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Article
Publication date: 27 March 2024

Syed Abidur Rahman, Seyedeh Khadijeh Taghizadeh, Golam Mostafa Khan and Malgorzata Radomska

The study aims to test the framework that proposes the role of resources (intellectual capital) in mobilizing entrepreneurial orientation that influences the competitiveness…

Abstract

Purpose

The study aims to test the framework that proposes the role of resources (intellectual capital) in mobilizing entrepreneurial orientation that influences the competitiveness improvement of micro-small-medium enterprises (MSMEs) under the lens of resource orchestration theory.

Design/methodology/approach

In this study, 347 respondents from the MSMEs participated through a structured questionnaire. For the data analysis purpose, the structural equation modeling technique was employed using SmartPLS software.

Findings

The results suggest human, structural, and relational capital are significant antecedents of entrepreneurial orientation, which leads to competitiveness improvement. The findings also indicate the mediation role of entrepreneurial orientation between intellectual capital and competitiveness improvement.

Practical implications

The current study presumably will supplement the promising research effort to progress the research orchestration theory and also could be a strategic guideline for the managers/owners of the MSMEs.

Originality/value

This study is possibly a novel attempt to divulge the association between intellectual capital (tripartite model) and competitiveness improvement of firms under the lens of resource orchestration theory.

Details

Journal of Small Business and Enterprise Development, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1462-6004

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

Article
Publication date: 23 October 2023

Manpreet K. Arora and Sukhpreet Kaur

Employee Stock Options [ESOs] have been used widely as a component of employees' compensation. To maximise the incentive effect of these options it is very important to understand…

Abstract

Purpose

Employee Stock Options [ESOs] have been used widely as a component of employees' compensation. To maximise the incentive effect of these options it is very important to understand the exercise decision of the employees. This is an important financial decision that is dependent on both rational and psychological factors. This paper aims to study the mediating role of Herding Bias on Personality Traits and the employees' decision to exercise ESOs.

Design/methodology/approach

The data were collected through a self-structured questionnaire from 210 employees of Banks and NBFCs [Non-Banking Financial Companies] who have received and exercised the ESOs. SPSS MACRO version 25 was used to understand the mediational effect of Herding Bias on Personality Traits and Employees' decision to exercise their ESOs.

Findings

The results showed that Personality Traits affect the employees' decision to exercise their ESOs. The study also shows a partial negative mediating effect of Herding Bias on Personality Traits and employees' decision to exercise ESOs.

Originality/value

Limited study has been conducted on how the employees make their decision to exercise ESOs. Although extant studies have touched upon the importance of including behavioural biases in ascertaining the exercise decision of the employees, the predictors of the behavioural biases have not been studied under this context. To the best of the author's knowledge, this study is the first in itself to study the inter-linkage between Personality Traits, Herding Bias and employees' decision to exercise ESOs.

Details

Managerial Finance, vol. 50 no. 4
Type: Research Article
ISSN: 0307-4358

Keywords

Book part
Publication date: 5 April 2024

Bruce E. Hansen and Jeffrey S. Racine

Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the…

Abstract

Classical unit root tests are known to suffer from potentially crippling size distortions, and a range of procedures have been proposed to attenuate this problem, including the use of bootstrap procedures. It is also known that the estimating equation’s functional form can affect the outcome of the test, and various model selection procedures have been proposed to overcome this limitation. In this chapter, the authors adopt a model averaging procedure to deal with model uncertainty at the testing stage. In addition, the authors leverage an automatic model-free dependent bootstrap procedure where the null is imposed by simple differencing (the block length is automatically determined using recent developments for bootstrapping dependent processes). Monte Carlo simulations indicate that this approach exhibits the lowest size distortions among its peers in settings that confound existing approaches, while it has superior power relative to those peers whose size distortions do not preclude their general use. The proposed approach is fully automatic, and there are no nuisance parameters that have to be set by the user, which ought to appeal to practitioners.

Details

Essays in Honor of Subal Kumbhakar
Type: Book
ISBN: 978-1-83797-874-8

Keywords

Book part
Publication date: 5 April 2024

Taining Wang and Daniel J. Henderson

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production…

Abstract

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

Book part
Publication date: 5 April 2024

Emir Malikov, Shunan Zhao and Jingfang Zhang

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework…

Abstract

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

Book part
Publication date: 5 April 2024

Feng Yao, Qinling Lu, Yiguo Sun and Junsen Zhang

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the…

Abstract

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

Details

Essays in Honor of Subal Kumbhakar
Type: Book
ISBN: 978-1-83797-874-8

Keywords

Article
Publication date: 14 November 2023

Yasir Abdullah Abbas, Nurwati A. Ahmad-Zaluki and Waqas Mehmood

This paper examines the relationship between the extent and quality of the four dimensions of corporate social responsibility disclosure (CSRD) namely community, environment…

Abstract

Purpose

This paper examines the relationship between the extent and quality of the four dimensions of corporate social responsibility disclosure (CSRD) namely community, environment, workplace and marketplace with the long-run share price performance of Malaysian initial public offering (IPO) companies.

Design/methodology/approach

This study utilised secondary data by the content analysis of the annual reports and Datastream of 115 IPOs listed from 2007 to 2015 in Malaysia. The IPO’s performance was determined by calculating the return measures under the equally weighted and value-weighted schemes of the mean abnormal returns and buy-and-hold abnormal returns covering the three years post-listing using the event-time approach.

Findings

The findings demonstrate that Malaysian IPOs experience substantial overperformance and underperformance when both the IPO performance measures are benchmarked against the matched companies and market. The results indicated that the extent and quality of the community and environment CSRD dimensions are positively and significantly correlated to the IPO’s performance. On the other hand, the extent and quality of the workplace and marketplace CSRD dimensions are negatively and significantly correlated to the IPO performance.

Practical implications

Malaysian regulators could benefit from these findings in their endeavour to carry out a reform process on CSRD to improve its quality. The results of this study are important to investors, regulators, non-government organisations, communities and policymakers. They also enhance the understanding of companies about the importance of disclosing greater CSR information to improve their performance and profitability.

Originality/value

To the researchers' best knowledge, this study provides new insights into the association between CSRD and the performance of Malaysian IPO companies, which is considered important.

Details

Management of Environmental Quality: An International Journal, vol. 35 no. 3
Type: Research Article
ISSN: 1477-7835

Keywords

Article
Publication date: 7 February 2022

Muralidhar Vaman Kamath, Shrilaxmi Prashanth, Mithesh Kumar and Adithya Tantri

The compressive strength of concrete depends on many interdependent parameters; its exact prediction is not that simple because of complex processes involved in strength…

Abstract

Purpose

The compressive strength of concrete depends on many interdependent parameters; its exact prediction is not that simple because of complex processes involved in strength development. This study aims to predict the compressive strength of normal concrete and high-performance concrete using four datasets.

Design/methodology/approach

In this paper, five established individual Machine Learning (ML) regression models have been compared: Decision Regression Tree, Random Forest Regression, Lasso Regression, Ridge Regression and Multiple-Linear regression. Four datasets were studied, two of which are previous research datasets, and two datasets are from the sophisticated lab using five established individual ML regression models.

Findings

The five statistical indicators like coefficient of determination (R2), mean absolute error, root mean squared error, Nash–Sutcliffe efficiency and mean absolute percentage error have been used to compare the performance of the models. The models are further compared using statistical indicators with previous studies. Lastly, to understand the variable effect of the predictor, the sensitivity and parametric analysis were carried out to find the performance of the variable.

Originality/value

The findings of this paper will allow readers to understand the factors involved in identifying the machine learning models and concrete datasets. In so doing, we hope that this research advances the toolset needed to predict compressive strength.

Details

Journal of Engineering, Design and Technology , vol. 22 no. 2
Type: Research Article
ISSN: 1726-0531

Keywords

Book part
Publication date: 5 April 2024

Zhichao Wang and Valentin Zelenyuk

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were…

Abstract

Estimation of (in)efficiency became a popular practice that witnessed applications in virtually any sector of the economy over the last few decades. Many different models were deployed for such endeavors, with Stochastic Frontier Analysis (SFA) models dominating the econometric literature. Among the most popular variants of SFA are Aigner, Lovell, and Schmidt (1977), which launched the literature, and Kumbhakar, Ghosh, and McGuckin (1991), which pioneered the branch taking account of the (in)efficiency term via the so-called environmental variables or determinants of inefficiency. Focusing on these two prominent approaches in SFA, the goal of this chapter is to try to understand the production inefficiency of public hospitals in Queensland. While doing so, a recognized yet often overlooked phenomenon emerges where possible dramatic differences (and consequently very different policy implications) can be derived from different models, even within one paradigm of SFA models. This emphasizes the importance of exploring many alternative models, and scrutinizing their assumptions, before drawing policy implications, especially when such implications may substantially affect people’s lives, as is the case in the hospital sector.

1 – 10 of 31