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Article
Publication date: 28 February 2019

Bernardí Cabrer-Borrás, Paz Rico Belda and Dolores Botella Carrubi

The purpose of this paper is to analyse the determinants of the survival of Spanish companies.

Abstract

Purpose

The purpose of this paper is to analyse the determinants of the survival of Spanish companies.

Design/methodology/approach

Two approaches are used and they are complementary. The first approach analyses the determinants of survival probability. For this purpose, a binary choice model is built and estimated using a sample of companies from the main economic sectors taken from the SABI database. Likewise, the Blinder–Oaxaca decomposition is applied to quantify the difference between companies with employees and without employees and the proportion of this difference that owes to observed factors or unobserved factors. Finally, the second approach is a survival analysis carried out through the Cox proportional hazard model that identifies the determinants of the duration of business activity.

Findings

The results of the empirical analysis show that companies without employees present less favourable conditions for survival at all stages of their evolution than companies with employees.

Originality/value

The contribution of this study to the empirical literature consists in analysing the difference between companies with and without employees. Due to the structure of Spanish companies, this aspect and the determinants of such difference are essential for policymakers to increase the survival for companies.

Details

International Journal of Entrepreneurial Behavior & Research, vol. 25 no. 8
Type: Research Article
ISSN: 1355-2554

Keywords

Article
Publication date: 16 February 2018

Paz Rico and Bernardí Cabrer-Borrás

The purpose of this paper is to analyse the gender differences of self-employment in Spain.

Abstract

Purpose

The purpose of this paper is to analyse the gender differences of self-employment in Spain.

Design/methodology/approach

A binary choice model is specified and estimated, using information from the Continuous Working Life Sample drawn from the registers of the Spanish Social Security. Moreover, the differences in self-employment between men and women are also analysed, through the decomposition proposed by Yun (2004).

Findings

The results indicate that the differences between both groups in the probability of being entrepreneurs stem from unobservable factors. The difference explained by the unobservable component is 84.12 per cent, whereas the rest, 15.88 per cent, is explained by the characteristics component. The explanatory factors of being an entrepreneur affect men and women in the same way, but to a different extent, explained mainly by factors related to gender.

Originality/value

This paper sets out to identify whether there are gender differences in the probability of becoming self-employed and, if there are, to quantify what part of the difference in entrepreneurship between men and women is explained by the characteristics of each gender group and what part is because of unobservable factors. From the perspective of the public authority, knowing the determinants that explain why the entrepreneurial activity is different depending on gender is fundamental in being able to reduce the entrepreneurial gap between men and women.

Details

International Journal of Gender and Entrepreneurship, vol. 10 no. 1
Type: Research Article
ISSN: 1756-6266

Keywords

Open Access
Article
Publication date: 13 February 2019

Paz Rico and Bernardí Cabrer-Borrás

The purpose of this paper is to analyse if the divergences in the economic growth of the Spanish regions are a result of sectoral differences, company size or technological level…

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Abstract

Purpose

The purpose of this paper is to analyse if the divergences in the economic growth of the Spanish regions are a result of sectoral differences, company size or technological level of the new firms that emerge in the market.

Design/methodology/approach

For this purpose, a model is specified and estimated in which the total factor productivity of Spanish regions is explained by business dynamics, innovation, human capital and the level of entrepreneurship in each region.

Findings

The results obtained lead the authors to conclude that entrepreneurship understood as both the creation of new firms and entrepreneurial activity, have a positive effect on productive efficiency and can explain the differences in the economic growth of the regions. In addition, the stock of human capital and the promotion of innovation act as catalysts for the productive efficiency of the regions. However, the results show that it is not enough to generate new firms to boost economic growth; these businesses must also be oriented towards sectors that promote technological innovation and with the objective to reach an adequate size.

Originality/value

Empirical studies use either the creation of new firms or the index of entrepreneurial activity as alternative measures of entrepreneurship. In this research, however, both variables are considered together. Specifically, the creation of new companies is used as a measure of regional business dynamics, and the entrepreneurial activity index, provided by the Global Entrepreneurship Monitor, as a measure of regional entrepreneurship. The main novelty of this paper’s approach is that it considers different types of entrepreneurial capital in considering productive sector, size and technological level of the new companies.

Details

European Journal of Management and Business Economics, vol. 28 no. 2
Type: Research Article
ISSN: 2444-8494

Keywords

Article
Publication date: 3 May 2011

Robert W. Nason

The purpose of this paper is to explore the genesis of the first Macro‐Marketing Seminar and to review the institutionalization of macromarketing which resulted from it.

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Abstract

Purpose

The purpose of this paper is to explore the genesis of the first Macro‐Marketing Seminar and to review the institutionalization of macromarketing which resulted from it.

Design/methodology/approach

The paper briefly reviews the history of macromarketing, the changes in society and marketing thought, and the seminal research which led to the first Macro‐Marketing Seminar.

Findings

Early macromarketing research was supplanted by a managerial marketing focus in mid‐twentieth century while at the same time society was awakening to the interconnections between human behavior and a broad range of societal problems. The early marketing theory seminars provided a template for the first Macro‐Marketing Seminar.

Originality/value

The paper explains the resurgence of macromarketing which from that first pivotal Macro‐Marketing Seminar has blossomed into a multifaceted and institutionalized area of study.

Details

Journal of Historical Research in Marketing, vol. 3 no. 2
Type: Research Article
ISSN: 1755-750X

Keywords

Article
Publication date: 21 November 2016

Daniel Arturo Cernas Ortiz and Mark A. Davis

This paper aims to examine the influence of future and past negative time perspectives on job satisfaction and organizational commitment. The effect of national culture (Mexico…

Abstract

Purpose

This paper aims to examine the influence of future and past negative time perspectives on job satisfaction and organizational commitment. The effect of national culture (Mexico versus the USA) as a moderator of the above baseline relationships is also analyzed.

Design/methodology/approach

The research model is tested using survey data drawn from a sample of 287 Mexican and 274 US MBA students (N = 561). Regression analyses were used to test the hypotheses.

Findings

Future time perspective has a positive relationship with job satisfaction and organizational commitment. Past negative time perspective has a negative association with both job attitudes. The effect of future time perspective on job satisfaction was significantly stronger in Mexico than in the USA. No other significant differences between the countries were found in terms of the time perspective and job attitudes association.

Practical implications

The results have implications for managing dispositions that affect work-related attitudes and behaviors with consequences for organizational effectiveness.

Originality/value

The findings suggest that time perspective affects job attitudes. Further, they also suggest that the interplay between future time perspective and culture influences job satisfaction.

Details

Management Research: Journal of the Iberoamerican Academy of Management, vol. 14 no. 3
Type: Research Article
ISSN: 1536-5433

Keywords

Article
Publication date: 23 June 2022

Kerim Koc, Ömer Ekmekcioğlu and Asli Pelin Gurgun

Central to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management…

Abstract

Purpose

Central to the entire discipline of construction safety management is the concept of construction accidents. Although distinctive progress has been made in safety management applications over the last decades, construction industry still accounts for a considerable percentage of all workplace fatalities across the world. This study aims to predict occupational accident outcomes based on national data using machine learning (ML) methods coupled with several resampling strategies.

Design/methodology/approach

Occupational accident dataset recorded in Turkey was collected. To deal with the class imbalance issue between the number of nonfatal and fatal accidents, the dataset was pre-processed with random under-sampling (RUS), random over-sampling (ROS) and synthetic minority over-sampling technique (SMOTE). In addition, random forest (RF), Naïve Bayes (NB), K-Nearest neighbor (KNN) and artificial neural networks (ANNs) were employed as ML methods to predict accident outcomes.

Findings

The results highlighted that the RF outperformed other methods when the dataset was preprocessed with RUS. The permutation importance results obtained through the RF exhibited that the number of past accidents in the company, worker's age, material used, number of workers in the company, accident year, and time of the accident were the most significant attributes.

Practical implications

The proposed framework can be used in construction sites on a monthly-basis to detect workers who have a high probability to experience fatal accidents, which can be a valuable decision-making input for safety professionals to reduce the number of fatal accidents.

Social implications

Practitioners and occupational health and safety (OHS) departments of construction firms can focus on the most important attributes identified by analysis results to enhance the workers' quality of life and well-being.

Originality/value

The literature on accident outcome predictions is limited in terms of dealing with imbalanced dataset through integrated resampling techniques and ML methods in the construction safety domain. A novel utilization plan was proposed and enhanced by the analysis results.

Details

Engineering, Construction and Architectural Management, vol. 30 no. 9
Type: Research Article
ISSN: 0969-9988

Keywords

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: 3 November 2023

Xiaojie Xu and Yun Zhang

The Chinese housing market has gone through rapid growth during the past decade, and house price forecasting has evolved to be a significant issue that draws enormous attention…

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Abstract

Purpose

The Chinese housing market has gone through rapid growth during the past decade, and house price forecasting has evolved to be a significant issue that draws enormous attention from investors, policy makers and researchers. This study investigates neural networks for composite property price index forecasting from ten major Chinese cities for the period of July 2005–April 2021.

Design/methodology/approach

The goal is to build simple and accurate neural network models that contribute to pure technical forecasts of composite property prices. To facilitate the analysis, the authors consider different model settings across algorithms, delays, hidden neurons and data spitting ratios.

Findings

The authors arrive at a pretty simple neural network with six delays and three hidden neurons, which generates rather stable performance of average relative root mean square errors across the ten cities below 1% for the training, validation and testing phases.

Originality/value

Results here could be utilized on a standalone basis or combined with fundamental forecasts to help form perspectives of composite property price trends and conduct policy analysis.

Details

Property Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-7472

Keywords

Article
Publication date: 15 November 2021

Xiaojie Xu and Yun Zhang

Chinese housing market has been growing fast during the past decade, and price-related forecasting has turned to be an important issue to various market participants, including…

321

Abstract

Purpose

Chinese housing market has been growing fast during the past decade, and price-related forecasting has turned to be an important issue to various market participants, including the people, investors and policy makers. Here, the authors approach this issue by researching neural networks for rent index forecasting from 10 major cities for March 2012 to May 2020. The authors aim at building simple and accurate neural networks to contribute to pure technical forecasting of the Chinese rental housing market.

Design/methodology/approach

To facilitate the analysis, the authors examine different model settings over the algorithm, delay, hidden neuron and data spitting ratio.

Findings

The authors reach a rather simple neural network with six delays and two hidden neurons, which leads to stable performance of 1.4% average relative root mean square error across the ten cities for the training, validation and testing phases.

Originality/value

The results might be used on a standalone basis or combined with fundamental forecasting to form perspectives of rent price trends and conduct policy analysis.

Details

Journal of Economic Studies, vol. 49 no. 8
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 1 January 1980

Juan R. Freudenthal

“A knowledge of different literatures is the best way to free one's self from the tyranny of any of them.” Jose Marti, Cuban writer, poet and statesman.

Abstract

“A knowledge of different literatures is the best way to free one's self from the tyranny of any of them.” Jose Marti, Cuban writer, poet and statesman.

Details

Collection Building, vol. 2 no. 1
Type: Research Article
ISSN: 0160-4953

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