Green human resources management (GHRM) is a critical research issue that has emerged in recent decades. This study aims to investigate the effect of GHRM practices on sustainable performance, with green innovation as a mediating variable, in manufacturing firms in Palestine. To this end, a research model was developed, and a self-administered questionnaire was designed and distributed to a random sample of top management personnel in manufacturing firms in Palestine. The research model was assessed via the partial least squares structural equation modeling (PLS-SEM) using the Smart-PLS software, based on a sample of 58 responses. The model revealed that GHRM practices, green innovation, and sustainable performance are implemented at a moderate level. Moreover, the results confirmed that GHRM practices and green innovation have significant positive effects on sustainable performance. GHRM practices also positively and significantly affect green innovation. Green innovation partially mediates the relation between GHRM practices and sustainable performance. The results of this research present a conceptual framework and a guideline for policymakers in manufacturing firms on how to use GHRM practices to strengthen employees’ commitment to the environment in order to maximize sustainable performance. Furthermore, the study provides a holistic view of GHRM practices, green innovation, and sustainable performance; such a perspective is considered a foundation for future research directions and provides empirical evidence about the relationships between these variables.

Purpose: This study aims at investigating the impact of total quality management (TQM) on corporate sustainability (CS) by mediating the role of corporate social responsibility (CSR) in developing countries.Design/methodology/approach: A mixed research approach was adopted by conducting interviews and a survey. A survey was used as a quantitative tool for data collection from 67 respondents at different managerial levels. Partial least squares structural equation modeling (PLS-SEM) was used for analysis.Findings: The findings demonstrate that customer focus and human resource management (HRM) were the most effective practices. Structural analysis revealed that TQM had a significant impact on CSR and CS. Furthermore, CSR partially mediates the relationship between TQM and CS.Research limitations/implications: The study has developed a conceptual framework to provide policymakers with guidelines on integrating TQM practices and CSR activities into their strategy.Originality/value: This research bridges the gap between TQM and the three pillars of CS, especially in manufacturing enterprises in a developing country context. This research also supports the TQM advocate's argument that effective TQM deployment can dramatically improve organizational performance. Additionally, this study verifies the CS model based on the triple bottom line (TBL) theory and stakeholder theory by assessing the conceptual model's robustness using a mixed-method research methodology, which has never been done before from a Palestinian perspective.

Purpose: This paper aims to investigate the sources of variation in aluminum profiles hot extrusion process for the purpose of process capability improvement at National Aluminum and Profiles Company (NAPCO) in Palestine. The critical-to-quality characteristics (CTQ) have been determined as base variables to measure the process capability.Design/methodology/approach: The DMAIC (Define, Measure, Analyze, Improve, and Control) Lean Six Sigma (LSS) approach has been adopted to conduct this study. More specifically, historical data analysis and PARETO charts have been employed. The defects' root causes have been determined using the cause-and-effect diagram and decision matrix. A course of suggested actions has been established to help in improving extrusion process capability. Minitab-18 software was used for conducting inferential statistical analysis. A case study considering a geometry CTQ of D3 dimension of bottom sash aluminum profiles 4,332 was selected for analysis.Findings: The results indicated a reduction in DPMO from 89,649 to 15,659, sigma level was improved from 2.84 to 3.65, process yield was improved from 91.04% to 98.43% and cost was reduced from U$75,972 to U$13,250.9 (i.e. a saving of U$62,721). Studying and improving the sigma level of the extrusion process would yield fewer defective products and consequently fewer customer complaints. A validation process which has been conducted during the year 2019 showed a consistent improvement that aligns with the first stage of improvement made on October 1, 2018.Research limitations/implications: This study focuses on only one critical quality characteristic (CTQ), namely, a geometry CTQ of D3 dimension of bottom sash aluminum profiles 4,332 produced by NAPCO was selected for analysis.Practical implications: This study would be useful for researchers and practitioners to improve the process capability in aluminum profiles manufacturing industries in general and hot extrusion processes in particular.Originality/value: Many previous studies on applying LSS-DMAIC methodology have been conducted in aluminum industries in developed countries. According to the literature, it is highly recommended to have more case studies of applying LSS-DMAIC in different industries in developing countries. NAPCO is the only aluminum manufacturing plant in Palestine that hotly extrudes and coats aluminum profiles. Hence, the present study is the first of its kind in NAPCO and in Palestine. Projecting the assessment of the impact of process improvement opportunities and capability analyses into monetary measures are also innovative.

Artificial Intelligence (AI) has been recently implemented in various advanced government applications, including security, transportation, and healthcare. The wide variety of AI applications raised the issue of adoption difficulties in governmental usage, which is what this study investigates. More specifically, the present study examines the relationship between personnel perceptions and organizational, technological, and environmental factors that affect the AI acceptance and adoption in the governmental sector. To this end, a conceptual framework integrating the Technology Acceptance Model (TAM) with the Technology Organization Environment (TOE) is proposed and evaluated, where a survey for collecting relevant data from 179 employees working in four Palestinian ministries was utilized. The Partial Least Squares-Structural Equation Modeling (PLS-SEM) analysis of data using Smart PSL 4.1.0.8 revealed a significant association between TAM constructs and AI acceptance and adoption. Specifically, the relationships between the TOE variables and TAM's Perceived Usefulness (PU) or Perceived Ease Of Use (PEOU) were significant, except for the legal framework and organizational readiness relationship with PEOU. Besides the analytical investigation, this paper contributes practical insights into AI implementation in the government sector emerging from personnel perspectives. Theoretically, the study analyzes the validity of the conceptual model and thoroughly investigates its constructs and factors, hence suggesting that the governmental ministries focus on the linkage between institutional factors and individual AI perceptions for the latter’seffective acceptance and adoption.

This research aims to investigate the impact of a green marketing mix, involving green promotion and green pricing support practices, on the consumer’s intention to purchase Electric Vehicles (EVs) in Palestine, with the mediation role of Green Perceived Value (GPV). A quantitative method was used in this research, where relevant data were collected from a random sample via a structured distributed questionnaire which was answered by 53 respondents. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for the analysis. The model revealed that the green promotion and green price support practices, as well as GPV have a positive impact on customer intention to purchase EVs. Moreover, the results confirmed that GPV partially mediates the relation between green marketing mix practices and customer intention to purchase EVs. The results of this research present a guideline for marketing decision makers in automobile dealerships to improve customer EV purchase intention.