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Publication date: 4 May 2018

Bakhtiar, Defi Irwansyah and Zulmiardi

Purpose – This study aims to determine the results of productivity index, profitability and improvement of company prices and to understand the relationship between…

Abstract

Purpose – This study aims to determine the results of productivity index, profitability and improvement of company prices and to understand the relationship between partial input factors and productivity, profitability, and price fixing.

Design/Methodology/Approach – In this work, the productivity at the palm oil factory PT Sayaukath Sejahtera was measured and evaluated by using The American Productivity Center (APC) model approach.

Findings/Results – The results showed that each index that has been analyzed has a 5.143% decrease in the productivity index per year with a profitability equal to 0.286% per year and an increase in the price improvement index of 5.143% per year. Thus, it is concluded that from each index that has been analyzed, there is a decrease in the productivity index and profitability per year and there is an annual increase in the price improvement index.

Research Limitations/Implications (if applicable)

Practical Implications (if applicable)

Originality/Value

Article
Publication date: 15 November 2022

Bismark Amfo, Adinan Bahahudeen Shafiwu and Mohammed Tanko

The authors investigated cocoa farmers' access to subsidized fertilizer in Ghana and implications on productivity.

Abstract

Purpose

The authors investigated cocoa farmers' access to subsidized fertilizer in Ghana and implications on productivity.

Design/methodology/approach

Primary data were sourced from 435 cocoa farmers. Cragg hurdle and two-step Tobit model with continuous endogenous regressors/covariates were applied for the drivers of cocoa farmers' participation in fertilizer subsidy programme and productivity. Propensity score matching (PSM), inverse-probability weights (IPW) and augmented inverse-probability weights (AIPW) were applied for productivity impact assessment of fertilizer subsidy.

Findings

All the farmers were aware of fertilizer subsidy for cocoa production in Ghana. Farmers became aware of fertilizer subsidy through extension officers, media and other farmers. Half of cocoa farmers benefitted from fertilizer subsidy. Averagely, cocoa farmers purchased 292 kg of subsidized fertilizer. Many socio-economic, farm-level characteristics and institutional factors determine cocoa farmers' participation in fertilizer subsidy programme, quantity of subsidized fertilizer obtained and productivity. Beneficiaries of fertilizer subsidy recorded higher cocoa productivity than non-beneficiaries. Hence, fertilizer subsidy for cocoa production in Ghana leads to a gain in productivity.

Practical implications

There should be more investments in fertilizer subsidy so that all cocoa farmers benefit and obtain the required quantities.

Originality/value

The authors provide new evidence on cocoa productivity gain or loss emanating from fertilizer subsidy by combining different impact assessment techniques for deeper analysis: PSM, IPW and AIPW.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

Keywords

Open Access
Article
Publication date: 18 November 2022

Reetta Oksa, Henri Pirkkalainen, Markus Salo, Nina Savela and Atte Oksanen

Social media platforms are increasingly used at work to facilitate work-related activities and can either challenge or make people feel more productive at jobs. This study…

Abstract

Purpose

Social media platforms are increasingly used at work to facilitate work-related activities and can either challenge or make people feel more productive at jobs. This study drew from technostress and employee well-being literature and analyzed longitudinal effects of professional social media (PSM) invasion, work engagement and work exhaustion on PSM-enabled productivity.

Design/methodology/approach

Nationally representative five-wave survey data of Finnish employees were analyzed with hybrid multilevel linear regression analysis. Outcome measure was PSM-enabled productivity and the predictors included PSM incqvasion, work exhaustion and work engagement. Age, gender, education, occupational sector, managerial position, remote work and personality traits were used as control variables.

Findings

PSM invasion and work engagement had both within-person and between-person effects on PSM-enabled productivity. Higher educated and individuals with open personality reported higher PSM-enabled productivity. No association between work exhaustion and PSM-enabled productivity was found.

Originality/value

The findings are central considering the increasing use of social media and other technologies for work purposes. The authors challenge the dominant view in the literature that has often seen PSM invasion as a negative factor. Instead, PSM invasion's positive association with PSM-enabled productivity and the association of work engagement and PSM-enabled productivity should be recognized in work life.

Details

Information Technology & People, vol. 35 no. 8
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 23 November 2022

Ibrahim Karatas and Abdulkadir Budak

The study is aimed to compare the prediction success of basic machine learning and ensemble machine learning models and accordingly create novel prediction models by…

Abstract

Purpose

The study is aimed to compare the prediction success of basic machine learning and ensemble machine learning models and accordingly create novel prediction models by combining machine learning models to increase the prediction success in construction labor productivity prediction models.

Design/methodology/approach

Categorical and numerical data used in prediction models in many studies in the literature for the prediction of construction labor productivity were made ready for analysis by preprocessing. The Python programming language was used to develop machine learning models. As a result of many variation trials, the models were combined and the proposed novel voting and stacking meta-ensemble machine learning models were constituted. Finally, the models were compared to Target and Taylor diagram.

Findings

Meta-ensemble models have been developed for labor productivity prediction by combining machine learning models. Voting ensemble by combining et, gbm, xgboost, lightgbm, catboost and mlp models and stacking ensemble by combining et, gbm, xgboost, catboost and mlp models were created and finally the Et model as meta-learner was selected. Considering the prediction success, it has been determined that the voting and stacking meta-ensemble algorithms have higher prediction success than other machine learning algorithms. Model evaluation metrics, namely MAE, MSE, RMSE and R2, were selected to measure the prediction success. For the voting meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R2 are 0.0499, 0.0045, 0.0671 and 0.7886, respectively. For the stacking meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R2 are 0.0469, 0.0043, 0.0658 and 0.7967, respectively.

Research limitations/implications

The study shows the comparison between machine learning algorithms and created novel meta-ensemble machine learning algorithms to predict the labor productivity of construction formwork activity. The practitioners and project planners can use this model as reliable and accurate tool for predicting the labor productivity of construction formwork activity prior to construction planning.

Originality/value

The study provides insight into the application of ensemble machine learning algorithms in predicting construction labor productivity. Additionally, novel meta-ensemble algorithms have been used and proposed. Therefore, it is hoped that predicting the labor productivity of construction formwork activity with high accuracy will make a great contribution to construction project management.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 16 November 2022

Biswajit Ghose, Leo Themjung Makan and Kailash Chandra Kabra

The primary purpose of this study is to investigate the impact of carbon productivity on firms' financial performance. Secondly, the study also examines the moderating…

Abstract

Purpose

The primary purpose of this study is to investigate the impact of carbon productivity on firms' financial performance. Secondly, the study also examines the moderating effect of industry types and firm size in the relationship between productivity and firm performance.

Design/methodology/approach

The data used for the study includes 66 listed Indian firms over the period from 2015–2016 to 2019–2020. The data used in the study are collected from the published corporate annual reports and sustainability reports. The study uses a random effect model based on the results of the Hausman test and the Breusch-Pagan test to investigate its objectives.

Findings

Carbon productivity has a favorable impact on firms' financial performance in India, indicating that firms may gain competitive advantages by minimizing carbon emissions and improving carbon productivity. Small and high carbon-intensive firms reap greater benefits from the improvement in carbon productivity compared to their opposite counterparts. However, such differential impact is only observed for the market-based measure but not for the accounting-based measure of financial performance.

Practical implications

The results suggest that high carbon-intensive firms should focus more on improving carbon productivity. Small firms and firms belonging to high carbon-intensive industries can improve their market performance by improving carbon productivity.

Originality/value

This study is a noble attempt to investigate the moderating effect of industry type and firm size while examining the impact of carbon productivity on firm performance in the context of an emerging economy.

Details

Managerial Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0307-4358

Keywords

Article
Publication date: 31 October 2022

Chaitanya Arun Sathe and Chetan Panse

The objective of the study is to analyze the impact of the adoption of the Agile Mindset on the productivity of Agile software development teams in IT enterprises during COVID-19.

Abstract

Purpose

The objective of the study is to analyze the impact of the adoption of the Agile Mindset on the productivity of Agile software development teams in IT enterprises during COVID-19.

Design/methodology/approach

A web-based survey is performed with voluntary participants working with the Agile software development professionals with a specific focus on IT enterprises around Pune, India. For this the initial exploratory literature review was performed, to explore the team's behaviors and their response to the crises like the Covid-19 pandemic. Data is collected from the targeted population using the random sampling method. A questionnaire is designed with the help of a five-point Likert scale. All the respondents were analyzed based on their behaviors shown and how adopting to Agile mindset has impacted their productivity during the pandemic. Collected data would be then analyzed using the Smart PLS-SEM methodology.

Findings

Findings of the study show that Agile software development teams adopting to Agile mindset are better at responding to crisis and quick to adapt to change as teams adopting the Agile mindset is likely to sustain or even improve their productivity during the crises like Covid-19 pandemic. Adapting to an Agile mindset is important for Agile software development teams during a crisis as a response to changes in the working as well as environmental conditions. This study also shows that by adopting an Agile mindset, development teams are better at responding to the crisis eventually improving productivity.

Research limitations/implications

Research limitations for this study-scope of the study could be extended to the larger population across geographies to have improved insights Productivity Factors like- Efforts Efficiency, Backlog-management Index (BMI), and Weighted Average Productivity (VWP) for team members can be included. More behavioral factors for Agile Mindset can be considered.

Practical implications

Agile software development teams are characterized by collaboration and responsibility. Recent enforcement of pandemic precautionary measures has enforced Agile software development teams to work remotely and maintain social distancing while in the office. It was challenging for most of the working people to adjust to the new working conditions (Yang et al., 2021) However, in IT organizations, adopting the Agile mindset has ensured continuous software deliveries, took ownership, and quickly adapted to the volatile situations, ultimately resulting into the growth in the productivity unlike to that of other sectors of the economy.

Social implications

In this study, we have analyzed the hypotheses with statistical significance in association with constructs that are in sync with the available literature. Adopting the Agile mindset values has positively impacted the team's behavior resulting in productivity improvement even in the distributed working locations in pandemic situations.

Originality/value

The study highlights that adopting to Agile mindset has positively impacted an Agile software development team's productivity during the Covid-19 pandemic. As environmental conditions during Covid-19 were uncertain and ambiguous and teams were working in distributed and disconnected ways, many researchers have believed that it would have affected the overall productivity. This was turned true for most of the sectors of the economy, however, Agile software development teams have shown positive trends in their productivity, as they have adopted the Agile mindset values and principles, during crises.

Details

Journal of Advances in Management Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0972-7981

Keywords

Article
Publication date: 18 October 2022

Yihays Fente Tarekegn, Weifeng Li and Huilin Xiao

The current paper's goal is to examine the productivity of the closed banking sector evidenced from Ethiopia. In addition, the inclusion of intangibles on productivity was…

Abstract

Purpose

The current paper's goal is to examine the productivity of the closed banking sector evidenced from Ethiopia. In addition, the inclusion of intangibles on productivity was examined in the current paper.

Design/methodology/approach

First, the standard Malmquist Productivity Index (MPI) was employed for 13 commercial banks for both stages. Second, by excluding the state-owned commercial bank, the analysis employed a bootstrapped MPI for the robust and comprehensive conclusion. Furthermore, from 2010 to 2019, the fixed effect Ordinary Least Square (OLS) regression with balanced panel data was used.

Findings

The standard MPI in both stages shows that the productivity of Ethiopian commercial banks is declining. The technological shock was the main reason for the loss. The catch-up in both stages scored above unity, mainly due to the pure efficiency change. Besides, when combined with tangible resources, the inclusion of resource-based view (RBV) proxy variables reduces technological shock regress and ultimately improves productivity change. The bootstrapped MPI also reveals that technological shock is the primary source of the productivity decline. However, efficiency change also contributes to the productivity decline based on this estimation.

Research limitations/implications

Future research could examine the more extensive productivity analysis by considering the primary sources of data collections for resource-based variables.

Practical implications

According to the study's results, banking regulatory authorities and bank management, including the shareholders, should continue to invest in cutting-edge technology to improve the productivity of the banking sector.

Originality/value

This is the first comprehensive study of productivity for Ethiopian commercial banks based on the standard MPI, bootstrapped MPI, and OLS by incorporating all resources into the analysis.

Details

International Journal of Productivity and Performance Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 18 October 2022

Ummad Mazhar

The health costs associated with obesity are increasing in developed and emerging economies. Particularly important, though remaining underexplored, is the overall impact…

Abstract

Purpose

The health costs associated with obesity are increasing in developed and emerging economies. Particularly important, though remaining underexplored, is the overall impact of health risks associated with being obese and overweight on the productivity of firms in a cross-country setting. The purpose of this paper is to address these issues.

Design/methodology/approach

This paper exploits the natural variation in the percentage of obese males in the population as an exogenous health risk randomly distributed across firms in each country.

Findings

Investigating this link for a sample of around 80 emerging countries, the evidence suggests a significant negative effect of health risks on productivity.

Research limitations/implications

The identification assumptions are checked using different approaches to establish the robustness of the empirical link.

Originality/value

This study helps us understand the microlevel effects of the rising average obesity rate. This knowledge is rare in emerging economies which are facing the highest risks of obesity and cardiovascular diseases associated with it.

Details

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

Keywords

Open Access
Article
Publication date: 1 September 2022

Oluseyi Julius Adebowale and Justus Ngala Agumba

Despite the significance of the construction industry to the nation's economic growth, there is empirical evidence that the sector is lagging behind other industries in…

Abstract

Purpose

Despite the significance of the construction industry to the nation's economic growth, there is empirical evidence that the sector is lagging behind other industries in terms of productivity growth. The need for improvements inspired the industry's stakeholders to consider using emerging technologies that support the enhancement. This research aims to report augmented reality applications essential for contractors' productivity improvement.

Design/methodology/approach

This study systematically reviewed academic journals. The selection of journal articles entailed searching Scopus and Web of Science databases. Relevant articles for reviews were identified and screened. Content analysis was used to classify key applications into six categories. The research results were limited to journal articles published between 2010 and 2021.

Findings

Augmented reality can improve construction productivity through its applications in assembly, training and education, monitoring and controlling, interdisciplinary function, health and safety and design information.

Originality/value

The research provides a direction for contractors on key augmented reality applications they can leverage to improve their organisations' productivity.

Details

Smart and Sustainable Built Environment, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2046-6099

Keywords

Article
Publication date: 16 September 2022

Anas Al-Refaie, Ali Alashwal, Zulkiflee Abdul-Samad, Hafez Salleh and Ahmed Elshafie

Weather is one of the main factors affecting labour productivity. Existing weather-productivity models focussed on hot and cold climates paying less attention to the…

Abstract

Purpose

Weather is one of the main factors affecting labour productivity. Existing weather-productivity models focussed on hot and cold climates paying less attention to the tropics. Many tropical countries are expected to be the most areas affected by accelerated climate change and global warming, which may have a severe impact on labour health and productivity. The purpose of this paper is to assess whether the existing models can be used to predict labour productivity based on weather conditions in the tropics.

Design/methodology/approach

Five models are identified from the literature for evaluation. Using real labour productivity data of a high-rise building project in Malaysia, the actual productivity rate was compared with predicted productivity rates generated using the five models. The predicted productivity rates were generated using weather variables collected from an adjusting weather station to the project.

Findings

Compared with other models evaluated in this paper, the United States Army Corps of Engineers (USACE) was found to be the best model to predict productivity based on the case study data. However, the result shows only a 57% accuracy level of the USACE model indicating the need to develop a new model for the tropics for more accurate prediction.

Originality/value

The result of this study is perhaps the first to apply meteorological variables to predict productivity rates and validate them using actual productivity data in the tropics. This study is the first step to developing a more accurate productivity model, which will be useful for project planning and more accurate productivity rate estimation.

Details

Built Environment Project and Asset Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-124X

Keywords

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