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Article
Publication date: 2 January 2018

Hira Rani, Ghulam Ali Arain, Aneel Kumar and Iram Rani Shaikh

This study aims to examine the effect of psychological contract breach on organizational disidentification through the “affect-based” mediating mechanisms of trust and distrust.

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Abstract

Purpose

This study aims to examine the effect of psychological contract breach on organizational disidentification through the “affect-based” mediating mechanisms of trust and distrust.

Design/methodology/approach

Using a convenient sampling technique, cross-sectional data were collected from 281 doctors working in public sector health-care organizations in Pakistan. After initial data screening, a confirmatory factor analysis (CFA) was conducted to test the measurement models’ validity and reliability. The hypothesized relationships were tested using structural equation modeling (SEM) with AMOS.

Findings

The results of this study showed that psychological contract breach had significant direct and indirect positive effects through the mediating mechanism of distrust on organizational identification. However, trust was not supported as a mediator in that relationship.

Research limitations/implications

This study uses cross-sectional data. Other researchers should use longitudinal design with two or three time lags. This study uses a sample of doctors from different cities of Pakistan, as this is a global era, so results cannot be generalized; this opens the future avenue for other scholars to select a broad sample from multiple organizations like businesses and NGOs from different countries or to use it in different context. The authors have used single source (questionnaires) and quantitative method to collect data for this study, so there is a probability of self-report bias. As future is of mixed method, so future researchers should use mixed method for deep and thorough understanding of different selected phenomena.

Practical implications

Due to the experiences of breach of psychological contract, the doctors may either lose trust or may experience distrust which may further reduce their level of identification in an organization. Their contribution toward best interest of hospital decreases and their willingness to identify with their working place declines. Practically, the authors have compared that it is either the trust or distrust which can lead to organizational disidentification among doctors.

Social implications

The findings will help employers and hospital authorities to understand that doctors are the most important strategic element of every hospital. Having sound financial, physical and informational capital is incomplete and worthless if there is no “doctor”. Because they have to deal directly with patients, so in this case, they are most important and crucial. A doctor’s identification and their loyalty with high level of trust directly on employer and indirectly on hospital all contributes toward an organization’s long-term success, and ultimately for the success of society.

Originality/value

This study contributes to the existing literature on the consequences of employees’ psychological contract breach by simultaneously testing trust and distrust as the two competing affect-based mediating mechanisms between psychological contract breach and organizational disidentification.

Details

Journal of Asia Business Studies, vol. 12 no. 1
Type: Research Article
ISSN: 1558-7894

Keywords

Available. Open Access. Open Access
Article
Publication date: 13 February 2024

Daniel de Abreu Pereira Uhr, Mikael Jhordan Lacerda Cordeiro and Júlia Gallego Ziero Uhr

This research assesses the economic impact of biomass plant installations on Brazilian municipalities, focusing on (1) labor income, (2) sectoral labor income and (3) income…

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Abstract

Purpose

This research assesses the economic impact of biomass plant installations on Brazilian municipalities, focusing on (1) labor income, (2) sectoral labor income and (3) income inequality.

Design/methodology/approach

Municipal data from the Annual Social Information Report, the National Electric Energy Agency and the National Institute of Meteorology spanning 2002 to 2020 are utilized. The Synthetic Difference-in-Differences methodology is employed for empirical analysis, and robustness checks are conducted using the Doubly Robust Difference in Differences and the Double/Debiased Machine Learning methods.

Findings

The findings reveal that biomass plant installations lead to an average annual increase of approximately R$688.00 in formal workers' wages and reduce formal income inequality, with notable benefits observed for workers in the industry and agriculture sectors. The robustness tests support and validate the primary results, highlighting the positive implications of renewable energy integration on economic development in the studied municipalities.

Originality/value

This article represents a groundbreaking contribution to the existing literature as it pioneers the identification of the impact of biomass plant installation on formal employment income and local economic development in Brazil. To the best of our knowledge, this study is the first to uncover such effects. Moreover, the authors comprehensively examine sectoral implications and formal income inequality.

Details

EconomiA, vol. 25 no. 2
Type: Research Article
ISSN: 1517-7580

Keywords

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Article
Publication date: 26 November 2024

Aneel Manan, Zhang Pu, Jawad Ahmad and Muhammad Umar

Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are…

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Abstract

Purpose

Rapid industrialization and construction generate substantial concrete waste, leading to significant environmental issues. Nearly 10 billion metric tonnes of concrete waste are produced globally per year. In addition, concrete also accelerates the consumption of natural resources, leading to the depletion of these natural resources. Therefore, this study uses artificial intelligence (AI) to examine the utilization of recycled concrete aggregate (RCA) in concrete.

Design/methodology/approach

An extensive database of 583 data points are collected from the literature for predictive modeling. Four machine learning algorithms, namely artificial neural network (ANN), random forest (RF), ridge regression (RR) and least adjacent shrinkage and selection operator (LASSO) regression (LR), in predicting simultaneously concrete compressive and tensile strength were evaluated. The dataset contains 10 independent variables and two dependent variables. Statistical parameters, including coefficient of determination (R2), mean square error (MSE), mean absolute error (MAE) and root mean square error (RMSE), were employed to assess the accuracy of the algorithms. In addition, K-fold cross-validation was employed to validate the obtained results, and SHapley Additive exPlanations (SHAP) analysis was applied to identify the most sensitive parameters out of the 10 input parameters.

Findings

The results indicate that the RF prediction model performance is better and more satisfactory than other algorithms. Furthermore, the ANN algorithm ranks as the second most accurate algorithm. However, RR and LR exhibit poor findings with low accuracy. K-fold cross-validation was successfully applied to validate the obtained results and SHAP analysis indicates that cement content and recycled aggregate percentages are the effective input parameter. Therefore, special attention should be given to sensitive parameters to enhance the concrete performance.

Originality/value

This study uniquely applies AI to optimize the use of RCA in concrete production. By evaluating four machine learning algorithms, ANN, RF, RR and LR on a comprehensive dataset, this study identities the most effective predictive models for concrete compressive and tensile strength. The use of SHAP analysis to determine key input parameters and K-fold cross-validation for result validation adds to the study robustness. The findings highlight the superior performance of the RF model and provide actionable insights into enhancing concrete performance with RCA, contributing to sustainable construction practice.

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Article
Publication date: 1 July 2024

Aneel Manan, Pu Zhang, Shoaib Ahmad and Jawad Ahmad

The purpose of this study is to assess the incorporation of fiber reinforced polymer (FRP) bars in concrete as a reinforcement enhances the corrosion resistance in a concrete…

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Abstract

Purpose

The purpose of this study is to assess the incorporation of fiber reinforced polymer (FRP) bars in concrete as a reinforcement enhances the corrosion resistance in a concrete structure. However, FRP bars are not practically used due to a lack of standard codes. Various codes, including ACI-440-17 and CSA S806-12, have been established to provide guidelines for the incorporation of FRP bars in concrete as reinforcement. The application of these codes may result in over-reinforcement. Therefore, this research presents the use of a machine learning approach to predict the accurate flexural strength of the FRP beams with the use of 408 experimental results.

Design/methodology/approach

In this research, the input parameters are the width of the beam, effective depth of the beam, concrete compressive strength, FRP bar elastic modulus and FRP bar tensile strength. Three machine learning algorithms, namely, gene expression programming, multi-expression programming and artificial neural networks, are developed. The accuracy of the developed models was judged by R2, root means squared and mean absolute error. Finally, the study conducts prismatic analysis by considering different parameters. including depth and percentage of bottom reinforcement.

Findings

The artificial neural networks model result is the most accurate prediction (99%), with the lowest root mean squared error (2.66) and lowest mean absolute error (1.38). In addition, the result of SHapley Additive exPlanation analysis depicts that the effective depth and percentage of bottom reinforcement are the most influential parameters of FRP bars reinforced concrete beam. Therefore, the findings recommend that special attention should be given to the effective depth and percentage of bottom reinforcement.

Originality/value

Previous studies revealed that the flexural strength of concrete beams reinforced with FRP bars is significantly influenced by factors such as beam width, effective depth, concrete compressive strength, FRP bars’ elastic modulus and FRP bar tensile strength. Therefore, a substantial database comprising 408 experimental results considered for these parameters was compiled, and a simple and reliable model was proposed. The model developed in this research was compared with traditional codes, and it can be noted that the model developed in this study is much more accurate than the traditional codes.

Details

Anti-Corrosion Methods and Materials, vol. 71 no. 5
Type: Research Article
ISSN: 0003-5599

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Article
Publication date: 12 April 2024

Miguel Afonso Sellitto, Maria Soares de Lima, Leandro Tomasin da Silva, Nelson Kadel Jr and Maria Angela Butturi

The purpose of the article is to identify relevant criteria for decision support in the implementation of waste-to-energy (WtE)-based systems.

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Abstract

Purpose

The purpose of the article is to identify relevant criteria for decision support in the implementation of waste-to-energy (WtE)-based systems.

Design/methodology/approach

The methodology is a simple case study with a qualitative approach. Five experts involved in the project of a thermoelectric power plant qualitatively evaluated, on a Likert scale, a decision model with 15 indicators derived from recent studies. The research object was the first stage of a project to implement a thermoelectric plant employing municipal solid waste (MSW) in southern Brazil.

Findings

The study identified 15 criteria supporting the decision-making process regarding WtE implementation for MSW in a mid-sized city in southern Brazil. The study identified that compliance with MSW legislation, compliance with energy legislation, initial investment and public health impact are the most influential criteria. The study offered two models for decision processes: a simplified one and a complete one, with ten and fifteen indicators, respectively.

Research limitations/implications

The study concerns mid-sized municipalities in southern Brazil.

Practical implications

Municipal public managers have now a methodology based on qualitative evaluation that admits multiple perspectives, such as technical, economic, environmental and social, to support decision-making processes on WtE technologies for MSW.

Social implications

MSW management initiatives can yield jobs and revenues for vulnerable populations and provide a correct destination for MSW, mainly in developing countries.

Originality/value

The main originality is that now municipal public decision-makers have a structured model based on four constructs (technical, economic, environmental and social) deployed in 15 indicators to support decision-making processes involving WtE and MSW management.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Available. Content available
Book part
Publication date: 23 August 2023

Free Access. Free Access

Abstract

Details

Strategic Corporate Responsibility and Green Management
Type: Book
ISBN: 978-1-80071-446-5

Available. Open Access. Open Access
Article
Publication date: 16 August 2024

Devisson Mesquita dos Santos, Fernanda Leandra Leal Lopes, André Cristiano Silva Melo, Denilson Ricardo de Lucena Nunes, Izabela Simon Rampasso and Vitor William Batista Martins

This paper is dedicated to elaborating, proposing and validating an action plan to enhance the mitigation of risks generated by the COVID-19 pandemic in the electric sector supply…

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Abstract

Purpose

This paper is dedicated to elaborating, proposing and validating an action plan to enhance the mitigation of risks generated by the COVID-19 pandemic in the electric sector supply chain, aiming to promote a more resilient supply chain.

Design/methodology/approach

For this, a systematic review of the literature was carried out to prepare an action plan that was validated by a group of experts, through the Delphi methodology.

Findings

As a result, an action plan was obtained, with 18 actions subdivided into 13 resilience elements and related to 20 main risks arising from the pandemic. The actions oriented to the development of relationships among supply chain members, promotion of a culture oriented to learning and problem solving, contingency plan, safety stock and risk management were pointed as those capable of generating resilience in the chain analyzed in the moment of crisis.

Originality/value

The results achieved can contribute to the expansion of debates in the area of resilient supply chain management, as well as contribute to supply chain managers in their elaboration and definition of actions that aim to make the supply chain more resilient. It is noteworthy that no similar study was found in the literature considering the specificities of supply chain management in the Brazilian Amazon region.

Details

Modern Supply Chain Research and Applications, vol. 6 no. 3
Type: Research Article
ISSN: 2631-3871

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Article
Publication date: 19 April 2022

Neha Chhabra Roy and N.G. Roy

The study aims to identify the severe socioeconomic, environmental, and ecological impacts caused by the construction of mega and large hydro-power plants in Uttarakhand, India…

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Abstract

Purpose

The study aims to identify the severe socioeconomic, environmental, and ecological impacts caused by the construction of mega and large hydro-power plants in Uttarakhand, India. In addition to identifying the attributes, the study creates an integrated index that will assist in the development of sustainable hydro-power.

Design/methodology/approach

The methodology used for this impact identification was based on extensive literature review, focused expert discussions and further validation through a primary survey among the stakeholders in the hydropower sector. The sustainability index (SI) was estimated using the fuzzy logic theory.

Findings

The study area SI shows that few projects are in extreme zones, and through suggestive measures, few project sites can be made viable for long-term sustainable project site. A Hydropower Sustainability Assessment Protocol–based conceptual model is also proposed for mitigation of impacts.

Originality/value

Hydropower plays an essential role in access to cleaner and cheaper sources of energy; it defines the usage of water resources toward inflation-free green energy and holds spectacular operational flexibility. Despite the significant advantages associated with hydroelectric power projects, there are adverse side effects as well. The water-based power sector industry contributes to any nation through both economic and environmental ways. Although one-third of the power business in India is carried out through water-based hydropower projects, recent trends in water-based hydropower projects show significant socioeconomic and environmental impacts that create a debate about the sustainability of these projects.

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Article
Publication date: 27 May 2014

Karthik N.S. Iyer

The purpose of this research is to enhance understanding of the sources of relational rents in supply chains and the nature of their relationships with performance. Using the…

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Abstract

Purpose

The purpose of this research is to enhance understanding of the sources of relational rents in supply chains and the nature of their relationships with performance. Using the relational view framework and contingency perspective, the study develops a model and hypotheses to understand the nature of the relationships of collaboration and resource specificity with operational performance under technology context contingencies.

Design/methodology/approach

Data for testing the hypothesized relationships in the conceptual model were collected through a survey of managers in the Hoover’s database of manufacturing firms. The survey sample included 115 responses from a wide variety of manufacturing forms.

Findings

Findings support the conventional wisdom relating collaboration and operational improvements. Notably, technological turbulence has a differential interactive influence on collaboration and resource specificity in predicting operational performance. In the former, the strength of the performance relationship is enhanced, while in the latter, it diminishes. Product complexity enhances the collaboration–operational performance linkage. The results, however, have to be further corroborated by more confirmatory analysis in future research.

Research limitations/implications

The research findings are not conclusive but of an exploratory initial evidence, as stepwise regression analysis has its limitations. Additionally, while the study specifically focused on demand-side collaboration aspects, supply chain management envelops upstream and internal collaboration as well. Investigating the performance implications and the interactive dynamics among all three partnerships in the supply chains provides a richer understanding of supply chain partnerships. Besides, more comprehensive insights could be obtained by modeling the interactive effects of other factors in the operating context.

Practical implications

Firms derive performance benefits from close collaboration with downstream partners because the operational enhancements from such relationships have customer service implications. Besides, the results provide a framework to managers for understanding the technology context conditions that may be best suited for leveraging collaborative initiatives and idiosyncratic investments in pursuit of operational performance improvements.

Originality/value

Much of the evidence on the rent generation capabilities in supply chain partnerships is still anecdotal and extant empirical research lacks adequate explanation. Another critical shortcoming in extant literature is research on the disentangled interactive influence of operating context factors on the supply chain sources of rent (i.e. capabilities)–performance relationships. The study contributes by addressing these issues.

Details

Journal of Business & Industrial Marketing, vol. 29 no. 5
Type: Research Article
ISSN: 0885-8624

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Article
Publication date: 8 December 2023

Weihua Liu, Tingting Liu, Ou Tang, Paul Tae Woo Lee and Zhixuan Chen

Using social network theory (SNT), this study empirically examines the impact of digital supply chain announcements disclosing corporate social responsibility (CSR) information on…

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Abstract

Purpose

Using social network theory (SNT), this study empirically examines the impact of digital supply chain announcements disclosing corporate social responsibility (CSR) information on stock market value.

Design/methodology/approach

Based on 172 digital supply chain announcements disclosing CSR information from Chinese A-share listed companies, this study uses event study method to test the hypotheses.

Findings

First, digital supply chain announcements disclosing CSR information generate positive and significant market reactions, which is timely. Second, strategic CSR and value-based CSR disclosed in digital supply chain announcements have a more positive impact on stock market, however there is no significant difference when the CSR orientation is either towards internal or external stakeholders. Third, in terms of digital supply chain network characteristics, announcements reflecting higher relationship embeddedness and higher digital breadth and depth lead to more positive increases of stock value.

Originality/value

First, the authors consider the value of CSR information in digital supply chain announcements, using an event study approach to fill the gap in the related area. This study is the first examination of the joint impact of digital supply chain and CSR on market reactions. Second, compared to the previous studies on the single dimension of digital supply chain technology application, the authors innovatively consider supply chain network relationship and network structure based on social network theory and integrate several factors that may affect the market reaction. This study improves the understanding of the mechanism between digital supply chain announcements disclosing CSR information and stock market, and informs future research.

Details

Industrial Management & Data Systems, vol. 124 no. 2
Type: Research Article
ISSN: 0263-5577

Keywords

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