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.
Warehousing serves as a critical component in the logistics chain, functioning as an intersection for inbound and outbound flows of goods before distribution to end customers. Given the complexity of warehousing operations, which involve numerous processes, activities, and workforce engagement, significant risks are inherently present. Consequently, a comprehensive risk analysis is imperative for effective risk management. Such analysis informs risk evaluation and facilitates the determination of appropriate mitigation strategies, with the goal of prioritising risks based on their potential impact. The objective of this study is to present a novel approach for risk assessment in warehouses operated by third-party logistics (3PL) companies, employing a combination of Failure Modes, Effects, and Criticality Analysis (FMECA) and Data Envelopment Analysis (DEA). The proposed framework aims to optimise risk prioritisation and to support the implementation of targeted preventive and corrective measures, thereby enhancing workplace safety and operational efficiency. This approach has been applied to a case study of a 3PL provider operating in the Serbian market, where 14 specific risks were identified and assessed. The most critical risks included falls from height, items falling from shelves during handling, forklift operations, and machinery-related risks involving packaging machines, electrical equipment, industrial cleaners, heaters, and forklift battery charging—particularly with regard to potential explosion hazards due to hydrogen gas release and acid spills. Based on the risk assessment, a series of preventive and corrective measures were formulated to mitigate the identified risks, thereby reducing the likelihood of occupational incidents, injuries, and fatalities. The integration of FMECA and DEA has been demonstrated as an effective methodology for systematically evaluating risks in warehouse operations, offering a robust basis for improving safety measures in logistics environments.
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.
In an age where online shopping and innovative services are rapidly evolving, consumer adaptation to shopping trends, store layouts, and payment modalities is critical. Among these adaptations, self-service checkout systems have been introduced in Vietnamese supermarkets to streamline the post-shopping payment process and alleviate cashier counter congestion. This research was conducted to assess factors influencing consumer intentions towards using self-service payment systems. Data from 497 consumers were collected through non-probability sampling and analyzed using the Smart PLS 4.0 software to test various hypotheses. It was found that consumers’ perceptions of usefulness and ease of use, along with their attitudes towards usage, significantly influence their intention to adopt these systems. Importantly, trust was identified as a positive moderator, enhancing the relationship between consumers’ attitudes towards usage and their intentions to engage with self-service payment systems. These findings suggest managerial implications for increasing system acceptance and understanding consumer needs related to self-service payment options in Vietnamese markets. The results contribute to the broader discourse on technology acceptance, particularly within the framework of the Technology Readiness and Acceptance Model, and underscore the importance of trust in the successful deployment of technological solutions in retail settings.
To understand the mechanism of innovative work behaviour (IWB) in China’s higher education. With a total of 495 valid responses from six universities in China, this study utilised Amos26 for data analysis. The structural equation model indicates that organisational politics (OP) significantly influences academics’ knowledge sharing behaviour (KSB) (β = -0.220, p < 0.000) and IWB (β = -0.126, p < 0.005). The mediating effect of knowledge sharing is confirmed (β = -0.193, p < 0.003). This study confirms the detrimental effect of OP on KSB and IWB within Chinese high education institutions. Consequently, to foster innovation among academics, management should consider controlling OP within the organisational environment. Standardising the supervision and management of executive power, ensuring that administrative power operates transparently. Additionally, delineating between OP and non-OP behaviours will mitigate the negative impact of OP on innovation.
The escalating migration from rural to urban locales necessitates an augmented demand for the workforce, local utility services, and mechanization to sustain a balance conducive to public health. This investigation delineates the pivotal role of human resources in executing daily operations required for the upkeep of public green and asphalted areas within Doboj, Bosnia and Herzegovina. It is posited that teamwork and the requisite competencies of the workforce are integral to the utility company’s efficacy and the establishment of conditions requisite for addressing business tasks delineated on weekly and monthly schedules. A cohort of 20 personnel, tasked with the aforementioned responsibilities, was segmented into three categories, predicated upon their skills and capability to fulfil the designated tasks within specified temporal bounds. A novel hybrid Multi-Criteria Decision-Making (MCDM) model, integrating Improved fuzzy Stepwise Weight Assessment Ratio Analysis (IMF SWARA) with Measurement Alternatives and Ranking according to Compromise Solution (MARCOS), was employed to appraise employees across the designated categories. Decision-makers articulated five criteria, which were quantified via the IMF SWARA methodology. Subsequently, the appraisal of worker categories through three discrete models was undertaken employing the MARCOS technique. Outcomes for each category were individually derived and subjected to verification tests, revealing that criterion significance markedly influences human resource ranking. This study underscores the crucial intersection between environmental stewardship and human resource management, advocating for a systematic approach to urban maintenance that leverages MCDM techniques to optimize workforce performance.
The accelerating process of globalization has led to an increase in freight transport volumes, exacerbated road congestion, and heightened environmental concerns, underscoring the imperative for sustainable and alternative transport solutions. Intermodal transport, which amalgamates the benefits of various modes of transportation, emerges as a paramount solution to these challenges. At the core of intermodal transport lies the intermodal terminal, whose efficiency and efficacy are critically contingent upon the transshipment technology employed. This investigation is dedicated to the evaluation of transshipment technologies within intermodal terminals. It is recognized that the selection of transshipment technology necessitates consideration of diverse criteria, mandating the application of appropriate multi-criteria decision-making methodologies. To address this complexity, a novel hybrid model, integrating Fuzzy Step-Wise Weight Assessment Ratio Analysis (FSWARA) with Axial-Distance-Based Aggregated Measurement (ADAM), is proposed. The efficacy of this model is demonstrated through its application in assessing various transshipment technologies, with an emphasis on optimizing the decision-making process in the selection of the most appropriate technology. This study contributes to the body of knowledge by providing a comprehensive framework for the evaluation of transshipment technologies in intermodal terminals, facilitating enhanced decision-making in the context of sustainable and efficient intermodal transport systems.
The viability of numerous businesses in today’s competitive landscape is significantly influenced by their ability to successfully implement outsourcing strategies, particularly in the realm of logistics. Despite the extensive body of literature exploring the multifaceted dimensions of outsourcing, there remains a notable gap in research specifically addressing logistics outsourcing in distinct markets through in-depth case studies. This analysis seeks to bridge this gap by providing a comprehensive examination of the logistics outsourcing process, as evidenced by a case study within the Serbian market. The research delineates the essential steps required for the establishment of a productive logistics partnership, encompassing the identification of needs, selection of a trusted Logistics Provider (LP), integration of logistics solutions with existing IT systems, delegation of goods handling, assignment of intralogistics responsibilities to maintain compliance with prevailing standards, specification of shipping and delivery requisites, and the continuous monitoring of activities and key performance indicators (KPIs). Through a detailed exploration of transportation, customs clearance, warehousing, customs declaration filing, document exchange, software implementation, and cargo insurance, the study illuminates the intricate processes involved. It is highlighted that the key advantages of such collaborations include enhanced efficiency and streamlined operations, while potential risks involve dependency and loss of control over logistics functions. The distinctiveness of this study lies in its comprehensive approach to outsourcing, encompassing seven critical activities, as opposed to the existing literature which predominantly focuses on the outsourcing of singular services. By offering both theoretical insights and practical implications, this research not only contributes to the existing body of knowledge but also paves the way for future investigations into logistics outsourcing, with a particular emphasis on the Serbian market.
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