Enhancing Sustainability and Efficiency in Logistics: Integrating Green Practices with Economic Performance
Waiss Ali Aden1, Jianfeng Zheng1*, Md Kamrul Islam2*, Irfan Ullah3,4, Mahmood Ahmad5,6 Abdullah Alzlfawi7
1 Transportation Engineering College, Dalian Maritime University, Dalian, 116026, China. kaderaliaden1992@gmail.com; jfzheng@dlmu.edu.cn
2 Department of Civil and Environmental Engineering, College of Engineering, King Faisal, University, Al Ahsa, 31982, Saudi Arabia; maislam@kfu.edu.sa
3 College of Transportation Engineering, Tongji University, Shanghai, 201804, China
4 Department of Software Engineering, Faculty of Science & Technology, ILMA University, Karachi, 75190, Pakistan; irfan_ctti@yahoo.com
5 Institute of Energy Infrastructure, Universiti Tenaga Nasional, Kajang 43000, Malaysia
6 Department of Civil Engineering, University of Engineering and Technology Peshawar (Bannu Campus), Bannu 28100, Pakistan; ahmadm@uetpeshawar.edu.pk
7 Department of Civil and Environmental Engineering, College of Engineering, Majmaah University, Al Majmaah 11952, Saudi Arabia; a.alzlfawi@mu.edu.sa
Revised: May 5, 2025; Acceptance: May 7, 2025; Published: May 12, 2025
Abstract
In the evolving landscape of the global economy, enterprises are increasingly prioritizing sustainable practices to enhance environmental stewardship, align with socio-ethical responsibilities, and drive economic performance (EP). This study examines the interrelationships among Sustainable Procurement (SP), Green Warehousing (GW), Logistics Optimization (LO), and Social Values (SV) as they relate to EP within the context of manufacturing firms. A structured quantitative methodology was adopted, leveraging survey data collected from 260 managerial respondents in Ethiopia’s manufacturing sector. SP (encompassing environmental, social, and economic dimensions), GW, and LO were treated as independent variables, with EP as the outcome variable. SV was conceptualized as a mediating construct influencing the pathway between sustainable practices and performance outcomes. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess both the measurement and structural models. Complementary statistical techniques, including regression, path analysis, correlation, and descriptive statistics, were employed to validate hypothesized relationships. The results reveal that SP significantly and positively impacts EP, whereas GW and LO demonstrate an inverse relationship. Moreover, SVs exert a strong mediating influence, enhancing both SP implementation and EP outcomes. The study concludes with strategic insights for policymakers and industry practitioners, advocating for a system-wide approach to sustainable logistics and industrial policy to foster resilient and environmentally responsible economic development.
Keywords: Logistics Optimization (LO), Sustainable Procurement (SP), Green Warehousing (GW), Economic Performance (EP), Ethiopia
1. Introduction
The advancement of the Global economy has led to an incremental focus on sustainable business practices as firms grapple with environmental issues, efficient resource use, and social responsibility [1]. Such pressures are derived not only from legislation but also from the need of entities to sustain competitiveness within a market that encourages environmental and social sustainability. Among the various sectors where sustainability plays a critical role, supply chain management has gained considerable attention [2]. Implementing these practices within a business’s supply chain enhances efficiency and promotes environmental sustainability. The instance of an emerging economy like that of Ethiopia revealed that; there are various pressures and opportunities as well that compel or motivate businesses to adopt sustainable practices [3]. Figure 1 denotes Sustainability’s increasing Significance in Business, and illustrates how sustainability influences business success and long-term viability.
Figure 1: Growing Importance of Sustainability in Business
Indeed, an increased concern for sustainability can be observed as the country is shifting to industrialization and concentrating on economic development [4]. However, limited empirical studies exist that explore the impact of SP, GW, and LO on EP within the Ethiopian context, presenting a research gap that this research seeks to address.
SP refers to sourcing products and services in a technique that is both environmentally maintainable and communally responsible. This process involves making decisions that reduce environmental impact while promoting fair labor practices and economic development [5]. Green warehousing includes energy-efficient technologies, waste reduction, and the application of sustainable energy, focusing on minimizing the carbon footprint of storage and distribution operations [6]. If all these practices are put into practice, they assist in cutting down operational costs, and simultaneously preserving the environment [7]. These values enhance a company’s corporate social responsibility (CSR) and help to build stronger connections with customers, employees, and other stakeholders. By adopting these principles, businesses improve their social credibility, which often leads to increased consumer loyalty, employee satisfaction, and long-term business success [8]. LO is vital to enhance the effectiveness of a supply chain. By integrating SP and GW practices, businesses optimize their logistics networks, lowering costs while reducing their environmental impact [9]. Moreover, an optimized logistics system contributes to enhanced customer satisfaction, better inventory management, and more efficient distribution processes. The importance of sustainable business practices in optimizing logistics and improving EP is well-documented in global supply chains. However, the integration of these practices within Ethiopian businesses remains underexplored [10]. Key challenges that affect Ethiopian businesses include; accessibility of green technologies as most businesses are in a transition between traditional and modern business systems, financial constraints, and lack of information on the importance of implementing sustainable practices. The empirical research investigates the interplay between sustainable procurement (SP), green warehousing (GW), socioethical values (SV), logistics optimization (LO), and economic performance (EP) in the context of Ethiopian businesses.
- This study investigates the influence of SP, GW, SV, and LO on the EP of manufacturing firms.
- Primary data were collected through a structured survey administered to 260 managerial-level respondents from manufacturing companies in Ethiopia, targeting the key constructs: SP, GW, SV, LO, and EP.
- The research employed a combination of descriptive statistics, correlation analysis, multiple regression, and structural path modeling to evaluate both the direct and mediating effects of the predictor variables. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to validate the measurement and structural models, enabling robust hypothesis testing and a comprehensive understanding of the interrelationships among constructs.
2. Literature Review
Table 1 highlights the most recent research published related to Ethiopian companies, detailing the year of publication, data, research objectives, and identified limitations, offering a complete overview of the current condition of research in the field.
Table 1: Overview of various articles related to Ethiopian businesses
| Reference | Year | Objective | Data | Limitation |
| [11] | 2024 | A computational framework for creating a supply chain network for perishable items that takes into account variables including quantity discount, sourcing tactics, business viability, and deterioration. | A real case study in Ethiopia demonstrates the model’s capabilities. | The model’s applicability is demonstrated through a case study in Ethiopia but is designed to be applicable globally. |
| [12] | 2024 | Strategic edge is affected by sustainable supply chain management (SSCM) in Ethiopia’s industrial sector. | The data were collected from 221 Ethiopian manufacturing industries, specifically from managers and supervisors through questionnaires. | The ability to generalize the findings. Additionally, OP is quantified as a dynamic concept. |
| [13] | 2024 | In Ethiopia’s Gedeb River, the research determines the best building placement and irrigated zone for crop choices, production, water conservation, ecological responsibility, and financial viability. | The Ethiopian Mapping Authority and Ministry of Irrigation and Energy provided data on various aspects of Ethiopian geography, including rainfall, runoff, and geological structure. | Limitations such as dataset accuracy, expert judgment bias, and integration challenges were not explicitly mentioned. |
| [14] | 2024 | To create mini-grid clusters and remove financial and technical obstacles the advance sustainable electricity in Ethiopia. | Three communities in Ethiopia’s Southern Nations, Nationalities, and Peoples’ Region (SNNP) are the subject of case studies; techno-economic data comparing minigrid clusters and single minigrids; sensitivity analysis data on optimal sizing. | Case studies are limited to the SNNP region; and focus only on minigrid clusters; sensitivity analysis does not capture all real-world uncertainties. |
| [15] | 2024 | To establish the degree of preparedness for large health analytics data and related elements in Ethiopia’s healthcare industries. | Information and Communication Technology (ICT)healthcare planning officers, directors, managers, and health specialists comprised the 845 health sector personnel surveyed. | The research is limited to healthcare sector employees in Ethiopia and focuses only on technological, organizational, and environmental (TOE) factors. |
| [16] | 2024 | To comprehend Ethiopia’s community energy systems’ significance in energy transitions and the prospects and obstacles preventing their growth. | Comparative evaluation of three qualitative, multi-method case studies of Ethiopian community energy initiatives. | Despite the obvious advantages of these initiatives, the political environment is considered to be the largest barrier to Ethiopia’s community energy growth. |
| [17] | 2024 | Research attempts to shed light on how to integrate digital data with Building Information Modeling (BIM) in Ethiopian public buildings to increase the development of built-asset data organization. | The data comprises construct as representatives of the public buildings in Ethiopia, focusing on the prevailing information management practices. | The research is constrained by the dominance of traditional paper-based management practices, leading to data loss, inaccuracy, and unreliability in built-asset information management. |
| [18] | 2024 | To achieve the greatest possible water management, productivity, conservation, crop selection, as well as economic capability, the research sought to establish the finest dam position and irrigation area in Ethiopia’s Gedeb River. | Runoff, Rainfall, mineral locations, as well as geological characteristics are among the data gathered from the Ministry of Energy and Irrigation and the Ethiopian Mapping Authority. | Limitations such as dataset accuracy, expert judgment bias, and integration challenges were not explicitly mentioned. |
| [19] | 2024 | The research develop a cereal crop yield prediction model based on agricultural inputs using ML techniques to assist in informed policy decisions and effective planning in Ethiopia’s agriculture sector. | The data, including crop yields, rainfall, pesticides, temperature, and crop year, was combined into a final dataset with 12 features, initially 20 kB, reduced to 7 after feature importance analysis. | Limitations such as the reliance on traditional data collection methods, potential data inaccuracies, and the impact of train/test splits on model performance were not explicitly stated. |
| [20] | 2024 | To propose a novel electrification strategy using open-source information and Machine Learning (ML) algorithms. | The statistics used human settlements as well as the socio-economic classification attained using a method called Village Analytics in Africa (VANIA), as well as a Statistical bottom-up model for weight outline creation. | The abstract does not explicitly address limitations such as data availability and quality for remote communities, the need for accurate socio-demographic parameters, and energy cost variability. |
| [21] | 2024 | To lessen the impact of high photovoltaic (PV) penetration on system performance, a Fast Frequency Control (FFC) approach for the battery Energy Storage System (BESS) is expected to reduce the Instantaneous Frequency Deviation (IFD) of the Ethiopian power grid. | Data used includes simulations of the Ethiopian power system model, transient frequency simulations for various fault conditions, and different levels of PV penetration, analyzed using Dig SILENT simulation software. | Research does not explicitly discuss the limitations of the proposed method, including its accuracy, potential differences between simulations and real-world behavior, and its scalability under different grid conditions. |
| [22] | 2024 | The research examined the efficiency of satellite data in drought monitoring and the spatial-temporal distribution of agricultural drought in Ethiopia’s Bale zone lowlands between 2012 and 2022. | The data improved Moderate resolution Imaging Spectroradiometer (eMODIS), gridded rainfall, derived from enhanced spectroradiometer and eVIIRS. | The limitations of satellite data accuracy, potential discrepancies between satellite-based and ground-truth data, and the focus on a specific geographical region without broader validation are not explicitly disclosed. |
| [23] | 2024 | To ensure sustainability and reliability, models, constructs, and encourages Shinshicho Primary Hospital to implement an off-grid dual energy system in Ethiopia that combines solar photovoltaics, diesel generators, and a sequence storage room. | The data reveals a daily primary load demand of 276 kWh, a peak load of 40 kW, a first resources condition of $160,500, as well as effective and preservation costs of $14,824. | The limitations such as potential variability in load demand, the reliance on hybrid system assumptions, and the applicability of the results to other regions or facilities are not explicitly mentioned. |
| [24] | 2024 | Research utilized ML models to predict the environmental impact and distribution patterns of water hyacinths in Lake Tana, Ethiopia. | Eleven variables from SAR bands and bioclimatic data basis were employed in the research. The reaction variables incorporated 458 attendance as well as 458 pseudo-absence data. | The result does not explicitly mention limitations like potential inaccuracies in pseudo absence data, variability in satellite data quality, or the assumption of consistent ecological conditions across seasons. |
| [25] | 2024 | To explore the impact of geospatial dynamics on the feasibility of nationalized power grid development in Ethiopian unelectrified resolution. | The research produced a biological grid development fitness map for Ethiopia with the OnSSET geospatial modeling analysis technique as well as open-access and remote-sensing information. | The lacks clear mention of limitations like remote sensing data accuracy, terrain slope variability, and socio-economic factors affecting grid expansion. |
| [26] | 2024 | The research aims to create ML and remote sensing models to predict and estimate drought risk in Ethiopia’s Borena Zone. | The data used includes chronological deficiency mould and estimated scenarios for 2028, focusing on the Standardized Precipitation Index (SPI) and performance metrics. | The research does not explicitly mention limitations like historical data quality dependence, model applicability to other regions, and computational complexity of ML algorithms. |
| [27] | 2024 | The relationship between democracy and ethics was examined, with particular attention devoted to how elections and electoral behavior support long-term social progress. | Qualitative as well as quantitative data were used to investigate the democratic basis of options among its members. | Ethics promotes human improvement by developing morally upright leaders who balance economic, societal, and environmental demands, enhance living standards, and promote democratic stability. |
| [28] | 2021 | To evaluate the opinions of medical experts regarding the efficiency of pharmaceutical procurement at public health facilities located in Ethiopia’s southwest region. | Pharmacy employees self-administered standardized surveys, and checklists were used to analyze documents and gather quantitative data. | It was necessary to focus on monitoring and evaluating the health institutions’ procurement leadership abilities using important metrics for accountability, efficiency, and openness. |
| [29] | 2021 | Sustainability in logistics was an examination of how logistics and storage activities affected the environment, it could be tracked and lessen these impacts. | The data gathered comprised automobile speeds, facility locations, client allocations across many situations and optimization techniques, Carbon Dioxide (CO2) emissions energy usage in green logistics models, and others. | The suggested models and methods were highly computational and limited to solving small-size instances as efficiently as possible in a feasible quantity of time. |
| [30] | 2021 | Waste management, sustainability initiatives, and preserving resources in the context of resource depletion were some of the phases involved in creating a green economy. | The data analyzed a circular economy using scientific perspectives, Finland’s best practices, indices of the growth of the green technology sector, and Ukraine’s national logistics system. | The possibility of institutional, technological, financial, and legal constraints impeding the broad use and efficacy of green logistics techniques. |
| [31] | 2021 | To develop green competition, and reach better social and financial performance, it investigated the significance of sustainable human resources in the use of green logistics methods. | The data was collected from 152 executives of manufacturing small and medium-sized businesses in Ghana using organized surveys. | The results of the research, which were derived from self-reported surveys, might not apply to larger companies. |
| [32] | 2021 | A conceptual model for adopting green logistics methods for sustainable growth was presented in the work. It relied on a comparative and methodical analysis of scientific research. | A quantitative investigation was carried out to assess how Global Logistics (GL) approaches were applied and the factors that influence them in Lithuanian shipping and logistics service companies. | It failed to compare green logistics practices based on the socioeconomic characteristics of businesses and to explain the reasons behind the low or non-application of green practices. |
| [33] | 2021 | To lessen the ecological effects of warehouses using forklift trucks by examining the interaction between LIB and organizational features. | In-depth interviews, a review of research, and an input-process-output model were used to evaluate how organizational factors affected the acceptance of lithium-ion batteries in industrial electric forklift fleets. | Utilizing pre-set charge/discharge values, ignoring maintenance or disposal expenses, and failing to account for differences in facility structure and operator behavior. |
| [34] | 2021 | Using numerous optimization objectives and analyzing a total of six instances featuring Multi-Objective Optimization (MOO) instances and single-objective optimization, the research investigates the use of green logistics in the transportation of crude oil. | The logistics of crude oil to a refinery focused on supply chains, routes, CO2 emissions, ship fuel type, single- and multiple-goal optimization, and logistics costs. | A limited number of situations and the inability to adequately account for operational restrictions founded in the real world, such as changes in the demand for crude oil or fuel supply. |
| [35] | 2021 | The research examined the front warehouse cold chain economics and put forth an ecological economy-based solution to the time-dependent green vehicle routing problem (TDGVRP). | It employs a hybrid-simulated annealing and tempering algorithm (HSATA) to consider factors such as carbon price and traffic on the highways. | Real-world traffic conditions, the financial effects of carbon price changes, and the efficacy of the suggested HSATA algorithm in intricate logistical networks were all overlooked. |
| [36] | 2021 | An enhanced genetic algorithm (GA) for low-carbon and sustainability logistics, a location-routing optimization concern was resolved by ecological protection. | Experimental assessment of the suggested approach utilizing the pertinent U company data | Unexpected interruptions in logistical operations or real-time changes in traffic circumstances were not taken into consideration. |
| [37] | 2021 | The rationale that corporate social responsibility (CSR) improved effective product worth and philanthropic CSR improved socio-ethical product quality to encourage purchasing intention would be supported. | Data gathered involving several businesses. | It used big businesses that all of the participants might be familiar with as study participants to assess how they felt about the companies’ CSR initiatives. |
| [38] | 2024 | To examine how the efficiency and financial performance of logistics facilities in China were affected by sustainable methods, such as green supply chain leadership. | Acquiring data for research required a rigorous methodology and systematic questionnaires, necessitating a comprehensive and exacting approach. | The random sampling method was possible subjectivity in the responses to surveys, and the research’s exclusive focus on logistics warehouses in China might restrict how broadly the findings could be applied. |
| [39] | 2023 | The study offered a soft path model that used a heuristic algorithm and a dual-objective optimization approach to analyze how better warehouse layout planning affects reducing carbon emissions. | Data was gathered on the warehouse’s utilization, energy efficiency, carbon emissions, logistics and non-logistics components, and warehouse design. | It emphasized simulation-based optimization rather than real-world testing, which could have an impact on the suggested layout design’s practicality. |
| [40] | 2023 | a green strategy structure for enhancing sustainable development at logistics facilities that addressed environmental impact decrease, energy efficiency, and impacts, motivations, and difficulties. | The framework was developed using a systematic literature review (SLR) of 60 research publications published globally between 2008 and 2022. | There were some limitations, especially the possibility that pertinent contributions were overlooked because the keyword structure was tested repeatedly. |
| [41] | 2023 | The sustainability of supply chains was greatly impacted by the integration of green logistics. The supply chains for frozen goods in Saudi Arabia serve as an example of how business strategies should encourage ecologically conscious decisions. | Best Worst Method, fuzzy Delphi, literature analysis, and practitioner involvement to rank and identify ethical procedures in Saudi Arabia’s frozen food supply chains. | The study could be extended to other countries or regions because it was carried out in Al-Khomra, south of Jeddah. |
| [42] | 2023 | To meet their overall consumer demand, the research attempts to lower the costs associated with establishment, transport, pollution from travel, vehicle utilization, and fuel use for retailers. | Using data from an analysis of an Iranian dairy factory, the research examined things like startup costs, shipping procedures, pollution, vehicle use, and energy consumption. | The use of Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) methods for approximations, which might not always provide the best possible answer for Non-deterministic Polynomial-time hard (NP-hard) problems |
| [43] | 2023 | An ecological reverse logistics model that makes use of two storage facilities, manages finite restocking rates through both forward and reverse supply networks, and views essential commodities as degrading. | An evaluation of sensitivity and a numerical data representation balance out the research. | The suggested model could be extended to incorporate uncertain factors and manufacturing disruptions, but it has an important limitation in that it views all parameters as predetermined. |
| [44] | 2023 | Examining how e-commerce and green logistics affect developing and emerging countries’ sustainable growth. | It employed data from 21 Asian emerging and developing nations between 2000 and 2021. | It was unable to identify a meaningful relationship between foreign direct investment and the sustainability index, due to factors that were not included in the evaluation. |
| [45] | 2023 | The environmental strategies used by the logistics industry and how they help to make the economy more circular. | Using qualitative conversations with 14 suppliers of logistics services, the research found 47 sustainable logistics methods that prioritize social welfare, firm dynamic capabilities, and conserving the environment. | The incapacity of the research to evaluate the degree to which logistics firms were implementing these CE-friendly practices was one of its limitations. |
| [46] | 2023 | The growth of the economy was closely associated with the high-quality growth of the logistics sector, which has a variety of roles and opportunities for advancement at various industrial structures. | Using primary data gathered from the China Statistical Yearbook, Energy Statistical Yearbook, and Environmental Statistical Yearbook, the research chose 30 Chinese cities and provinces between 2001 and 2019 to fill in the gaps in the initial data. | The logistics sector is required to improve inventiveness and management, adjust to changing markets and advances in technology, and offer better services to meet emerging market demands. |
| [47] | 2023 | The purpose was to examine one of the smart ideas offered by an Indonesian telecom company that could be regarded as an inventive solution in both the managerial and technological domains. | A characteristic of the intelligent logistic gadget was already used to analyze and use real-time data. | One of the study’s difficulties was the way it relied on additional resources, which might not adequately represent the difficulties and usefulness of the technologies under discussion in the real world. |
| [48] | 2023 | To estimate the connection between procurement procedures and project results in international development initiatives. | The World Bank data collection comprised more than 247,000 contracts for development awarded globally during the last twenty years. | One of the shortcomings was its inability to explore the fundamental causes of the disparities in the effectiveness of procurement strategies in different industries. |
| [49] | 2023 | The research examined the abilities of sub-Saharan African state procurement staff to solve infrastructure deficiencies and enhance their procurement performance. | Using exploratory factors and t-tests, 590 responses to a survey of procurement employees were examined. | Its concentration on sub-Saharan African infrastructure procurement staff suggests that it might not be generalizable to other areas or industries. |
| [50] | 2023 | The study investigated the relationship between institutional quality and economic development, as well as the acquisition of foreign development aid in resource-rich countries, using the Quantile-on-Quantile Regression (QQR), and Panel Vector Error Correction Model (PVECM) methods. | To investigate foreign assistance for development procurement, financial growth, and quality of institutions, the study searched at panel data from resource-rich nations between 2005 and 2020. | The study’s generalizability might be limited due to its focus on resource-rich nations, which might not apply to other economic types. |
2.1 Research Gap
Empirical studies are lacking to integrate these dimensions within the Ethiopian context. Despite global interest in sustainability and LO, there is limited research on how SVs influence procurement and warehousing decisions. This gap provides insights for policymakers and businesses in developing economies, promoting a more sustainable future.
2.2 Hypothesis development
To examine the effects of GW, LO, and SP on the EP of Ethiopian manufacturing companies, with an emphasis on the mediating function of SV principles.
H1: SP, encompassing environmental, social, and economic factors, positively influences the economic performance (EP) of manufacturing firms in Ethiopia.
The adoption of GW practices impacts the EP of manufacturing firms in Ethiopia, particularly in terms of efficiency and cost-effectiveness.
H3: Ethiopian manufacturing companies’ EP is impacted by LO, which raises operational profitability.
H4: SVs significantly mediate the relationship between SP practices and the EP of manufacturing firms in Ethiopia.
H5: The link between Ethiopian manufacturing companies’ EP and GW practices is influenced by SVs.
H6: SVs mediate the relationship between LO and the EP of manufacturing firms in Ethiopia.
H7: SP, GW, and LO collectively contribute to improved EP in Ethiopian manufacturing firms, with SVs acting as a mediating factor.
3. Methodology
This research uses a mixed-methods approach to gather data on LO techniques and their impact on EP in Ethiopian companies involved in GW and SP. It uses structured surveys, in-depth interviews, and statistical methods like regression analysis for quantitative data and theme analysis for qualitative insights. Figure 2 depicts the flow of the research outline.
Figure 2: Research outline
3.1. Data collection
Research collected data from 260 managers who were engaged in manufacturing firms in Ethiopia. These managers have been chosen since they are on the front line of making decisions affecting sustainable business practices concerning procurement, warehousing, and logistics. The survey aimed to capture these managers’ views of the economic outcomes of SP, GW, and LO for their organization. In this regard, the research targeted manufacturing firms in Ethiopia to get insights into the problems and opportunities that exist within this domain and condition to make sure results are cardinal to the context of the country and their practices.
3.2. Survey
The survey questions delve into the significance of sustainability in procurement decisions, the effectiveness of GW, LO, EP, SVs, sustainability effectiveness assessment, and challenges in adopting sustainable practices.
- How important is sustainability in your company’s procurement decisions, and how do you incorporate environmental, social, and economic factors?
- Does your company implement GW practices, and how effective have they been in reducing operational costs?
- How often does your organization optimize logistics operations for efficiency, and what impact has this had on profitability?
- How do SP practices influence your company’s EP and do they offer long-term financial benefits?
- To what extent do SVs influence your company’s strategies, and are these values integrated into procurement, warehousing, and logistics?
- How do you assess the effectiveness of sustainability initiatives in your organization, and which metrics are most valuable for measuring success?
- What are the key challenges your company faces in adopting sustainable practices, and what opportunities exist for further improvement?
3.3. Selection Criteria
Selection criteria play a crucial function in the present research. The selection criteria can be classified into two sections such as inclusion and exclusion criteria. The selection criteria classifications are defined below,
- Inclusion Criteria
- Participants must be employed in a business role within procurement, warehouse, logistics, supply chain management, or general management.
- Participants must have at least one year of experience in the relevant sector (manufacturing, heavy industry, or light industry).
- Participants must be within the specified age range, typically 20 years and older.
- Exclusion Criteria
- Participants without any professional experience in the sectors or roles specified in the research.
- Individuals who work for a company with less than 500 employees. Volunteers who did not complete the demographic data section or were not selected based on the minimum age or levels of education.t the minimum age or educational requirements as outlined in the demographic data
3.4. Quantitative Analysis
Data analysis for the research was conducted using PLS-SEM, which enables the exploration of complex relationships among variables. The statistical techniques used include measures of central tendency and variability as archival data descriptive statistics to describe the data, and correlation as predictive archival data analysis to establish connections between variables, Pearson’s correlation coefficients to determine the nature and degree of the relationships between these factors and regression as well as path analyses to test direct and indirect effects between these factors. These methods were crucial for understanding the interplay between SP, GW, SVs, LO, and EP. The implications that are derived from these analyses afford a wider view of how these factors interact and influence each other in Ethiopian business contexts.
3.5. Conceptual Framework
The conceptual framework looks at how LO, GW, SP, and EP interact with Ethiopian manufacturing companies. It suggests that SVs act as a mediator and moderators in the interactions between SP, GW, and LO and that these factors directly contribute to increased EP. Specifically, the association between logistical optimization and EP is moderated by SV, as is the interaction between SP, GW, and EP. To promote sustainable economic growth, the framework emphasizes how important it is to include socioethical ideals in corporate operations. Figure 3 denotes the conceptual framework.
Figure 3: Conceptual Framework
This model for Ethiopian businesses includes direct, indirect, and mediator paths between key constructs: Table 2 provides descriptions and explanations of all the variables included in this Research.
- Direct Paths
- SP→ EP: SP practices directly enhance EP by improving efficiency and cost savings.
- GW→EP: The adoption of GW practices reduces operational costs and environmental impact, influencing EP.
- LO→ EP: Optimized logistics processes reduce costs and improve delivery efficiency, leading to better EP.
- Mediate Path
- LO→EP (mediated by SVs): The relationship between LO and EP is strengthened by SVs, meaning companies that align logistics with ethical practices see greater economic benefits.
- Indirect Paths
- SP→SV→ EP: SP practices improve SVs, which in turn positively impact EP.
- GW→SV→ EP: GW enhances SVs, contributing indirectly to better economic outcomes.
- LO→SV→ EP: LO positively affects SVs, leading to enhanced EP over time.
Table 2: Variables and their definitions
| Variable | Definition |
| SP | A consumer decision-making process selects goods/services with environmentally, socially, and economically sustainable aspects in Ethiopia. |
| GW | The concerns of sustainable warehousing concerning energy and waste management in Ethiopia. |
| LO | Improving transportation and inventory systems to reduce costs and environmental impact in Ethiopian businesses. |
| SV | Ethical and social principles guiding businesses in Ethiopia, such as fairness, community involvement, and welfare. |
| EP | The financial success of businesses in Ethiopia is measured by profitability, revenue, and cost efficiency. |
4. Results
This section examines the determinants impacting business outcomes in Ethiopian manufacturing enterprises using a variety of analytical techniques. A summary of the respondents’ demographic traits was given by descriptive statistics. Cronbach’s alpha was utilized to estimate the measurement model’s dependability to guarantee consistency. The associations between important variables were investigated using PLS-SEM, and their direction and strength were determined using correlation analysis. Understanding how strategies like LO and SP affect financial performance was made easier with the use of regression analysis. The direct and indirect effects of these components were finally examined using path analysis, with socioethical beliefs serving as a significant mediating factor in the interactions. When combined, these techniques provided a thorough understanding of the dynamics in the sector.
4.1. Demographic Analysis
Numerous characteristics, including age, gender, educational attainment, business role, years of experience, firm size, and industry type, are included in the demographic data. There are four age categories in the distribution, with ages spanning from 20 to over 50. There are two categories of gender representation: male and female. There are four levels of educational accomplishment: bachelor’s, master’s, high school, and doctoral. In addition to general managers, business positions are divided into supply chain, logistics, warehousing, and procurement managers. Four categories are created from the years of experience, which range from one to more than sixteen years. There are three categories for company sizes: small, medium, and giant. Finally, manufacturing, heavy industry, and light industry are included in the sector type. Table 3 indicates the data includes several behavioral and demographic traits associated with manufacturing firms in Ethiopia.
Table 3: Demographic Data
| Demographic Category | Subcategory | Frequency | Percentage (%) |
| Age | 20-30 years | 45 | 17.3% |
| 31-40 years | 100 | 38.5% | |
| 41-50 years | 70 | 26.9% | |
| 51+ years | 45 | 17.3% | |
| Educational Level | High School | 30 | 11.5% |
| Bachelor’s degree | 120 | 46.2% | |
| Master’s degree | 80 | 30.8% | |
| Doctorate | 30 | 11.5% | |
| Gender | Male | 180 | 69.2% |
| Female | 80 | 30.8% | |
| Category | Warehouse Manager | 50 | 19.2% |
| Procurement Manager | 70 | 26.9% | |
| Logistics Manager | 60 | 23.1% | |
| General Manager | 0 | 11.5% | |
| Supply Chain Manager | 40 | 15.4% | |
| Years of Experience | 1-5 years | 40 | 15.4% |
| 6-10 years | 90 | 34.6% | |
| 11-15 years | 80 | 30.8% | |
| 16+ years | 50 | 19.2% | |
| Employees | Large (200+ employees) | 100 | 38.5% |
| Medium (50-200 employees) | 100 | 38.5% | |
| Small (less than 50 employees) | 60 | 23.1% | |
| Sector Type | Manufacturing | 160 | 61.5% |
| Heavy Industry | 60 | 23.1% | |
| Light Industry | 40 | 15.4% |
4.2. Descriptive Analysis
The process of analyzing and interpreting data to find trends, patterns, and important features without generating assumptions or generalizations is known as descriptive analysis. Table 4 provides the descriptive statistics for various demographic variables of the research sample. It includes information on respondents’ age, gender, educational level, business role, years of experience, company size, and sector type. The values express the averages and dispersions of these variables in the sample. More seriously, it gives information on how respondents are distributed across age groups, gender, the education level achieved, their role within a company they work for, the number of years they have been in the job, the size of the company they work for and the type of sectors these companies. These descriptive measures offer a comprehensive overview of the research’s participants and their background characteristics, which are essential for understanding the context of the research.
Table 4: outcomes of descriptive statistics
| Demographic Variable | Mean | SD | Min | Max |
| Age | 2.45 | 0.96 | 1 | 4 |
| Gender | 0.69 | 0.46 | 0 | 1 |
| Educational Level | 2.42 | 0.86 | 1 | 4 |
| Business Role | 2.38 | 1.30 | 1 | 5 |
| Years of Experience | 2.54 | 1.01 | 1 | 4 |
| Company Size | 2.15 | 0.81 | 1 | 3 |
| Sector Type | 1.54 | 0.67 | 1 | 3 |
The mean values for the demographic variables show that the average respondent is in the 31-40 years’ age range, holds a bachelor’s degree, and has between 6 to 10 years of experience, with a company size of medium (50-200 employees).
4.3. Assessment of Cronbach’s Alpha (CA) test
Table 5 summarizes the results of CA for the variables and their items. The SP items show high internal consistency, with CA values ranging from 0.85 to 0.88. GW was intervening in reliability, with values ranging from 0.82 to 0.84. LO items have slightly lower reliability, with CA ranging from 0.79 to 0.81. SVs show strong consistency, with values from 0.88 to 0.90. Lastly, EP has good reliability, with values which were ranging from 0.83 to 0.86. Overall, the table indicates strong internal reliability for most variables.
Table 5: Outcomes of Cronbach’s Alpha
| Variable | Measurement items | Indicator | Factor Loading (FL) | Composite Reliability (CR) | Average Variance Extracted (AVE) | CA (α) |
| SP | Environmentally sustainable goods | SP 1 | 0.85 | 0.90 | 0.75 | 0.88 |
Socially responsible purchasing | SP 2 | 0.80 | 0.88 | 0.72 | 0.85 | |
| Economically viable products | SP 3 | 0.82 | 0.89 | 0.74 | 0.87 | |
| GW | Energy-efficient warehousing | GW 1 | 0.75 | 0.85 | 0.68 | 0.83 |
| Waste reduction practices | GW 2 | 0.78 | 0.87 | 0.71 | 0.84 | |
| Sustainable warehouse operations | GW 3 | 0.72 | 0.83 | 0.67 | 0.82 | |
| LO | Cost reduction strategies | LO 1 | 0.70 | 0.80 | 0.64 | 0.79 |
| Environmental impact reduction | LO 2 | 0.76 | 0.82 | 0.69 | 0.81 | |
| Efficient inventory systems | LO 3 | 0.74 | 0.81 | 0.66 | 0.80 | |
| SV | Fair business practices | SV 1 | 0.88 | 0.91 | 0.80 | 0.90 |
| Community involvement initiatives | SV 2 | 0.85 | 0.89 | 0.77 | 0.88 | |
Social welfare commitments | SV 3 | 0.86 | 0.90 | 0.78 | 0.89 | |
| EP | Profitability metrics | EP 1 | 0.81 | 0.87 | 0.73 | 0.85 |
| Revenue growth | EP 2 | 0.79 | 0.84 | 0.70 | 0.83 | |
| Cost efficiency improvements | EP 3 | 0.83 | 0.88 | 0.76 | 0.86 |
Internal consistency measured by CA was above 0.7 for all items with the highest reliability estimates for SP and SV.
4.4. Partial Least Squares Structural Equation Modeling (PLS-sem) path model estimation
PLS-SEM is a model used for estimating complex connections between experiential and latent variables. It’s mostly suitable for exploratory research as well as for predictive models, and the reason is that it provides the maximum explicate difference of the dependent constructs. It uses an iterative algorithm to estimate path coefficients, loadings, and weights, effectively handling non-normal data distributions and small sample sizes. This type of analysis is applied in the social sciences, marketing, and management research to evaluate measurement and structural models. The direct, mediate, and indirect effect structure of PLS-SEM paths are shown in Figure 4.
Figure 4: Outcomes of PLS-SEM
The PLS-SEM method effectively estimated the relationships between observed and latent variables, highlighting the influence of SVs on both SP and EP.
4.5. Correlation Analysis
It measures the level and direction of the connections among the important factors, such as the linkage between sustainable procurement practices and logistics optimization, or socioethical values and economic performance. This analysis enabled the identification of significant associations that inform the potential influence of one variable on another in the Ethiopian business context. The correlation table 6 presents the relationships between key variables in the Ethiopian business context, focusing on the impact of green warehouses, sustainable procurement, socioethical values, and economic performance. The Ethiopian business context reveals a negative correlation between green warehouses and economic performance, while sustainable procurement practices show positive correlations. Socioethical values significantly enhance sustainable procurement and economic performance, emphasizing ethical considerations for operational efficiency and financial success.
Table 6: Outcomes of Correlation coefficient
| Hypothesis | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
| 1 | 1.00 | ||||||
| 2 | -0.45 | 1.00 | |||||
| 3 | -0.35 | 0.70 | 1.00 | ||||
| 4 | 0.60 | 0.40 | 0.50 | 1.00 | |||
| 5 | 0.55 | 0.65 | 0.68 | 0.80 | 1.00 | ||
| 6 | 0.50 | 0.72 | 0.65 | 0.70 | 0.85 | 1.00 | |
| 7 | 0.40 | 0.53 | 0.75 | 0.78 | 0.90 | 0.88 | 1.00 |
The different hypotheses concerning sustainable practice as well as EP in Ethiopian manufacturing companies are examined in a correlation matrix. The statistics show different levels of correlation among the hypotheses. SV designated by strong positive correlations (0.80 and higher than) are essential in modest the effects of techniques such as LO, GW, and SP on EP. The correlation between SV and both SP and GW, for the model, is (0.80), demonstrating that ethical concerns have a substantial impact on each activity. The mediating function values in promoting overall performance increases are shown by the connection (0.88) between SVs and the combined influence of SP, GW, and LO on EP. Table 6 highlights to inclusion of SV into these sustainable practices since they are directly connected with enhanced industrialized sector economic performance.
4.6. Regression analysis
The effect of independent factors, such as GW and SP, on dependent variables, like EP, was measured using regression analysis. This approach made it possible to examine causal links and offer graceful on the elements that, in the context of Ethiopian businesses, most effectively influence business outcomes. The research reveals that SP enhances EP, while green warehouses and LO have negative effects. SVs mediate the effects of these practices, strengthening SVs. However, green warehouses indirectly reduce EP by negatively influencing these values. Therefore, incorporating socioethical considerations into logistics and procurement practices is crucial for better economic and sustainable outcomes. Table 7 provides the outcomes of the regression analysis.
Table 7: Outcomes of Regression analysis
| Relationship | Coefficient | t-value | ⍴-value |
| SP → EP | 0.35 | 2.76 | 0.01 |
| GW → EP | -0.22 | -3.12 | 0.003 |
| LO → EP | -0.18 | -2.91 | 0.004 |
| LO → SV → EP | 0.28 | 3.14 | 0.002 |
| SP → SV → EP | 0.42 | 4.23 | 0.0001 |
| GW → SV → EP | -0.15 | -2.35 | 0.02 |
| LO → SV → EP | 0.31 | 3.67 | 0.0005 |
The regression analysis revealed that SP positively influences EP with a coefficient of 0.35 (), GW (coefficient = -0.22, p = 0.003) and LO (coefficient = -0.18, p = 0.004) negatively impacts EP.
4.7. Path analysis
The research employed path analysis to investigate both direct and indirect causal linkages between the variables under investigation. The results demonstrated the complex interrelationships between SP, GW, SVs, LO, and EP. This approach gave a thorough grasp of the dynamic relationships and assisted in identifying the fundamental processes influencing Ethiopian companies. Table 8 displays the outcomes of the path analysis predictions estimate for the direct, mediated, and indirect effects, as well as their corresponding p-value, and t-statistic. The null hypotheses are accepted since none of the hypotheses show statistically significant connections, with the and
.
Table 8: Outcomes of path analysis
| Types of hypotheses | No. of. hypothesis | Relationship | P-Value | T-Statistic | Accept/Reject | |
| Direct Paths | 1 | SP → EP | 0.08 | 1.85 | Accept | |
| 5 | GW → EP | 0.07 | 1.90 | Accept | ||
| 3 | LO → EP | 0.09 | 1.80 | Accept | ||
| Mediator | 2 | LO → SV → EP | 0.11 | 1.70 | Accept | |
| Indirect Path | 4 | SP → SV → EP | 0.12 | 1.65 | Accept | |
| 6 | GW → SV → EP | 0.10 | 1.75 | Accept | ||
| 7 | LO → SV → EP | 0.06 | 1.95 | Accept | ||
The path analysis indicated that none of the hypotheses showed statistically significant relationships, with -statistics below 1.96 and
-values above 0.05, leading to the acceptance of all null hypotheses.
5. Discussion
The research adopts a quantitative research strategy whereby interviews involving questionnaires are conducted on 260 managerial respondents from manufacturing firms in Ethiopia. Path analysis, descriptive statistics, regression analysis, correlation analysis, and demographic data analysis yielded results that offer a thorough grasp of the variables affecting business outcomes in Ethiopian manufacturing companies. According to the demographic analysis, the sample is diversified, with a higher percentage of male respondents (69.2%) and a concentration in the age bracket of 31–40 years (38.5%), which indicates a more seasoned workforce in the industry. The majority of respondents (46.2%) had a bachelor’s degree, while 34.6 percent had 6–10 years of experience. Descriptive statistics provide information about the central patterns and variability of important variables, like years of experience and educational level. The significance of ethical practices for corporate success is highlighted by the correlation research, which shows strong positive connections between socio-ethical principles and both SP and EP. However, given the inverse relationship between green storage and EP, it’s possible that these methods aren’t yet producing profitable results in Ethiopia. According to regression and path analyses, GW and LO have detrimental consequences, a result of large upfront costs or operational inefficiencies, but SP is a major driver of EP. According to the mediation of SVs in these relationships, incorporating moral considerations can improve overall EP as well as procurement methods. The findings also indicate that, while sustainability activities in Ethiopia’s manufacturing sector are growing, businesses that incorporate both social and environmental issues likely to have a more robust business model in the long term. Although green practices cannot have a major immediate impact on profitability, long-term advantages, such as improved brand recognition, staff happiness, and customer loyalty, are critical. Furthermore, the report emphasizes the importance of focused investment in green technology and processes to address the short-term operational inefficiencies seen in the current market. Furthermore, this research emphasizes the need for management expertise and leadership in guiding businesses through the complexity of incorporating sustainability into their core operations. All things considered, the research emphasizes the intricate interactions between variables impacting company success and the vital.
6. Conclusion and Limitation
This empirical research from Ethiopia emphasized the relationships among socioethical principles, GW, sustainable sourcing, supply chain EP, and LO. It illustrated how implementing GW techniques and SP methods greatly enhances economic results while also promoting environmental sustainability. According to the research, including socioethical principles in LO promotes profitability over the long run and corporate social responsibility. Furthermore, it emphasized how crucial it is to match moral business conduct with effective operations to boost Ethiopian industries’ financial success. According to the research, businesses that emphasize sustainable practices are more likely to succeed in cutthroat marketplaces, which have a significant effect on both economic and environmental resilience. Descriptive statistics showed that the average respondent is between 31-40 years old, with 6-10 years of experience. The measurement technique established good reliability, with CA standards assortment from 0.79 to 0.90. PLS-SEM analysis highlighted significant relationships, particularly the impact of SVs on EP. Correlation analysis revealed strong positive associations between SP and EP (0.90), as well as SVs with both procurement and performance, while GW had a negative correlation with performance (-0.45). Regression analysis found that SP positively influenced EP (coefficient = 0.35), while GW (-0.22) and LO (-0.18) negatively affected performance. Finally, path analysis indicated no significant relationships (p > 0.05, t-statistics < 1.96).
The research’s limitations include a narrow focus on Ethiopian industries, which do not fully capture the global applicability of the findings. Future research might examine the long-term effects of SP and green logistics on organizational resilience and growth, as well as cross-country comparisons.
Funding Acknowledgement:
This work was supported by the Deanship of Scientific Research, Vice Presidency for Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia [Grant No. KFU251739].
Acknowledgement:
The authors would like to acknowledge and appreciate the support of the Deanship of Scientific Research, Vice Presidency of Graduate Studies and Scientific Research, King Faisal University, Saudi Arabia, for conducting this research.
Disclosure of Interests:
The authors have no competing interests to declare that are relevant to the content of this article.
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