Pub Date : 2024-06-13DOI: 10.1108/ijppm-08-2023-0410
Zahid Jumah, Muhammad Moazzam, W. Manzoor, Nabeel Safdar
PurposeThis study investigates the effect of economic policy uncertainty on the firm profitability through moderating role of logistics infrastructure index using US non-financial firms listed at NASDAQ.Design/methodology/approachWe used secondary data set which includes firm-level indicators of 2,323 non-financial US firms listed at NASDAQ over the period of 1998–2018. Ordinary least squares regression with multiple fixed effects used to analyze the data and estimate hypotheses.FindingsThe results show that economic policy uncertainty negatively impacts the firm’s profitability whereas the logistics infrastructure positively moderates the negative impact of EPU on the firm’s profitability.Research limitations/implicationsEconomic policy uncertainty is a significant challenge for managerial decision making and a direct threat to a firm’s profitability. The results of this study imply that the state of logistics infrastructure must be considered as an important policy tool by the senior management to mitigate the negative impact of economic policy uncertainty and to safeguard a firm’s profitability.Originality/valueThis study highlights that logistic infrastructure plays an important role in alleviating the adverse effect of economic policy uncertainty on the profitability of a US non-financial firm.
{"title":"Economic policy uncertainty and firm’s profitability: the role of logistics infrastructure","authors":"Zahid Jumah, Muhammad Moazzam, W. Manzoor, Nabeel Safdar","doi":"10.1108/ijppm-08-2023-0410","DOIUrl":"https://doi.org/10.1108/ijppm-08-2023-0410","url":null,"abstract":"PurposeThis study investigates the effect of economic policy uncertainty on the firm profitability through moderating role of logistics infrastructure index using US non-financial firms listed at NASDAQ.Design/methodology/approachWe used secondary data set which includes firm-level indicators of 2,323 non-financial US firms listed at NASDAQ over the period of 1998–2018. Ordinary least squares regression with multiple fixed effects used to analyze the data and estimate hypotheses.FindingsThe results show that economic policy uncertainty negatively impacts the firm’s profitability whereas the logistics infrastructure positively moderates the negative impact of EPU on the firm’s profitability.Research limitations/implicationsEconomic policy uncertainty is a significant challenge for managerial decision making and a direct threat to a firm’s profitability. The results of this study imply that the state of logistics infrastructure must be considered as an important policy tool by the senior management to mitigate the negative impact of economic policy uncertainty and to safeguard a firm’s profitability.Originality/valueThis study highlights that logistic infrastructure plays an important role in alleviating the adverse effect of economic policy uncertainty on the profitability of a US non-financial firm.","PeriodicalId":503012,"journal":{"name":"International Journal of Productivity and Performance Management","volume":"29 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141346197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12DOI: 10.1108/ijppm-09-2023-0514
Ankit Sharma, S. Jakhar, Ilias Vlachos, Satish Kumar
PurposeOver the past two decades, the hub location domain has witnessed remarkable growth, yet no prior study reviewed and synthesised problem formulation and solution methodologies to address real-life challenges.Design/methodology/approachThe current study conducts a comprehensive bibliometric literature review to develop a thematic framework that describes and presents hub location problems. The work employs cluster, bibliometric, and social network analyses to delve into the essential themes.FindingsKey themes include cooperation, coopetition, sustainability, reshoring, and dynamic demand, contributing to the complex challenges in today’s hub location problems. As the first work in this field, the study serves as a valuable single-source reference, providing scholars and industry practitioners with key insights into the evolution of hub location research, prominent research clusters, influential authors, leading countries, and crucial keywords.Research limitations/implicationsFindings have significant implications since they highlight the current state of hub location research and set the stage for future endeavours. Specifically, by identifying prominent research clusters, scholars can explore promising directions to push the boundaries of knowledge in this area.Originality/valueThis work is a valuable resource for scholars in this domain and offers practical insights for industry practitioners seeking to understand the hub location problems. Overall, the study’s holistic approach provides a solid foundation for advancing future research work in the hub location field.
{"title":"Advances in hub location problems: a literature review and research agenda","authors":"Ankit Sharma, S. Jakhar, Ilias Vlachos, Satish Kumar","doi":"10.1108/ijppm-09-2023-0514","DOIUrl":"https://doi.org/10.1108/ijppm-09-2023-0514","url":null,"abstract":"PurposeOver the past two decades, the hub location domain has witnessed remarkable growth, yet no prior study reviewed and synthesised problem formulation and solution methodologies to address real-life challenges.Design/methodology/approachThe current study conducts a comprehensive bibliometric literature review to develop a thematic framework that describes and presents hub location problems. The work employs cluster, bibliometric, and social network analyses to delve into the essential themes.FindingsKey themes include cooperation, coopetition, sustainability, reshoring, and dynamic demand, contributing to the complex challenges in today’s hub location problems. As the first work in this field, the study serves as a valuable single-source reference, providing scholars and industry practitioners with key insights into the evolution of hub location research, prominent research clusters, influential authors, leading countries, and crucial keywords.Research limitations/implicationsFindings have significant implications since they highlight the current state of hub location research and set the stage for future endeavours. Specifically, by identifying prominent research clusters, scholars can explore promising directions to push the boundaries of knowledge in this area.Originality/valueThis work is a valuable resource for scholars in this domain and offers practical insights for industry practitioners seeking to understand the hub location problems. Overall, the study’s holistic approach provides a solid foundation for advancing future research work in the hub location field.","PeriodicalId":503012,"journal":{"name":"International Journal of Productivity and Performance Management","volume":"117 34","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141352021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-12DOI: 10.1108/ijppm-10-2023-0582
Syed Mohsin Ali Shah, F. Lai, Muhammad Kashif Shad, Salaheldin Hamad, N. Ellili
PurposeDespite the growing emphasis on sustainability and the need to manage environmental, social, and governance (ESG) risks, the direct relationship between enterprise risk management (ERM) and green growth (GG) has not been investigated. This study seeks to fill this gap by examining the effect of ERM on the GG of oil and gas (O&G) companies in Malaysia.Design/methodology/approachThe study used panel data regression models to analyze panel data from 2012 to 2021. For computing GG, we adapted the Organization for Economic Cooperation and Development’s (OECD) GG framework. ERM is computed using COSO and WBCSD guidelines for ESG-related risks. Weighted content analysis is used to measure ERM and GGFindingsThe findings derived from the content and descriptive statistics analyses indicate a consistent and ongoing rise in the adoption of ERM practices over time. However, some companies are still in the initial stages of incorporating ERM to address ESG risks. The study’s findings unequivocally establish a substantial and positive relationship between ERM and GG. ERM drives GG by significantly influencing its environmental and resource productivity dimensions. The study further reveals that the impact of ERM on economic opportunities and policy responses, as well as the natural asset base, is statistically significant, albeit with relatively lower coefficient values.Practical implicationsTo enhance the legitimacy of organizations and foster positive stakeholder relationships, regulators, governments, and policymakers should actively promote the adoption of ERM standards that specifically address ESG risks, as outlined by COSO and WBCSD. This strategic alignment with risk management practices will ultimately contribute to improving green growth for organizations.Originality/valueTo the best of the authors' knowledge, this is the first study examining ERM’s effect on GG. The study adds to the existing literature by focusing on ERM’s role in a company’s GG. It clarifies ERM’s significant effect on diminishing emerging ESG risks and advancing GG
{"title":"Exploring the effect of enterprise risk management for ESG risks towards green growth","authors":"Syed Mohsin Ali Shah, F. Lai, Muhammad Kashif Shad, Salaheldin Hamad, N. Ellili","doi":"10.1108/ijppm-10-2023-0582","DOIUrl":"https://doi.org/10.1108/ijppm-10-2023-0582","url":null,"abstract":"PurposeDespite the growing emphasis on sustainability and the need to manage environmental, social, and governance (ESG) risks, the direct relationship between enterprise risk management (ERM) and green growth (GG) has not been investigated. This study seeks to fill this gap by examining the effect of ERM on the GG of oil and gas (O&G) companies in Malaysia.Design/methodology/approachThe study used panel data regression models to analyze panel data from 2012 to 2021. For computing GG, we adapted the Organization for Economic Cooperation and Development’s (OECD) GG framework. ERM is computed using COSO and WBCSD guidelines for ESG-related risks. Weighted content analysis is used to measure ERM and GGFindingsThe findings derived from the content and descriptive statistics analyses indicate a consistent and ongoing rise in the adoption of ERM practices over time. However, some companies are still in the initial stages of incorporating ERM to address ESG risks. The study’s findings unequivocally establish a substantial and positive relationship between ERM and GG. ERM drives GG by significantly influencing its environmental and resource productivity dimensions. The study further reveals that the impact of ERM on economic opportunities and policy responses, as well as the natural asset base, is statistically significant, albeit with relatively lower coefficient values.Practical implicationsTo enhance the legitimacy of organizations and foster positive stakeholder relationships, regulators, governments, and policymakers should actively promote the adoption of ERM standards that specifically address ESG risks, as outlined by COSO and WBCSD. This strategic alignment with risk management practices will ultimately contribute to improving green growth for organizations.Originality/valueTo the best of the authors' knowledge, this is the first study examining ERM’s effect on GG. The study adds to the existing literature by focusing on ERM’s role in a company’s GG. It clarifies ERM’s significant effect on diminishing emerging ESG risks and advancing GG","PeriodicalId":503012,"journal":{"name":"International Journal of Productivity and Performance Management","volume":"67 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141350549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-10DOI: 10.1108/ijppm-04-2023-0201
Jorge Aníbal Restrepo, Emerson Andres Giraldo, Juan Gabriel Vanegas
PurposeThis study proposes a novel method to improve the accuracy of overall equipment effectiveness (OEE) estimation in the metallurgical industry. This is achieved by modeling the frequency and severity of stoppage events as random variables.Design/methodology/approachAn analysis of 80,000 datasets from a metal-mechanical firm (2020–2022) was performed using the loss distribution approach (LDA) and Monte Carlo simulation (MCS). The data were further adjusted with a product price index to account for inflation.FindingsThe variance analysis revealed supporting colleagues (59.8% of variance contribution), food breaks (29.8%) and refreshments (9.0%) as the events with the strongest influence on operating losses.Research limitations/implicationsThis study provides a more rigorous approach to operational risk management and OEE measurement in the metal-mechanical sector. The developed algorithm supports the establishment of risk management guidelines and facilitates targeted OEE improvement efforts.Originality/valueThis research introduces a novel OEE estimation method specifically for the metallurgical industry, utilizing LDA and MCS to improve accuracy compared to existing techniques.
{"title":"Measuring the production performance indicators for metal-mechanic industry: an LDA modeling approach","authors":"Jorge Aníbal Restrepo, Emerson Andres Giraldo, Juan Gabriel Vanegas","doi":"10.1108/ijppm-04-2023-0201","DOIUrl":"https://doi.org/10.1108/ijppm-04-2023-0201","url":null,"abstract":"PurposeThis study proposes a novel method to improve the accuracy of overall equipment effectiveness (OEE) estimation in the metallurgical industry. This is achieved by modeling the frequency and severity of stoppage events as random variables.Design/methodology/approachAn analysis of 80,000 datasets from a metal-mechanical firm (2020–2022) was performed using the loss distribution approach (LDA) and Monte Carlo simulation (MCS). The data were further adjusted with a product price index to account for inflation.FindingsThe variance analysis revealed supporting colleagues (59.8% of variance contribution), food breaks (29.8%) and refreshments (9.0%) as the events with the strongest influence on operating losses.Research limitations/implicationsThis study provides a more rigorous approach to operational risk management and OEE measurement in the metal-mechanical sector. The developed algorithm supports the establishment of risk management guidelines and facilitates targeted OEE improvement efforts.Originality/valueThis research introduces a novel OEE estimation method specifically for the metallurgical industry, utilizing LDA and MCS to improve accuracy compared to existing techniques.","PeriodicalId":503012,"journal":{"name":"International Journal of Productivity and Performance Management","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141363599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1108/ijppm-09-2023-0512
Abbas Abbasi, Behnaz Shirazi, S. Mohamadi
PurposeThis research highlights the ongoing concern about organizational productivity and the lack of focus on designing an optimal model. The authors aim to create a comprehensive model for managing organizational productivity, considering its impact on profitability, customer satisfaction, and employee morale. They use qualitative research methods, including Systematic Literature Review and Interpretive Structural Modeling (ISM).Design/methodology/approachIn this research using the qualitative research method of Systematic Literature Review, 57 variables affecting productivity were identified. These variables were placed in 16 layers by using the ISM method, which were classified analytically in four sections: INPUTS, OUTPUTS, OUTCOMES and IMPACTS. By determining the relationship between the sections, the research model was designed.FindingsThe potential model for organizational productivity management provides a comprehensive framework addressing critical factors like technology adoption, employee empowerment, organizational culture, and more. It identifies Linkage, Dependent, and independent variables. The lower layers consist of INPUTS such as Technological Tools, Organizational Values, and more. In the highest layer, impactful variables like Enhanced competitiveness, Improved decision-making, and Improved organizational culture are labeled as IMPACTS. Middle layer variables are categorized as OUTPUTS and OUTCOMES.Originality/valueIn this study, the concept of productivity management was redefined for the first time, and a multi-layered model for productivity management was creatively explicated using the structural equation modeling method.
{"title":"A multilevel model for organizational productivity management: an interpretive structural modeling approach","authors":"Abbas Abbasi, Behnaz Shirazi, S. Mohamadi","doi":"10.1108/ijppm-09-2023-0512","DOIUrl":"https://doi.org/10.1108/ijppm-09-2023-0512","url":null,"abstract":"PurposeThis research highlights the ongoing concern about organizational productivity and the lack of focus on designing an optimal model. The authors aim to create a comprehensive model for managing organizational productivity, considering its impact on profitability, customer satisfaction, and employee morale. They use qualitative research methods, including Systematic Literature Review and Interpretive Structural Modeling (ISM).Design/methodology/approachIn this research using the qualitative research method of Systematic Literature Review, 57 variables affecting productivity were identified. These variables were placed in 16 layers by using the ISM method, which were classified analytically in four sections: INPUTS, OUTPUTS, OUTCOMES and IMPACTS. By determining the relationship between the sections, the research model was designed.FindingsThe potential model for organizational productivity management provides a comprehensive framework addressing critical factors like technology adoption, employee empowerment, organizational culture, and more. It identifies Linkage, Dependent, and independent variables. The lower layers consist of INPUTS such as Technological Tools, Organizational Values, and more. In the highest layer, impactful variables like Enhanced competitiveness, Improved decision-making, and Improved organizational culture are labeled as IMPACTS. Middle layer variables are categorized as OUTPUTS and OUTCOMES.Originality/valueIn this study, the concept of productivity management was redefined for the first time, and a multi-layered model for productivity management was creatively explicated using the structural equation modeling method.","PeriodicalId":503012,"journal":{"name":"International Journal of Productivity and Performance Management","volume":"116 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141377660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-06DOI: 10.1108/ijppm-02-2024-0113
Mohamed Y. El Mokadem, Magdy Khalaf
PurposeThe aim of this research is to examine the relationship between green supply chain management and sustainability performance in a manufacturing context.Design/methodology/approachA survey approach was adopted to collect data from 163 manufacturing organizations to test the research hypotheses. A structural equation modeling (SEM) using the technique of path analysis with bootstrapping is used to test the hypothesized relationships.FindingsThe research findings provide supporting evidence for the importance of implementing green supply chain management (GSCM) as a holistic system that includes internal and external green practices. Besides, the findings highlight the direct effect of GSCM on environmental, social and operational performance. Finally, the findings provide supporting evidence that GSCM could only be translated into better economic returns through the improvement of environmental and operational performance.Research limitations/implicationsThe nature of the surveyed sample and the use of a single informant might limit the ability to generalize the research findings outside the research context.Practical implicationsThe research findings help managers understand that GSCM must be implemented as a holistic system and that the real benefits of its implementation extend beyond the mere environmental benefits to include operational, social as well as economic benefits.Originality/valueThe paper’s contribution to knowledge is twofold. First, the study identifies how GSCM is conceptualized and how its effect is translated into improved economic performance. Second, the research explains the contradicting findings in previous studies regarding the relationship between GSCM and economic performance.
{"title":"Building sustainable performance through green supply chain management","authors":"Mohamed Y. El Mokadem, Magdy Khalaf","doi":"10.1108/ijppm-02-2024-0113","DOIUrl":"https://doi.org/10.1108/ijppm-02-2024-0113","url":null,"abstract":"PurposeThe aim of this research is to examine the relationship between green supply chain management and sustainability performance in a manufacturing context.Design/methodology/approachA survey approach was adopted to collect data from 163 manufacturing organizations to test the research hypotheses. A structural equation modeling (SEM) using the technique of path analysis with bootstrapping is used to test the hypothesized relationships.FindingsThe research findings provide supporting evidence for the importance of implementing green supply chain management (GSCM) as a holistic system that includes internal and external green practices. Besides, the findings highlight the direct effect of GSCM on environmental, social and operational performance. Finally, the findings provide supporting evidence that GSCM could only be translated into better economic returns through the improvement of environmental and operational performance.Research limitations/implicationsThe nature of the surveyed sample and the use of a single informant might limit the ability to generalize the research findings outside the research context.Practical implicationsThe research findings help managers understand that GSCM must be implemented as a holistic system and that the real benefits of its implementation extend beyond the mere environmental benefits to include operational, social as well as economic benefits.Originality/valueThe paper’s contribution to knowledge is twofold. First, the study identifies how GSCM is conceptualized and how its effect is translated into improved economic performance. Second, the research explains the contradicting findings in previous studies regarding the relationship between GSCM and economic performance.","PeriodicalId":503012,"journal":{"name":"International Journal of Productivity and Performance Management","volume":"24 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141378957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-14DOI: 10.1108/ijppm-08-2023-0426
Punam Singh, Lingam Sreehitha, Vimal Kumar, B. Rajak, Shulagna Sarkar
PurposeEmployee engagement (EE) continues to be one of the most difficult challenges for organizations today. Numerous factors have been linked to EE, according to studies. However, the necessary human resource management (HRM) strategies and systems for enhancing EE have not yet been developed. It is questionable if all employees inside the company require the same HRM strategies, to boost engagement as one size does not fit all. Therefore, it is necessary to create employee profiles based on factors associated with EE. This study aims to develop employee profiles based on engagement dimensions and outcomes. It seeks to comprehend the relationship between engagement level and factors such as age, years of service and employment grade.Design/methodology/approachUsing latent profile analysis (LPA), we identified five EE profiles (highly engaged, engaged, moderately engaged, disengaged and highly disengaged). These five profiles were characterized by five EE dimensions (Culture Dimensions, Leadership Dimensions, People Process, Business alignment Dimension and Job Dimension) and EE outcomes (Say, Stay and Strive).FindingsThe study revealed that Engaged profiles exhibited low stay outcomes. The highest percentage of disengaged employees fall under 25 years of age with less than 5 years of experience and are at the entry level.Research limitations/implicationsThe study highlights the significance of the people processes dimensions in enhancing engagement. Profiles with low people process dimensions showed high disengagement. Person-centered LPA adds and complements variable-centered approach to develop a better understanding of EE and help organizations devise more personalized strategies. The study would be of interest to both academics and practitioners.Originality/valueThe novelty of this study lies in its attempt to model the employee profiles to comprehend the relationship between engagement levels using LPA.
目的员工敬业度（EE）仍然是当今组织面临的最严峻挑战之一。研究表明，许多因素都与员工敬业度有关。然而，提高员工敬业度所需的人力资源管理（HRM）战略和系统尚未开发出来。公司内部的所有员工是否都需要同样的人力资源管理战略来提高参与度，这一点值得商榷，因为 "一刀切 "的做法并不适合所有人。因此，有必要根据与敬业度相关的因素建立员工档案。本研究旨在根据敬业度维度和结果建立员工档案。设计/方法/途径通过潜在特征分析（LPA），我们确定了五种员工敬业度特征（高度敬业、敬业、中度敬业、脱离敬业和高度脱离敬业）。这五种特征由五个 EE 维度（文化维度、领导力维度、人员流程、业务调整维度和工作维度）和 EE 结果（说、留和努力）来描述。研究的局限性/影响研究强调了人员流程维度在提高敬业度方面的重要性。人员流程维度较低的员工离职率较高。以人为中心的 LPA 是对以变量为中心的方法的补充和完善，有助于更好地了解 EE，帮助组织制定更加个性化的策略。这项研究对学术界和从业人员都很有意义。原创性/价值这项研究的新颖之处在于它尝试使用 LPA 建立员工档案模型，以理解敬业度之间的关系。
{"title":"Profiling employee engagement dimensions and outcomes: a person-centered approach","authors":"Punam Singh, Lingam Sreehitha, Vimal Kumar, B. Rajak, Shulagna Sarkar","doi":"10.1108/ijppm-08-2023-0426","DOIUrl":"https://doi.org/10.1108/ijppm-08-2023-0426","url":null,"abstract":"PurposeEmployee engagement (EE) continues to be one of the most difficult challenges for organizations today. Numerous factors have been linked to EE, according to studies. However, the necessary human resource management (HRM) strategies and systems for enhancing EE have not yet been developed. It is questionable if all employees inside the company require the same HRM strategies, to boost engagement as one size does not fit all. Therefore, it is necessary to create employee profiles based on factors associated with EE. This study aims to develop employee profiles based on engagement dimensions and outcomes. It seeks to comprehend the relationship between engagement level and factors such as age, years of service and employment grade.Design/methodology/approachUsing latent profile analysis (LPA), we identified five EE profiles (highly engaged, engaged, moderately engaged, disengaged and highly disengaged). These five profiles were characterized by five EE dimensions (Culture Dimensions, Leadership Dimensions, People Process, Business alignment Dimension and Job Dimension) and EE outcomes (Say, Stay and Strive).FindingsThe study revealed that Engaged profiles exhibited low stay outcomes. The highest percentage of disengaged employees fall under 25 years of age with less than 5 years of experience and are at the entry level.Research limitations/implicationsThe study highlights the significance of the people processes dimensions in enhancing engagement. Profiles with low people process dimensions showed high disengagement. Person-centered LPA adds and complements variable-centered approach to develop a better understanding of EE and help organizations devise more personalized strategies. The study would be of interest to both academics and practitioners.Originality/valueThe novelty of this study lies in its attempt to model the employee profiles to comprehend the relationship between engagement levels using LPA.","PeriodicalId":503012,"journal":{"name":"International Journal of Productivity and Performance Management","volume":"11 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-01DOI: 10.1108/ijppm-04-2023-0180
M. H. Al-Rifai
PurposeThe purpose of this paper is twofold: first, a case study on applying lean principles in manufacturing operations to redesign and optimize an electronic device assembly process and its impact on performance and second, introducing cardboard prototyping as a Kaizen tool offering a novel approach to testing and simulating improvement scenarios.Design/methodology/approachThe study employs value stream mapping, root cause analysis, and brainstorming tools to identify root causes of poor performance, followed by deploying a Kaizen event to redesign and optimize an electronic device assembly process. Using physical models, bottlenecks and opportunities for improvement were identified by the Kaizen approach at the workstations and assembly lines, enabling the testing of various scenarios and ideas. Changes in lead times, throughput, work in process inventory and assembly performance were analyzed and documented.FindingsPre- and post-improvement measures are provided to demonstrate the impact of the Kaizen event on the performance of the assembly cell. The study reveals that implementing lean tools and techniques reduced costs and increased throughput by reducing assembly cycle times, manufacturing lead time, space utilization, labor overtime and work-in-process inventory requirements.Originality/valueThis paper adds a new dimension to applying the Kaizen methodology in manufacturing processes by introducing cardboard prototyping, which offers a novel way of testing and simulating different scenarios for improvement. The paper describes the process implementation in detail, including the techniques and data utilized to improve the process.
{"title":"Redesigning and optimizing an electronic device assembly cell through lean manufacturing tools and kaizen philosophy: an application case study","authors":"M. H. Al-Rifai","doi":"10.1108/ijppm-04-2023-0180","DOIUrl":"https://doi.org/10.1108/ijppm-04-2023-0180","url":null,"abstract":"PurposeThe purpose of this paper is twofold: first, a case study on applying lean principles in manufacturing operations to redesign and optimize an electronic device assembly process and its impact on performance and second, introducing cardboard prototyping as a Kaizen tool offering a novel approach to testing and simulating improvement scenarios.Design/methodology/approachThe study employs value stream mapping, root cause analysis, and brainstorming tools to identify root causes of poor performance, followed by deploying a Kaizen event to redesign and optimize an electronic device assembly process. Using physical models, bottlenecks and opportunities for improvement were identified by the Kaizen approach at the workstations and assembly lines, enabling the testing of various scenarios and ideas. Changes in lead times, throughput, work in process inventory and assembly performance were analyzed and documented.FindingsPre- and post-improvement measures are provided to demonstrate the impact of the Kaizen event on the performance of the assembly cell. The study reveals that implementing lean tools and techniques reduced costs and increased throughput by reducing assembly cycle times, manufacturing lead time, space utilization, labor overtime and work-in-process inventory requirements.Originality/valueThis paper adds a new dimension to applying the Kaizen methodology in manufacturing processes by introducing cardboard prototyping, which offers a novel way of testing and simulating different scenarios for improvement. The paper describes the process implementation in detail, including the techniques and data utilized to improve the process.","PeriodicalId":503012,"journal":{"name":"International Journal of Productivity and Performance Management","volume":"61 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140356519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-01DOI: 10.1108/ijppm-02-2023-0092
M. Stor
PurposeThe main goal of the article is to determine the mediating role of HRM outcomes in the relationships between staffing the organization and company performance results and to establish whether there are any identifiable regularity in this scope in the pre-pandemic and pandemic period in the HQs and foreign subsidiaries of MNCs.Design/methodology/approachThe empirical research included 200 MNCs headquartered in Central Europe. To capture the actual relations between the variables under study the raw data in the variables were adjusted with the efficiency index (EI). The Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to verify the research hypotheses and assess the mediating effects.FindingsThe research findings show that, with the exception of the HQs in the pandemic period, when staffing had a negative effect on the company performance results in quality, in other cases it had a positive effect on results in HRM, finance, innovativeness and quality, both in the pre-pandemic and pandemic period, although this effect was not always statistically significant. Furthermore, the company's performance results in HRM mediate positively the relationships between staffing and the other three categories of company performance results, regardless of the organizational level (HQs' or subsidiaries') and time period under consideration. Additionally, during the pandemic, the company's performance results in HRM mediate the relationships between staffing and the other company's performance results stronger than in the pre-pandemic time.Originality/valueIn addition to confirming the results of some other studies, the article also provides new knowledge. It determines the mediating role of HRM outcomes in the relationship between staffing and company performance results in finance, innovativeness and quality. Moreover, it identifies certain regularities in the four studied contexts, which is a novelty in this type of research. It also uses an innovative approach to including employee KPIs as the efficiency index in analyzing the relationships between the variables under study.
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Pub Date : 2024-03-29DOI: 10.1108/ijppm-08-2023-0428
Rashmiranjan Panigrahi, A. Shrivastava, S. Nudurupati
PurposeEffective inventory management is crucial for SMEs due to limited resources and higher risks like cash flow, storage space, and stockouts. Hence, the aim is to explore how technology and know-how can be integrated with inventory practices and impact operational performance.Design/methodology/approachThe basis of the analysis was collecting papers from a wide range of databases, which included Scopus, Web of Science, and Google Scholar. In the first phase of the process, a search string with as many as nine related keywords was used to obtain 175 papers. It further filtered them based on their titles and abstracts to retain 95 papers that were included for thorough analysis.FindingsThe study introduced innovative methods of measuring inventory practices by exploring the impact of know-how. It is the first of its kind to identify and demonstrate how technical, technological, and behavioral know-how can influence inventory management practices and ultimately impact the performance of emerging SMEs. This study stands out for its comprehensive approach, which covers traditional and modern inventory management technologies in a single study.Research limitations/implicationsThe study provides valuable insights into the interplay between technical, technological, and behavioral know-how in inventory management practices and their effects on the performance of emerging SMEs in Industry 5.0 in the light of RBV theory.Originality/valueThe RBV theory and the Industry 5.0 paradigm are used in this study to explore how developing SMEs' inventory management practices influence their performance. This study investigates the effects of traditional and modern inventory management systems on business performance. Incorporating RBV theory with the Industry 5.0 framework investigates firm-specific resources and technological advances in the current industrial revolution. This unique technique advances the literature on inventory management and has industry implications.
目的 由于资源有限，且现金流、存储空间和缺货等风险较高，有效的库存管理对中小企业至关重要。因此，本研究旨在探讨如何将技术和诀窍与库存实践相结合，并对运营绩效产生影响。设计/方法/途径分析的基础是从各种数据库（包括 Scopus、Web of Science 和 Google Scholar）中收集论文。在该过程的第一阶段，我们使用了包含多达九个相关关键词的搜索字符串来获取 175 篇论文。研究结果该研究通过探索专有技术的影响，引入了衡量库存实践的创新方法。它首次确定并展示了技术、工艺和行为诀窍如何影响库存管理实践，并最终影响新兴中小企业的绩效。本研究的突出之处在于其全面的方法，在一项研究中涵盖了传统和现代库存管理技术。研究局限/意义本研究根据 RBV 理论，就库存管理实践中技术、工艺和行为诀窍之间的相互作用及其对工业 5.0 新兴中小企业绩效的影响提供了有价值的见解。本研究探讨了传统和现代库存管理系统对企业绩效的影响。将 RBV 理论与工业 5.0 框架相结合，研究了当前工业革命中企业特有的资源和技术进步。这项独特的技术推动了库存管理文献的发展，并对行业产生了影响。
{"title":"Impact of inventory management on SME performance: a systematic review","authors":"Rashmiranjan Panigrahi, A. Shrivastava, S. Nudurupati","doi":"10.1108/ijppm-08-2023-0428","DOIUrl":"https://doi.org/10.1108/ijppm-08-2023-0428","url":null,"abstract":"PurposeEffective inventory management is crucial for SMEs due to limited resources and higher risks like cash flow, storage space, and stockouts. Hence, the aim is to explore how technology and know-how can be integrated with inventory practices and impact operational performance.Design/methodology/approachThe basis of the analysis was collecting papers from a wide range of databases, which included Scopus, Web of Science, and Google Scholar. In the first phase of the process, a search string with as many as nine related keywords was used to obtain 175 papers. It further filtered them based on their titles and abstracts to retain 95 papers that were included for thorough analysis.FindingsThe study introduced innovative methods of measuring inventory practices by exploring the impact of know-how. It is the first of its kind to identify and demonstrate how technical, technological, and behavioral know-how can influence inventory management practices and ultimately impact the performance of emerging SMEs. This study stands out for its comprehensive approach, which covers traditional and modern inventory management technologies in a single study.Research limitations/implicationsThe study provides valuable insights into the interplay between technical, technological, and behavioral know-how in inventory management practices and their effects on the performance of emerging SMEs in Industry 5.0 in the light of RBV theory.Originality/valueThe RBV theory and the Industry 5.0 paradigm are used in this study to explore how developing SMEs' inventory management practices influence their performance. This study investigates the effects of traditional and modern inventory management systems on business performance. Incorporating RBV theory with the Industry 5.0 framework investigates firm-specific resources and technological advances in the current industrial revolution. This unique technique advances the literature on inventory management and has industry implications.","PeriodicalId":503012,"journal":{"name":"International Journal of Productivity and Performance Management","volume":"84 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140366479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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