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Showing 3 results for Performance Measurement
An Integrated Model for Continuous and Simultaneous Performance Improvement: A SCOR-Based Supply Chain Decision Alignment
Mahdi Rezaei, Ali Salmasnia, Mohammad Reza Maleki,
Volume 34, Issue 3 (9-2023)
Abstract
This article develops an integrated model of transmitting strategies and operational activities to enhance the efficiency of supply chain management. As the second objective, this paper aims to improve supply chain performance management (SCPM) by employing proper decision-making approaches. The proposed model optimizes the performance indicator based on SCOR metrics. A process-based method is utilized for high-level decisions, while a mathematical programming method is proposed for low-level decisions. The suggested operational model takes some major supply chain properties such as multiple suppliers, multiple plants, multiple materials, and multiple produced items over several time periods into account. To solve the operational multi-objective optimization model, a goal programming approach is applied. The computational results are explained in terms of a numerical example, and a sensitivity analysis is performed to investigate how the performance of the supply chain is influenced by strategic scenario planning.
 
Measuring the Supply Chain Performance of a Manufacturing Industry with the Characteristics of a Shift of Role in the Global Supply Chain Using the Scor Model
Tenaw Tegbar Tsega, Thoben Klaus-Dieter, Rao D.k.nageswara, Bereket Haile Woldegiorgis,
Volume 35, Issue 2 (6-2024)
Abstract
Ethiopia has made enormous efforts in the leather industry to gain manufacturing capabilities that can be scaled up to other sectors. Those efforts have resulted in the industry shifting its role from raw material supplier to producer of value-added products for the global supply chain (GSC). However, the industry has faced severe challenges in generating the expected revenue, utilizing capacity, and finally coping with the global competitive environment. Studies reveal that manufacturing firms tackle similar challenges by improving their supply chain performance (SCP). The challenges that appeared in the leather industry of Ethiopia could also be solved by improving its SCP. Nonetheless, there is a lack of study on the basic characteristics and SCP of the industry after it has shifted its role. The main objective of this study is, therefore, to measure the SCP to know where it stands using a bench mark and identify the elements that contribute considerably to the low overall SCP in order to lay the foundation for subsequent improvement. To achieve the research objective, data was collected from primary and secondary sources through a questionnaire, survey, observation, and focus group discussion. The data is analyzed using the supply chain operations reference model (SCOR version 12.0). Accordingly, the overall SCP is found to be 67.33%, suggesting an average rating as per the set benchmark. The source process is identified as the most influential element for the overall low SCP, with a percentage gap of 17.23%. Taking corrective action on the identified elements could help the industry overcome the existing challenges by improving its SCP.

Future Direction Of Intelligent Human Resources Management Applications In Employee Performance Measurement And Data Analysis In The Industrial Sector In Jordan
Kafa Al Nawaiseh, Abdullah Al Khatib, Fayiz Sharari, Victor Soultanian, Al’a Jaradat,
Volume 35, Issue 2 (6-2024)
Abstract
The world today gives much importance to human resource management which is viewed as the gate towards effective performance. In this respect, the application of intelligent human resources management increases the effectiveness of HRM and brings about effective performance. Given the importance of this topic, this study sought to evaluate the future direction of intelligent human resources management applications in employee performance measurement and data analysis in the industrial sector in Jordan. It specifically evaluated the effect of intelligent human resources management applications (recruitment and talent acquisition, learning and development, benefits and incentives, workforce planning and improvement) on measuring the performance of employees and analyzing data in the Jordanian industrial sector. This research used the descriptive-inferential method (Inductive Descriptive Methodology). The population included all employees in the supervisory authorities of the 33 industrial companies listed on the ASE, while the sample includes 146 participants. This research found that human resources management applications directly affect measuring the performance of employees and analyzing data in the Jordanian industrial sector. The novelty of this research is that, unlike the previous studies like Al-Wakeel and Ibraheem (2020) and Wang (2024) that were applied to samples from different countries other than Jordan, it specifically addresses the effect of HRM practices on measuring the performance of employees and analyzing data in the Jordanian industrial sector. This research provides the Industrial Sector in Jordan with the necessary knowledge of the future directions of intelligent human management. Adopting intelligent human resource management is deemed important for the Jordanian industrial sector.  It is very important to carry out this research to highlight the effect of human resources management applications on measuring the performance of employees and analyzing data in the Jordanian industrial sector.

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