The efficient delivery of e-commerce parcels is heavily reliant on the performance of couriers, who represent a critical interface between businesses and end-users, thus influencing the competitive positioning of companies within the logistics sector. This study seeks to analyse the pivotal role of couriers in e-commerce delivery by evaluating various operational activities associated with the delivery process. Through an extensive literature review and analysis of company-provided data, nine key performance criteria were identified: daily delivery volume, average delivery time, delivery accuracy, monthly complaint rate, customer satisfaction ratings, route efficiency, professionalism, incidence of damaged shipments, and overtime rate. Subsequently, 20 courier alternatives were assessed based on these criteria, with the objective of ranking their relative performance in the delivery process. A novel methodological approach, integrating the CRiteria Importance Through Intercriteria Correlation (CRITIC) and Multi-Attributive Border Approximation Area Comparison (MABAC) techniques, was adopted to determine the criteria weights and rank the couriers, respectively. The CRITIC method was employed to compute the relative importance of each criterion, while the MABAC method was utilised to rank the couriers according to their performance. The results indicated that courier alternative A16 achieved the highest performance ranking, whereas alternative A15 was ranked lowest. The findings underscore the robustness of the proposed model and its potential applicability to similar decision-making challenges in related domains, such as supply chain management and logistics. This study highlights the importance of performance-based assessments in improving operational efficiency and enhancing the overall effectiveness of logistics networks.
The rapid advancement of digital finance has emerged as a crucial driver of sustainable urban development, yet its impact on green total factor productivity (GTFP) remains underexplored. This study investigates the mechanisms through which digital finance influences GTFP and examines its spatial spillover effects within Chinese prefecture-level cities. Utilizing panel data from 278 cities spanning 2011 to 2021, the Digital Financial Inclusion Index and an urban GTFP measurement framework are employed to conduct a dynamic analysis. The findings reveal that digital finance facilitates GTFP growth primarily through three channels: fostering technological innovation, promoting industrial upgrading, and mitigating resource misallocation. Significant regional heterogeneity is observed, with the impact being more pronounced in central and western China compared to the eastern region. Moreover, cities with lower levels of financial development experience a stronger enhancement in GTFP through digital finance than their more financially developed counterparts. A temporal analysis further indicates that the green efficiency effect of digital finance has intensified over time. Employing a Spatial Error Model (SEM), robust evidence of significant spatial spillover effects is identified, demonstrating a clustering pattern in regional green efficiency improvements. These findings underscore the need for tailored policy interventions to optimize the role of digital finance in promoting sustainable urban development. Policy recommendations include enhancing financial accessibility in underdeveloped regions, strengthening technological diffusion, and fostering coordinated regional green development strategies.
In an increasingly competitive energy sector, the strategic utilization of human resources is paramount to achieving sustainable competitive advantage. The alignment between human resource management (HRM) and strategic objectives plays a critical role in enhancing organizational performance, particularly in power plant operations. This study aims to prioritize human resource performance indicators within the context of power plants by employing a hybrid multi-criteria decision-making (MCDM) approach. Through a comprehensive literature review, the key evaluation criteria—preparation, implementation, and evaluation—were identified. A mixed-method research design was adopted, integrating the Delphi method for expert consensus with a fuzzy Analytic Hierarchy Process (AHP)-Complex Proportional Assessment (COPRAS) approach for quantitative analysis. The study was conducted as an applied case study, with data collected from 15 senior experts and managers at the Nowshahr Combined Cycle Power Plant. Findings indicate that among the main criteria, the implementation dimension was assigned the highest priority, with a final weight of 0.418. Within this category, the training system emerged as the most influential sub-criterion, receiving a weight of 0.1154. Additionally, continuous performance measurement was identified as the most effective strategy for sustaining workforce efficiency. The proposed methodology provides a systematic framework for decision-makers in the energy sector to enhance human resource performance from a strategic perspective, thereby improving overall operational effectiveness.
Human resource management plays a pivotal role in organizational success, with employee satisfaction being a critical factor in maximizing potential and productivity. This study investigates the relationship between leadership styles, organizational justice, and employee satisfaction within the hotel sector in Zadar County. The findings indicate that distributive justice has the most significant positive impact on employee satisfaction, while an autocratic leadership style is found to have a detrimental effect, contributing to lower motivation and higher stress levels among employees. Conversely, transformational leadership positively influences satisfaction by fostering motivation and encouraging employee participation in decision-making processes. The hotels in Zadar County generally report a high level of employee satisfaction, predominantly driven by a transactional leadership style, which emphasizes goal achievement through clearly defined tasks and performance-based rewards. Furthermore, managers exhibit a notable degree of interpersonal justice, treating employees with respect and empathy. These practices are considered to enhance the overall effectiveness of hotel management. In conclusion, the hotel sector in Zadar County benefits from a relatively high level of management effectiveness, characterized by efficiency and respect for employees. However, to further enhance employee satisfaction, it is recommended that management adopt a more democratic leadership style and focus on improving distributive justice, as these factors have the strongest positive influence on satisfaction. The integration of these strategies is expected to foster a more supportive work environment, thereby improving employee morale and retention.
The digitalization of manufacturing processes in Small and Medium-Sized Enterprises (SMEs) is increasingly recognized as a pivotal factor for business growth, market expansion, innovation, and improved investment efficiency. Despite the European Union’s overarching goal of fostering digital transformation across all sectors by 2030, significant regional disparities persist, particularly within Southeast Europe (SEE). Although substantial research has been conducted on the digitalization of businesses within the EU, limited attention has been paid to the specific dynamics of Southeast European countries, especially those aspiring to join the Union. This study aims to fill this gap by analyzing the degree of digitalization and the adoption of Information and Communication Technologies (ICT) in SMEs across Southeast Europe. The Evaluation Based on Distance from the Average Solution (EDAS) method, enhanced by the Entropy weighting technique, was employed to assess the relative position of these countries in relation to the EU digitalization benchmark. Data obtained from the Eurostat database were utilized to evaluate ICT integration in SMEs with 10 to 249 employees. The results highlight a significant divide between EU member states and the candidate countries, with several SEE nations lagging behind the EU average in terms of digital maturity. Notably, discrepancies were identified not only between EU members and non-members but also within the SEE region itself, with clear divisions emerging between countries that have already joined the EU and those in the accession process. These findings underscore the urgent need for accelerated digital transformation and infrastructure development in countries where ICT adoption remains limited. The study emphasizes the importance of targeted policy interventions to foster digital integration and competitiveness among SMEs in Southeast Europe, thus contributing to the broader objectives of the EU’s digital agenda.
This study aims to develop a model of sustainable business performance within small and medium-sized enterprises (SMEs) in the manufacturing sector, with a particular focus on Human Resource Management (HRM) factors, and to compare this model across different sectors, namely manufacturing, trade, and services. The empirical research was conducted in February 2024 across the Visegrad Four (V4) countries—Czech Republic, Slovakia, Poland, and Hungary. Data collection was managed by the European Centre for Economic and Social Research through a Computer-Assisted Web Interviewing (CAWI) method, using a survey questionnaire designed by the research team. Linear regression modeling (LRM) was employed to test the proposed hypotheses. The findings reveal that a participative management style and a high-quality employee appraisal system were identified as significant factors influencing business sustainability within the manufacturing sector. Additionally, career growth planning, employee satisfaction, and low turnover rates were found to have positive effects on sustainability. When comparing the models across the sectors, the research highlighted significant sectoral differences. In the trade sector, all HRM factors were found to be influential, whereas, in the manufacturing sector, only the factors related to participative management style (x1), employee appraisal quality (x2), and career growth planning (x4) showed significant effects. The least significant impact of HRM factors on business sustainability was observed in the services sector, where only two factors (x2 and x4) were significant. Notably, differences were observed in the significance of certain factors across the sectors: while factor x2 (employee appraisal quality) was crucial in the manufacturing sector, it was insignificant in the services sector. Conversely, factor x3 (employee satisfaction) showed no significant effect in the manufacturing sector but was significant in the trade sector. These findings underscore the importance of adapting HRM practices to the specific characteristics of each sector in order to enhance sustainability. The study highlights the necessity for tailored HRM strategies that align with the sector-specific dynamics of SMEs to promote long-term business sustainability.
This study introduces a novel framework that integrates the balanced scorecard (BSC) with Data Envelopment Analysis (DEA) to address the critical challenge of aligning organizational strategy with operational efficiency. The BSC, a widely adopted tool for translating strategic objectives into measurable performance indicators, is utilized to define inputs and outputs in the DEA model. This approach facilitates a comprehensive evaluation of the relative efficiency of decision-making units (DMUs) within organizations, while ensuring that performance assessments are aligned with overarching strategic goals. The integration of these methodologies bridges the gap between qualitative strategic insights and quantitative efficiency assessments, offering a holistic perspective on organizational performance. A case study in the banking sector illustrates the framework’s applicability, demonstrating its effectiveness in identifying inefficiencies, benchmarking high-performing units, and providing actionable recommendations for resource optimization. The results underscore the robustness of the proposed model, highlighting its ability to enhance data-driven decision-making processes and support sustainable organizational growth. The framework’s versatility is further evidenced by its potential for application across diverse sectors, making it a powerful tool for contemporary performance management. The implications of this approach are significant, offering organizations a systematic method for evaluating efficiency while simultaneously ensuring that performance aligns with strategic objectives, thereby fostering long-term organizational success.
The determinants influencing marketing performance in small and medium-sized enterprises (SMEs) have garnered increasing scholarly attention due to their critical role in driving economic development. SMEs face multifaceted challenges in optimizing market strategies, necessitating a comprehensive understanding of the factors underpinning marketing success. Through a systematic literature review (SLR) adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocols, this study synthesizes insights from 44 empirical studies published between 2019 and 2023. Key determinants identified include entrepreneurial orientation, marketing capabilities, innovation, and digital strategies. Entrepreneurial orientation and marketing capabilities were found to exhibit a strong correlation with marketing performance, highlighting their importance in shaping SME competitiveness. Furthermore, innovative practices and the strategic use of digital marketing tools were observed to significantly bolster market positioning, enabling SMEs to achieve competitive differentiation. Enhanced marketing performance is shown to contribute to consistent revenue generation, organizational resilience, and financial stability, thereby promoting long-term sustainability in competitive industries. This investigation advances the academic discourse by proposing an integrated conceptual framework to guide future research on SME marketing performance. Additionally, evidence-based recommendations are provided to assist enterprises in leveraging identified determinants to enhance marketing efficacy and achieve sustainable growth.
The descriptions of Research and Development (R&D) activities in the annual reports of listed companies provide crucial insights into a company’s internal governance, external competitiveness, and long-term sustainability strategies. However, R&D disclosures in China’s securities market are largely semi-mandatory, often leading listed companies to adopt either “self-enhancement” or “self-suppression” approaches in their R&D activity descriptions. This inconsistency between actions and disclosures erodes trust among market participants and exacerbates information asymmetry. Based on annual report data from Chinese manufacturing firms, this study assesses the intensity of R&D activity disclosures from both accounting data and textual information using Latent Dirichlet Allocation (LDA) topic modeling and principal component analysis (PCA). Normalized difference metrics are applied to quantify the level of inconsistency between these two dimensions. Empirical findings reveal a prevalent degree of inconsistency in R&D activity descriptions within manufacturing firms’ annual reports. Furthermore, both accounting and textual disclosure intensities have increased over time, with inconsistency levels initially rising and then showing a marked decline. The findings offer a theoretical basis for enhancing and standardizing R&D activity descriptions and disclosures, serving as a resource for government, companies, third-party agencies, and investors.
Blockchain technology, which gained prominence with the advent of Bitcoin in 2008, has garnered significant attention across various sectors due to its inherent transparency, security, and decentralization. The ability to operate without central authorities has facilitated more efficient and secure transactions, particularly in an increasingly digital environment where cybersecurity has become a critical concern. Cybersecurity, defined as the protection of electronic systems, networks, and data from malicious threats, is paramount for individuals, organizations, and nations. Blockchain has emerged as a promising solution in the cybersecurity domain, offering enhanced data integrity and immutability. Each block in the chain is cryptographically linked to the previous one, making data tampering exceedingly difficult. The decentralized nature of blockchain, requiring validation from multiple participants, reduces the risk of single-point failures and enhances protection against cyberattacks, such as Distributed Denial of Service (DDoS) attacks. Blockchain aligns closely with the Confidentiality, Integrity, and Availability (CIA) triad in cybersecurity by employing encryption techniques and private keys for data protection, ensuring immutability of records, and providing continuous access through distributed networks. While its potential applications are broad, ranging from healthcare to supply chain management and Internet of Things (IoT), several limitations still hinder blockchain’s widespread adoption in cybersecurity. Chief among these are issues related to scalability and resource management, as high transaction volumes can lead to inefficiencies in speed and cost. Emerging solutions, such as hybrid blockchain models, sidechains, and sharding, are being explored to address these challenges. Despite these obstacles, blockchain presents a resilient framework capable of enhancing cybersecurity measures across multiple sectors. Continued research and innovation are necessary to overcome existing limitations and fully unlock the potential of blockchain in reducing cyber risks. As blockchain technology evolves, its role in fortifying defences against cyber threats is expected to become increasingly pivotal, providing a robust and adaptive mechanism to combat future cyberattacks.
The applicability of Industry 4.0 technologies in air cargo terminals was rigorously evaluated with a focus on optimizing operational processes. This study is motivated by the potential of these technologies to substantially enhance efficiency, safety, and the overall quality of logistics services within the air transport sector. To achieve a comprehensive assessment, Multi-Criteria Decision-Making (MCDM) methods were applied, notably the Best-Worst Method (BWM) for determining the prioritization of criteria, and Comprehensive Distance-Based Ranking (COBRA) for an in-depth analysis and ranking of the technologies. The evaluation encompassed critical criteria such as efficiency, productivity, financial sustainability, data security and privacy, integration, scalability, adaptability and flexibility, reliability and resilience, innovation, and the quality of logistics services. The findings indicate that autonomous mobile robots (AMR) emerged as the top-ranked technology, exhibiting superior performance across all key criteria. AMR technology demonstrated remarkable potential in efficiently integrating logistics operations, enhancing productivity, and ensuring high levels of data security and scalability. In addition to AMR, technologies such as the Internet of Things (IoT) and blockchain were identified as pivotal in improving operational processes in air cargo terminals, offering notable benefits in integration, security, and information transparency. The significance of applying Industry 4.0 technologies to transform operational processes in air cargo terminals is underscored, providing a deeper understanding of their capacity to enhance logistics operations in air transport. Further research is recommended to explore the implementation and optimization of these technologies.
Studying the success factors of sustainability-focused business incubators is crucial because these incubators support startups that address environmental and social challenges, promoting sustainable development. Understanding these success factors enables incubators to provide targeted support that enhances the viability and impact of sustainable ventures. By optimizing the performance of sustainability incubators business will address global sustainability challenges and contribute to a more sustainable economy. This study aims to identify factors that support the success of a business incubator in a case study at Andalas University. This research used the Analytic Hierarchy Process (AHP) method, identifying ten factors with 49 subfactors supporting the incubator’s success. Impact Factor (I) with a weight of 0.2349, Output (O) with a weight of 0.1978, and Resource Capacity (SD) with a weight of 0.1286 are the three main factors that determine the success of an incubator. The prioritized subfactors are Contribution to Regional Economic Growth (I2) with a weight of 0.1898, Technology and New Products (O3) with a weight of 0.0711, and Cooperation with Industry (EK1) with a weight of 0.0477. These factors are recommended because they are expected to support the success of the Andalas University Business Incubator.
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