Organizational Size Research Articles

The Symphony of Evolution: Unraveling Infrastructure Public–Private Partnerships Collaboration Networks Through Participant Characteristics

ABSTRACTUsing collaborative governance theory and stochastic actor‐oriented models (SAOMs), this study examines the co‐evolution of networks and participant characteristics in 1505 infrastructure PPP projects involving 3225 participants across 35 large and medium‐sized Chinese cities. The results show that collaborative networks are highly structured and exhibit small‐world characteristics. Furthermore, in the evolving landscape of China's PPPs, the collaboration network has shifted into three governance patterns: government‐SOEs (State‐owned enterprises) driven, SOEs‐consulting driven, and SOEs dominant. In addition, results reveal that network evolution is promoted by transitive triads, the similarity of organizational size, and geographic proximity, while it is hindered by outdegree, similarities of organizational age and type. The findings provide insights for partner selection and the involvement of governments in public service delivery and the development of governance strategies.

IMPLEMENTED RECONFIGURABLE CACHE MEMORY ARCHITECTURE BASED ON 32-BITS MIPS PROCESSOR

This work presents the design of a reconfigurable cache memory utilizing a 32-bit MIPS processor, implemented through the utilization of VHDL (Very high-speed IC Hardware Description Language). A comprehensive implementation of a 32-bit, single-cycle MIPS processor is presented in VHDL. This processor is capable of supporting 50 instructions, comprising 25-R-type, 16-I-type, and 9-J-type instructions. The processor incorporates a three-dimensional reconfigurable cache memory architecture, enabling the modification of cache memory size, cache organization (in terms of associativity), and cache block size. The reconfigurable cache memory concept proposes the use of multi-cache controller units to execute reconfiguration operations and ensure that all permitted cache memory sets can be utilized with varying levels of associativity. The design is built on an FPGA using the Xilinx ISE design suite, which is based on the hardware description language. To ensure that assess functionality of the proposed reconfigurable cache memory design for various reconfiguration scenarios, numerous assembly language programs have been developed and performed on the MIPS processor. The results validated the efficacy of the suggested reconfigurable cache memory concept and demonstrated its simulation using the Xilinx ISim simulator.

Transforming performance: how agility, response, resilience and support shape success in digital strategies

PurposeEvolving business landscapes have highlighted the crucial role of innovative digital transformation strategies (DTSs) in reimagining organisational operations and responses to optimise performance, regardless of organisational size or employee composition. The study suggests that DTS is a process that occurs continuously, rather than being a one-time event. It also underscores the critical role of personal resilience and organisational support in achieving job performance goals.Design/methodology/approachUsing a survey analysis, this study examines the impact of organisational response and agility, as fundamental components of DTS, on employees' job performance. In addition, it investigates how boundary conditions of personal resilience and organisational support moderates the relationship between (1) organisational agility and job performance, and (2) organisational response and job performance.FindingsThe research findings demonstrate the impact of DTS on job performance. It highlights the mediating roles of organisational support and agility in improving employees' performance. The study also discusses the critical role of personal resilience and organisational support in navigating the insightful impacts of organisational agility and organisational response on the job performance.Originality/valueThis paper presents a theoretical framework that integrates the dynamic capabilities of employees and organisations, providing academics and practitioners with a comprehensive perspective on the growth of employees' dynamic capabilities. By offering insightful discussions, the study highlights that, while creating new DTS, organisations not only improve their dynamic capabilities but also enhances the people’s dynamic capabilities and make them more resilient.

Real-time inventory optimization in dynamic supply chains using advanced artificial intelligence

This paper explores the transformative impact of advanced artificial intelligence (AI) techniques on real-time inventory optimization within dynamic supply chains. The introduction highlights the significance of inventory optimization and the limitations of traditional methods, setting the stage for the integration of AI. A comprehensive literature review summarizes existing research on AI applications in supply chain management, identifying key gaps and areas for further exploration. The paper then delves into various AI techniques, including machine learning, deep learning, and reinforcement learning, detailing their application in predicting demand and supply, and the benefits and challenges of implementing these technologies in real-time inventory systems. The analysis of AI-driven inventory optimization reveals significant improvements in supply chain responsiveness, efficiency, and risk management, alongside discussions on scalability and adaptability across different industries and organizational sizes. The conclusion synthesizes key findings and provides recommendations for future research and practical implementation, emphasizing the need for enhanced data quality, model transparency, and ethical considerations. By harnessing AI, businesses can achieve more efficient, responsive, and resilient supply chains, positioning themselves competitively in an increasingly complex global market.. Keywords: Real-Time Inventory Optimization, Dynamic Supply Chains, Artificial Intelligence, Machine Learning, Deep Learning.

Implementation of AI Recruitment Systems in Swiss HRM: The Importance of Technological and Organizational Factors

Purpose – There are no studies on the factors involved in the spread of AI recruitment tools in Swiss HR. Aims(s) – The aim of this paper is to understand the determinants of AI diffusion in Swiss human resources recruitment process. In addition to the usual factors such as relative advantage, costs, security, financial resources or organizational size, this paper also looks at factors such as red tape or the innovative climate of organizations. Design/methodology/approach – This article is based on a quantitative method, PLS-SEM. Our database consists of 324 private and public respondents working in Swiss HR. They were selected through a survey based on their membership of the various regional sections of the HR Swiss association. Findings – The main findings of this article are that relative advantage, compatibility, complexity, cost reduction, size of organization, technological expertise of employees, innovative climate, and red tape are directly related to the evaluation and adoption stages of this type of AI tool. Security, for its part, is only linked to the evaluation of these tools. Compatibility and technological expertise are also directly linked to the routinization of these tools. Limitations of the study – First, this is a longitudinal study that needs to be replicated to offer causal explanations. There may also be a selection bias in favor of optimistic respondents who already have HR AI in their organization. This bias is nevertheless controlled, as few of our respondents already use this type of tool. In the future, other predictors could be added to our model, including environmental or individual predictors. Practical implications – HR decision-makers now know what levers they can use to successfully implement HR AI in their recruitment process. Originality/value – This article makes a significant contribution to the literature about the diffusion of nascent HR information systems in the specific context of Switzerland and provides decision-makers with levers on which to act to encourage the introduction of this type of AI-based information systems within their organization. No other study has identified the factors behind the spread of HR AI tools in the specific context of Switzerland, as they are still in their infancy.

Beyond organizational size: Recommendations for addressing the scientist–practitioner gap

Beyond organizational size: Recommendations for addressing the scientist–practitioner gap

Impact of Digitalisation in Construction on Australian Designers and Builders: A Cross-Analysis Based on the Size of Organisations

The construction industry has yet to reach significant levels of digitalisation compared to other sectors, which could enhance its processes. Recent building failures globally have eroded public trust in the industry, highlighting issues of compliance. This has prompted the introduction of building regulations, where digitalisation is expected to play a key role in supporting compliance. This paper aims to assess the impact of digitalisation on two key stakeholder groups within the construction industry—designers and builders—across various organisational sizes. A questionnaire survey was conducted with designers and builders in Australia, focusing on information technology (IT) infrastructure, digital capability, training, and research and development. Descriptive statistics were analysed and cross-analyses between designers and builders, as well as across different organisation sizes, were conducted using the Mann–Whitney U and Kruskal–Wallis H tests. The findings revealed clear differences between designers and builders regarding digitalisation across IT infrastructure, digital capability, training, and R&D. For example, builders primarily rely on cloud storage while designers use a combination of local and cloud storage. Designers allocate a higher percentage of their turnover to IT, whereas builders are twice as likely as designers to lack structured training for digital skills. When organisation size was considered independently, similarities were observed across sizes. These results provide insight into the current digitalisation landscape in construction, offering a foundation to support the adoption of future industry regulations.

Centralized Data Warehouse vs. Data Mesh: A Comparative Analysis of Modern Data Management Paradigms

This comprehensive article explores the evolving landscape of enterprise data management, focusing on comparing traditional centralized data warehouses and the emerging data mesh paradigm. As organizations grapple with exponential data growth, projected to reach 180 zettabytes by 2025 [1], the choice of data architecture has become increasingly critical. The article examines both approaches' core principles, advantages, and challenges, highlighting how centralized data warehouses offer strong consistency and governance [2, 8] but face scalability issues [3]. In contrast, data mesh provides enhanced flexibility and domain-specific optimization [4] at the cost of more complex governance [5]. Through a detailed comparative analysis, the study investigates the impact of these architectures on organizational control, scalability, adaptability to business needs, and data quality management. Furthermore, it explores the potential of hybrid approaches that aim to leverage the strengths of both paradigms. The research considers various factors influencing the selection of data management strategies, including organization size, data complexity, and industry-specific requirements. By synthesizing current literature and industry trends, this article provides data professionals and decision-makers with a nuanced understanding of modern data management paradigms, enabling them to make informed choices aligned with their specific business contexts and long-term data strategies.

New development: The implementation (gap) of senior civil service recruitment reform—a matter of organizational size?

IMPACT The article provides insights into public management reform by examining how organizational size affects public organizations’ ability to implement innovations. The case of Italy’s senior civil service recruitment reform is described to highlight strategies that address implementation gaps and mitigate the challenges faced by smaller organizations with limited administrative capacity and limited resources for innovation. For policy-makers, the findings underscore the need to design support mechanisms for smaller entities, balancing local flexibility with consistent central-level enforcement. The results emphasize the importance of collaboration to share best practices and jointly deliver services across public sector organizations, fostering economies of scale and scope, especially in a domain like public personnel policy.

Analysis of Product Quality and Customer Satisfaction: A Case Study of the Automotive Parts Industry

Purpose: The automobile parts industry is a technologically and capital-intensive industry with a vast supply chain that influences various related industries. Many Taiwanese automobile parts manufacturers are small to medium-sized enterprises, with a complete industry supply chain. They possess the advantages of small-scale, diversified, and flexible manufacturing, enabling them to compete internationally and potentially enter the supply chains of international car manufacturers. Good product quality is favored by customers, and there is a correlation between product quality and customer satisfaction. The design of product attributes is primarily aimed at meeting customer needs. To outperform competitors, companies can establish additional value in their products to actively please customers and even enhance customer loyalty. This study investigates the differences in demographic variables on product quality and customer satisfaction and analyzes the degree of correlation between the two variables. Research Methodology: This study adopts a questionnaire survey method as the tool for data collection. The questionnaire is designed based on the research objectives, focusing on customer satisfaction, to explore the satisfaction levels of the case company's relevant dimensions among existing customers and compare them with customer expectations, providing recommendations accordingly. The subjects of this study are companies in the automotive parts industry with a capital of over ten million. The questionnaire was distributed from April to May 2022, with a total of 170 questionnaires distributed and 157 collected, resulting in a response rate of 92.35%. Results: The study results indicate significant differences in gender, marital age, education level, and seniority concerning product quality and customer satisfaction, but no significant differences were found in the organizational size of the company. Subsequent Pearson correlation analysis reveals a Pearson correlation coefficient of 0.85, indicating a high correlation between product quality and customer satisfaction. This suggests that excellent product quality influences customer satisfaction. Limitations: This study focused on the case of the automotive parts industry to explore the differential analysis of product quality and customer satisfaction. The research results are only applicable to the automotive parts industry. Contribution: The study found a positive correlation between product quality and customer satisfaction. Therefore, the capability to enhance product quality, making products attractive and creating differentiated brand value, is actively pursued by companies as a development goal. The results of this study are consistent with previous research findings. With more streamlined product quality and detailed production history information, consumers' willingness to purchase increases. As consumer purchasing intention rises, so does brand loyalty, leading to increased profitability and surpassing competitors.

Varieties of climate activism: assessing public support for mainstream and unorthodox climate action in the United Kingdom

Abstract Is the UK public willing to financially support environmental organizations that adopt disruptive tactics (museum and art gallery protests, sporting event disruptions, and traffic stoppages), as opposed to orthodox tactics (litigation, lobbying, and research and education)? Using a conjoint choice experiment (N = 1,023; Nobs = 10,230), we asked respondents’ willingness to donate £25 to hypothetical environmental organizations that differ in terms of (1) advocacy tactics, (2) expenditure on administrative overheads, (3) representation of women on their boards, (4) organizational age, (5) organizational size, (6) number of volunteers, and (7) revenue from citizen donations. We find respondents’ willingness to donate diminishes when organizations adopt disruptive tactics. These results hold across party preferences, ideology, generation, location, and environmental policy attitudes. Further, respondents are willing to donate to organizations that rely on donations from the general public, have low overheads, are supported by volunteer labor, and provide representation to women on their boards.

AI-Powered Information Governance: Balancing Automation and Human Oversight for Optimal Organization Productivity

This study employs a mixed-methods approach to examine the optimal balance between AI-powered automation and human oversight in information governance frameworks, aiming to enhance organizational productivity, efficiency, and compliance. Quantitative data collected from 384 respondents were analyzed using Pearson correlation, regression models, and Structural Equation Modeling (SEM). The results reveal strong positive correlations between AI automation levels and both organization size (r = 0.55, p < .01) and AI adoption duration (r = 0.62, p < .01). Regression analysis indicates that higher levels of AI automation significantly improve error reduction (β = 1.12, p < .001) and compliance (β = 1.05, p < .001), especially in larger organizations with longer AI adoption periods. SEM findings highlight that human oversight positively impacts error reduction (β = 0.65, p < .001) and compliance improvement (β = 0.72, p < .001), and the interaction between human oversight and AI automation further enhances these outcomes (error reduction: β = 0.32, p < .001; compliance improvement: β = 0.35, p < .001). The qualitative analysis, involving thematic extraction from industry reports, reveals ethical challenges such as data quality issues, algorithmic bias, and privacy concerns. Hence, it is necessary to integrate human oversight to ensure ethical standards and build stakeholder trust in AI-driven systems. The study concludes with practical recommendations for organizations: establishing transparent AI governance frameworks, investing in continuous training for employees, and regularly auditing AI processes to mitigate risks. By addressing both the technological and ethical dimensions, organizations can implement AI-powered information governance that not only boosts productivity and efficiency but also ensures compliance and ethical integrity.

The Impact of the Difficult Economic Situation on the Operation of Slovak Companies in the Shadow of War

Purpose: The purpose of this study is to examine the organizational and human resource (HR) responses to the challenging economic conditions caused by the war and the COVID-19 pandemic. Given the limited evidence available on how organizations adapt to such crises, this research aims to develop a conceptual model and empirically investigate the influence of two specific factors: organizational size and direct economic ties with the Russian and Ukrainian markets. Methodology: This study employs a mixed-method approach, combining both theoretical and empirical research. A conceptual model was first developed to outline potential organizational reactions to crisis conditions. The empirical part of the study involved data collection from 128 organizations, including companies and institutions, in Slovakia. The analysis was conducted to test two hypotheses regarding how organizational size and economic connections with the Russian and Ukrainian markets affect organizational and HR responses in times of war. Findings: The findings of the study indicate that neither organizational size nor direct economic linkages with the Russian and Ukrainian markets significantly influenced the responses of the organizations studied to the economic difficulties caused by the war. This suggests that other factors may play a more critical role in shaping organizational and HR strategies in response to crises. Implications for theory and practice: For theory, this study contributes to the existing literature by challenging the assumption that organizational size and direct economic ties to conflict-affected markets are primary determinants of organizational responses to crisis. For practice, the findings suggest that managers and HR professionals need to consider a broader range of factors beyond size and market exposure when developing strategies to cope with economic disruptions caused by global crises. Originality and value: This research is original in its focus on the specific impacts of war and pandemic-induced economic conditions on organizations in Slovakia. The study provides valuable insights into how organizations navigate crises, expanding the understanding of crisis management and organizational adaptability. It adds value by highlighting the need for more comprehensive models that consider a wider array of factors influencing organizational behavior in times of global economic disruption.

We need to aim at the top: Factors associated with cybersecurity awareness of cyber and information security decision-makers.

Cyberattacks pose a significant business risk to organizations. Although there is ample literature focusing on why people pose a major risk to organizational cybersecurity and how to deal with it, there is surprisingly little we know about cyber and information security decision-makers who are essentially the people in charge of setting up and maintaining organizational cybersecurity. In this paper, we study cybersecurity awareness of cyber and information security decision-makers, and investigate factors associated with it. We conducted an online survey among Slovenian cyber and information security decision-makers (N = 283) to (1) determine whether their cybersecurity awareness is associated with adoption of antimalware solutions in their organizations, and (2) explore which organizational factors and personal characteristics are associated with their cybersecurity awareness. Our findings indicate that awareness of well-known threats and solutions seems to be quite low for individuals in decision-making roles. They also provide insights into which threats (e.g., distributed denial-of-service (DDoS) attacks, botnets, industrial espionage, and phishing) and solutions (e.g., security operation center (SOC), advanced antimalware solutions with endpoint detection and response (EDR)/extended detection and response (XDR) capabilities, organizational critical infrastructure access control, centralized device management, multi-factor authentication, centralized management of software updates, and remote data deletion on lost or stolen devices) are cyber and information security decision-makers the least aware of. We uncovered that awareness of certain threats and solutions is positively associated with either adoption of advanced antimalware solutions with EDR/XDR capabilities or adoption of SOC. Additionally, we identified significant organizational factors (organizational role type) and personal characteristics (gender, age, experience with information security and experience with information technology (IT)) related to cybersecurity awareness of cyber and information security decision-makers. Organization size and formal education were not significant. These results offer insights that can be leveraged in targeted cybersecurity training tailored to the needs of groups of cyber and information security decision-makers based on these key factors.

APPRAISE: a Governance Framework for Innovation with Artificial Intelligence Systems

As artificial intelligence (AI) systems increasingly impact society, the EU Artificial Intelligence Act (AIA) is the first legislative attempt to regulate AI systems. This paper proposes a governance framework for organizations innovating with AI systems. Building upon secondary research, the framework aims at driving a balance between four types of pressures that organizations, innovating with AI, experience, and thereby creating responsible value. These pressures encompass AI/technology, normative, value creation, and regulatory aspects. The framework is partially validated through primary research in two phases. In the first phase, a conceptual model is proposed that measures the extent to which organizational tasks result in AIA compliance, using elements from the AIA as mediators and strategic variables such as organization size, extent of outsourcing, and offshoring as moderators. 34 organizations in the Netherlands are surveyed to test the conceptual model. The average actual compliance score of the 34 participants is low, and most participants exaggerate their compliance. Organization size is found to have significant impact on AIA compliance. In phase 2, two case studies are conducted with the purpose of generating in-depth insights to validate the proposed framework. The case studies confirm the interplay of the four pressures on organizations innovating with AI, and furthermore substantiate the governance framework.

Unveiling the Nexus: Elevating marketing strategies for enhancing satisfaction and loyalty in elderly health care services

The study aimed to examine whether there is an association of marketing mix, and perception with customer’s satisfaction, and loyalty among elderly people. A total of 400 participants were included in the study. The study population comprised individuals aged 65 years and above from Assam, India including both males and females. Participants were primarily selected from residential homes, old age homes, and various common gathering places such as parks, shops, Namghar (a holy place), and community halls. The study indicated a significant correlation between the dimensions of the marketing mix, perception, satisfaction, and loyalty. Moreover, the findings from the linear regression analysis, revealed customer satisfaction towards the marketing of healthcare services can be attributed to product, price, place, process, and physical evidence (7 P’s) and customer perception (R2=.54; .53 respectively). Additionally, customer loyalty towards the marketing of healthcare services is influenced by product and price (7P’s), and customer perception (R2=.54; .2 respectively). This study contributes to understanding the overlooked aspect of marketing to the elderly population, providing valuable insights for healthcare companies to develop improved marketing strategies. Hence, irrespective of the organization's size, type, or location, whether it's a startup or an established entity, privately owned or government-operated, local or global, the role of business managers is vital in making informed decisions and establishing strategic priorities to allocate resources efficiently in order to meet evolving customer demands and achieve business success. As a result, commercial enterprises need to develop tools, concepts, and strategies to effectively navigate the dynamic and unpredictable marketing landscape.

Age Management Practices and Benefits in Organisation: An Evaluation of the Effect of Economic Sector, Organisation Size, and Family Business Status

Abstract Background The ageing of the population impacts all areas and is also a challenge for human resources management. To solve this issue, age management practices are used in organisations. To get the best potential out of everyone, this concept should not only involve older employees but should be focused on all of them. Choosing the right practice to get the desired results is a task for managers. Objectives The paper aims to determine whether the sector of the economy, the size of the organisation, or the family business status plays a role in determining age management practices and observed benefits. Methods/Approach Using a questionnaire survey, the most commonly used practices and the observed benefits were identified. Using the chi-square test, differences in chosen categories were confirmed. Results It can be stated that choosing age management practices is influenced by the economic sector, and the size of the organisation influences observed benefits. Conclusions The results can guide organisations on which practices to choose and what benefits to expect from implementing age management practices.

Understanding organizational resilience: A cross-country analysis of factors influencing organizational mortality

This study delves into organizational resilience by investigating the factors contributing to organizational mortality, with a focus on the interplay between internal (endogenous) and external (exogenous) influences. Drawing on concepts from organizational ecology, the research seeks to provide a clearer understanding of how these factors impact the survival and adaptability of organizations. The study employs advanced techniques such as data mining, multiple linear regression, and Multivariate Adaptive Regression Splines (MARSplines) to analyze both stimulators and inhibitors of organizational mortality. The findings reveal that internal factors, particularly organizational size, significantly increase mortality risks. This research offers a holistic approach by integrating insights from organizational ecology, finance, and management, providing a comprehensive view of how various factors interact to influence organizational resilience. It highlights the importance of understanding the non-linear and dynamic relationships between these factors over time, offering valuable insights for managers and strategists who aim to strengthen organizational survival. While the findings offer important implications, further research is recommended to validate the results and deepen our understanding of organizational mortality and resilience dynamics.

What do employers need when supporting stroke survivors to return to work?: a mixed-methods study

ABSTRACT Background Employers are key in supporting stroke survivors to return to work (RTW) but do not always have knowledge/skills or guidance to do so. Objectives To explore employers’ needs for provision of post-stroke RTW support. Methods Mixed-methods study. Participants recruited through voluntary response/purposive sampling. Survey of employers investigated stroke knowledge (maximum score: 7), RTW process knowledge (maximum score: 8), and perceived competency for actions supporting RTW (maximum score: 100%). Regression analyses explored relationships between employers’ demographic/contextual characteristics and knowledge and perceived competency scores. Interviews with employers explored factors influencing their post-stroke RTW support. Interview data were analyzed using a framework analysis. Survey/interview findings were synthesized with those from a qualitative systematic review. Results Across the survey (n = 50), interviews (n = 7), and review (25 studies), employers’ support was influenced by stroke survivors’ decisions to disclose stroke-related limitations, employers’ knowledge regarding roles/responsibilities, employers’ communication skills, and information provided by healthcare. Regression analyses: Human resources/occupational health support was positively associated with stroke knowledge (ß = 2.30, 95% CI 0.36–4.41, p = 0.013) and RTW process knowledge (ß = 5.12, 95% CI 1.80–6.87, p = 0.001). Post-stroke RTW experience was positively associated with stroke knowledge (ß = 1.36, 95% CI 0.46–2.26, p = 0.004) and perceived competency (ß = 31.13, 95% CI 18.40–44.76, p = 0.001). Organization size (i.e. working in a larger organization) was positively associated with RTW process knowledge (ß = 2.96, 95% CI 1.52–4.36, p = <.001). Conclusions Employers’ RTW support was influenced by personal and environmental factors; they may benefit from education and guidance on stroke and their roles/responsibilities during the RTW process.

Unlocking the Synergy: Increasing productivity through Human-AI collaboration in the industry 5.0 Era

The prevailing trajectory of technological evolution emphasizes the sustainable development of human-AI collaboration. In this study, we employ the coupling coordination degree model to evaluate the dynamics of human-AI collaboration in China and match it with listed companies. Through panel models, the study not only quantifies the contribution of such collaboration to enhancing company input–output efficiency but also explores how it serves as a catalyst for technological catch-up. Our findings indicate that the integration of human capital with AI emerges as a potent driver of company efficiency, with the extent of the impact also tied to organizational characteristics. Furthermore, the scale of investment and organizational size play a crucial role in the effectiveness of HIC, underscoring the adaptability of human-AI collaboration strategies to various organizational contexts and the importance of tailored implementation. Our research highlights the inherent collaborative potential of AI within the Industry 5.0 framework, advocating for the fusion of human creativity with AI precision to foster a development paradigm that is resource-efficient, cost-effective, and human-centric.