreign direct investment (FDI) factors and develops a rational framework for FDI inflow in Western European countries such as France, Germany, the…

Abstract

Purpose

This study aims to examine foreign direct investment (FDI) factors and develops a rational framework for FDI inflow in Western European countries such as France, Germany, the Netherlands, Switzerland, Belgium and Austria.

Design/methodology/approach

Data for this study were collected from the World development indicators (WDI) database from 1995 to 2018. Factors such as economic growth, pollution, trade, domestic capital investment, gross value-added and the financial stability of the country that influence FDI decisions were selected through empirical literature. A framework was developed using interpretable machine learning (IML), decision trees and three-stage least squares simultaneous equation methods for FDI inflow in Western Europe.

Findings

The findings of this study show that there is a difference between the most important and trusted factors for FDI inflow. Additionally, this study shows that machine learning (ML) models can perform better than conventional linear regression models.

Research limitations/implications

This research has several limitations. Ideally, classification accuracies should be higher, and the current scope of this research is limited to examining the performance of FDI determinants within Western Europe.

Practical implications

Through this framework, the national government can understand how investors make their capital allocation decisions in their country. The framework developed in this study can help policymakers better understand the rationality of FDI inflows.

Originality/value

An IML framework has not been developed in prior studies to analyze FDI inflows. Additionally, the author demonstrates the applicability of the IML framework for estimating FDI inflows in Western Europe.

Details

Journal of Economics, Finance and Administrative Science, vol. 29 no. 57
Type: Research Article
ISSN: 2077-1886

Keywords

1 – 10 of 441