Search results

1 – 10 of over 9000
Article
Publication date: 3 January 2019

Joko Mariyono

The purpose of this paper is to analyse factors that determine farmers’ intention to commercialise vegetable-based agribusiness ventures in rural areas and assess the effect of…

Abstract

Purpose

The purpose of this paper is to analyse factors that determine farmers’ intention to commercialise vegetable-based agribusiness ventures in rural areas and assess the effect of commercialisation on farmers’ income.

Design/methodology/approach

The study used a regression approach. Market participation and farmers’ income were hypothesised to be dependent on other external factors. This study employed data compiled from a quantitative survey of 357 farm households located in four major vegetable producing regions of rural East Java and Bali, Indonesia.

Findings

Results indicate that household attributes, business environment, supporting facilities and farm characteristics determined farmers to commercialise vegetable farming. Access to credit, seed technology and farm site played high contribution to the market participation. Ultimately, commercial vegetable farming provides an economic advantage regarding increased income. Land fragmentation and status of landholding were identified to influence the net revenue of vegetable farming.

Research limitations/implications

This study has a limitation concerning the number of samples and the availability of data and information. The number of samples is 357 which is about 4 per cent of the total population.

Practical implications

Establishment of vegetable agribusiness terminals with all market infrastructures, adequate access to market information, credit and human capital investment through training and extension services are also required, will boost market participation. Re-structuring land ownership might be the best step to augment farmers’ income, through consolidation of fragmented fertile lands devoted to intensive vegetable farming.

Originality/value

This study was purposely conducted in rural areas where there were subsistence farmers, as this is to improve farmers’ income by commercialising vegetable crops. A novel feature of this finding is the role of access to credit in the commercialisation of vegetable farming and the impact of landholding status on the profitability of intensive farming of high-valued vegetables.

Article
Publication date: 30 November 2020

Jan Jakub Szczygielski, Leon Brümmer and Hendrik Petrus Wolmarans

This study aims to investigate the impact of the macroeconomic environment on South African industrial sector returns.

Abstract

Purpose

This study aims to investigate the impact of the macroeconomic environment on South African industrial sector returns.

Design/methodology/approach

Using standardized coefficients derived from time-series factor models, the authors quantify the impact of macroeconomic influences on industrial sector returns. The authors analyze the structure of the resultant residual correlation matrices to establish the level of factor omission and apply a factor analytic augmentation to arrive at a specification that is free of omitted common factors.

Findings

The authors find that global influences are the most important drivers of returns and that industrial sectors are highly integrated with the global economy. The authors show that specifications that comprise only macroeconomic factors and proxies for omitted factors in the form of residual market factors are likely to be underspecified. This study demonstrates that a factor analytic augmentation is an effective approach to ensuring an adequately specified model.

Research limitations/implications

The findings have a number of implications that are of interest to investors, econometricians and researchers. While the study focusses on a single market, the South African stock market, as represented by the Johannesburg Stock Exchange (JSE), it is a highly developed and globally integrated market. In terms of market capitalization, it exceeds the Madrid Stock Exchange, the Taiwan Stock Exchange and the BM&F Bovespa. Yet, a limited number of studies investigate the macroeconomic drivers of the South African stock market.

Practical implications

Investors should be aware that while the South African domestic environment, especially political risk, has an impact on returns, global influences are the greatest determinants of returns. No industrial sectors are insulated from global influences and this limits the potential for diversification. This study suggests an alternative set of macroeconomic factors that may be used in further analysis and asset pricing studies. From an econometric perspective, this study demonstrates the usefulness of a factor analytic augmentation as a solution to factor omission in models that use macroeconomic factors to proxy for systematic influences that describe asset prices.

Originality/value

The contribution lies in providing insight into a large and well-developed yet understudied financial market, the South African stock market. This study considers a much broader set of macroeconomic factors than prior studies. A methodological contribution is made by estimating and interpreting standardized coefficients to discriminate between the impact of domestically and internationally driven factors. This study shows that should coefficients not be standardized, inferences relating to the relative importance of factors will differ. Finally, the authors unify an approach of using pre-specified factors with a factor analytic approach to address factor omission and to ensure a valid and readily interpretable specification.

Article
Publication date: 6 September 2013

Jorge Francisco Lengler, Carlos M.P. Sousa and Catarina Marques

Despite some attempts to integrate the market orientation construct into the international marketing area, most conceptual and empirical studies have been conducted in the context…

1885

Abstract

Purpose

Despite some attempts to integrate the market orientation construct into the international marketing area, most conceptual and empirical studies have been conducted in the context of domestic operations. In addition, few studies have examined the quadratic effects of customer and competitor orientation on export performance. To address this gap in the literature we test a model that examines whether customer and competitor orientation have linear or quadratic relationships with export performance. We also investigate if competitive intensity moderates the linear and quadratic relationships between customer and competitor orientation and export profit.

Design/methodology/approach

The hypotheses are tested using survey data collected from 197 Brazilian export firms. Structural equation modeling was conducted to test the hypothesized relationships and to validate the proposed conceptual model.

Findings

Empirical evidence reveals that, while customer orientation has a U‐shaped relationship with export sales, the competitor orientation–export profit relationship is linear. Our results also provide evidence that the positive quadratic relationship between customer orientation and export profit is mediated by export sales. Contrary to expectations, the results also indicate that none of the linear or quadratic relationships investigated in the model are moderated by competitive intensity.

Originality/value

We test a model in an export context that examines whether the relationships between the separate components of market orientation and export performance are linear or quadratic. We also contribute to the literature by examining these relationships in the context of a developing country, namely Brazil.

Details

International Marketing Review, vol. 30 no. 5
Type: Research Article
ISSN: 0265-1335

Keywords

Book part
Publication date: 29 August 2007

J. Myles Shaver

As a field, we should put more emphasis on interpreting the magnitude of coefficient estimates rather than only assessing statistical significance. To support this claim, I…

Abstract

As a field, we should put more emphasis on interpreting the magnitude of coefficient estimates rather than only assessing statistical significance. To support this claim, I demonstrate how focusing only on statistical significance can lead to incorrect and incomplete conclusions in many common applications of the linear regression model. Moreover, I demonstrate why interpreting coefficient estimates in common non-linear estimators (e.g., probit, logit, Poisson, and negative binomial estimators) requires additional care compared to the linear regression model.

Details

Research Methodology in Strategy and Management
Type: Book
ISBN: 978-0-7623-1404-1

Article
Publication date: 29 August 2019

Vivekanand Venkataraman, Syed Usmanulla, Appaiah Sonnappa, Pratiksha Sadashiv, Suhaib Soofi Mohammed and Sundaresh S. Narayanan

The purpose of this paper is to identify significant factors of environmental variables and pollutants that have an effect on PM2.5 through wavelet and regression analysis.

Abstract

Purpose

The purpose of this paper is to identify significant factors of environmental variables and pollutants that have an effect on PM2.5 through wavelet and regression analysis.

Design/methodology/approach

In order to provide stable data set for regression analysis, multiresolution analysis using wavelets is conducted. For the sampled data, multicollinearity among the independent variables is removed by using principal component analysis and multiple linear regression analysis is conducted using PM2.5 as a dependent variable.

Findings

It is found that few pollutants such as NO2, NOx, SO2, benzene and environmental factors such as ambient temperature, solar radiation and wind direction affect PM2.5. The regression model developed has high R2 value of 91.9 percent, and the residues are stationary and not correlated indicating a sound model.

Research limitations/implications

The research provides a framework for extracting stationary data and other important features such as change points in mean and variance, using the sample data for regression analysis. The work needs to be extended across all areas in India and for various other stationary data sets there can be different factors affecting PM2.5.

Practical implications

Control measures such as control charts can be implemented for significant factors.

Social implications

Rules and regulations can be made more stringent on the factors.

Originality/value

The originality of this paper lies in the integration of wavelets with regression analysis for air pollution data.

Details

International Journal of Quality & Reliability Management, vol. 36 no. 10
Type: Research Article
ISSN: 0265-671X

Keywords

Open Access
Article
Publication date: 17 January 2020

Erkki Kalervo Laitinen

The purpose of this study is to introduce a matching function approach to analyze matching in financial reporting.

7235

Abstract

Purpose

The purpose of this study is to introduce a matching function approach to analyze matching in financial reporting.

Design/methodology/approach

The matching function is first analyzed analytically. It is specified as a multiplicative Cobb-Douglas-type function of three categories of expenses (labor expense, material expense and depreciation). The specified matching function is solved by the generalized reduced gradient method (GRG) for 10-year time series from 8,226 Finnish firms. The coefficient of determination of the logarithmic model (CODL) is compared with the linear revenue-expense correlation coefficient (REC) that is generally used in previous studies.

Findings

Empirical evidence showed that REC is outperformed by CODL. CODL was found independent of or weakly negatively dependent on the matching elasticity of labor expense, positively dependent on the material expense elasticity and negatively dependent on depreciation elasticity. Therefore, the differences in matching accuracy between industries emphasizing different expense categories are significant.

Research limitations/implications

The matching function is a general approach to assess the matching accuracy but it is in this study specified multiplicatively for three categories of expenses. Moreover, only one algorithm is tested in the empirical estimation of the function. The analysis is concentrated on ten-year time-series of a limited sample of Finnish firms.

Practical implications

The matching function approach provides a large set of important information for considering the matching process in practice. It can prove a useful method also to accounting standard-setters and other specialists such as managers, consultants and auditors.

Originality/value

This study is the first study to apply the new matching function approach.

Details

Journal of Financial Reporting and Accounting, vol. 18 no. 1
Type: Research Article
ISSN: 1985-2517

Keywords

Open Access
Article
Publication date: 22 November 2022

Kedong Yin, Yun Cao, Shiwei Zhou and Xinman Lv

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems…

Abstract

Purpose

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Design/methodology/approach

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Findings

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

Originality/value

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

Details

Marine Economics and Management, vol. 5 no. 2
Type: Research Article
ISSN: 2516-158X

Keywords

Article
Publication date: 1 June 2000

A. Savini

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community…

1128

Abstract

Gives introductory remarks about chapter 1 of this group of 31 papers, from ISEF 1999 Proceedings, in the methodologies for field analysis, in the electromagnetic community. Observes that computer package implementation theory contributes to clarification. Discusses the areas covered by some of the papers ‐ such as artificial intelligence using fuzzy logic. Includes applications such as permanent magnets and looks at eddy current problems. States the finite element method is currently the most popular method used for field computation. Closes by pointing out the amalgam of topics.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. 19 no. 2
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 17 October 2016

Georg Fassott, Jörg Henseler and Pedro S. Coelho

The purpose of this paper is to explain how to model moderating effects of composites using partial least squares (PLS) path modeling. It provides the methodological underpinning…

4132

Abstract

Purpose

The purpose of this paper is to explain how to model moderating effects of composites using partial least squares (PLS) path modeling. It provides the methodological underpinning of moderating effects in general and describes the various approaches for forming the interaction term, i.e., the product indicator approach, the two-stage approach, and orthogonalization.

Design/methodology/approach

The paper discusses the use of standardized vs unstandardized construct scores and introduces spotlight analysis as a useful way to report findings.

Findings

Researchers should rely on unstandardized estimates when analyzing moderating effects. Centering or orthogonalization can help improve the interpretability of path coefficients.

Practical implications

PLS software implementations should facilitate unstandardized estimates.

Originality/value

This paper formulates step by step guidelines for analyzing moderating effects of composites using PLS path modeling. It is the first to propose spotlight analysis for PLS path modeling.

Details

Industrial Management & Data Systems, vol. 116 no. 9
Type: Research Article
ISSN: 0263-5577

Keywords

Book part
Publication date: 29 August 2005

Kai S. Cortina, Hans Anand Pant and Joanne Smith-Darden

Over the last decade, latent growth modeling (LGM) utilizing hierarchical linear models or structural equation models has become a widely applied approach in the analysis of…

Abstract

Over the last decade, latent growth modeling (LGM) utilizing hierarchical linear models or structural equation models has become a widely applied approach in the analysis of change. By analyzing two or more variables simultaneously, the current method provides a straightforward generalization of this idea. From a theory of change perspective, this chapter demonstrates ways to prescreen the covariance matrix in repeated measurement, which allows for the identification of major trends in the data prior to running the multivariate LGM. A three-step approach is suggested and explained using an empirical study published in the Journal of Applied Psychology.

Details

Multi-Level Issues in Strategy and Methods
Type: Book
ISBN: 978-1-84950-330-3

1 – 10 of over 9000