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This study aims to evaluate an artificial intelligence (AI) capability scale using resource-based theory and tests its impact on dynamic capabilities and organizational creativity to influence the performance of public organizations.

The study used qualitative and quantitative methods to develop and validate an AI capability scale using an integrative psychometric approach. An initial set of 26 items was selected from the literature for qualitative analysis. Self-reported data from 344 public managers in United Arab Emirates public organizations were used for scale refinement and validation. Hypotheses were tested against theoretically related constructs for nomological validation.

A 23-item AI capability scale was developed. Nomological testing confirmed that AI capability positively and significantly enhances dynamic capabilities, which in turn boosts organizational creativity and improves organizational performance.

Previous information system literature has not sufficiently addressed the importance of organizational-level complementary resources in developing distinctive capabilities within public organizations. Grounded in resource-based theory and recent AI research, this study provides a framework for public sector organizations to assess their AI capabilities. The findings empirically support the proposed theoretical framework, showing that AI capability increases dynamic capabilities, organizational creativity and performance.

Based on the job-demands resources (JD-R) model and the self-determination theory (SDT), this paper aims to explore team empowerment (TEMP) as a mediating mechanism through which team climate (TC) marked by innovativeness, cohesion and trust and knowledge management (KM) in teams.

Using a convenience sampling method, data were gathered from 246 employees of Tunisian knowledge-intensive firms (KIFs) and involved within 69 R&D teams. The partial least square-structural equation modeling approach through SMART PLS 3.2 software was used to evaluate the constructs’ psychometric properties and hypotheses. The mediating effect in the model was evaluated through the non-parametric bootstrapping method.

Results highlight that TC marked by innovativeness, cohesion and trust represents a key team contextual antecedent promoting TEMP and KM in teams. In turn, TEMP, as a critical intrinsic task motivation factor, is revealed as a driver of KM practices. This research demonstrates that TEMP partially mediates the relationship between TC and KM in teams.

This study pioneers the examination of TEMP’s mediating role between a TC marked by innovativeness, trust and cohesion and KM. By applying insights from the JD-R model and SDT to team-level dynamics, it uniquely positions TEMP as an intrinsic motivational factor explaining the mechanism through which the contextual resources provided by a supportive TC promote KM practices. It provides practical insights for KIFs’ managers through highlighting how intrinsically motivated teams of knowledge workers, empowered by a cohesive, innovative and trust-based TC, can effectively navigate the challenges inherent in knowledge-intensive teamwork, leading to enhanced KM practices.

This chapter investigated tendering in stealth construction, emphasising innovative approaches and methodologies that prioritise environmental protection, safety, efficiency, and aesthetics. It began with an overview of the construction industry’s tendering processes, followed by an in-depth examination of various tendering types, including competitive and negotiated methods. The study highlighted contemporary trends such as electronic tendering, Building Information Modelling (BIM), green and sustainable procurement, risk management, data analytics, artificial intelligence, lean construction practices, and blockchain technology. Moreover, with a specific focus on stealth construction, the chapter further analysed certain criteria, including building cross-section development, visibility, radio frequency emission, and countermeasures. It explored integrating functional construction systems, including environmental, safety, health, and quality management. Additionally, it discussed methods like green building, modular construction, and low-impact techniques. Lastly, the chapter emphasised the strategies to achieve environmental protection, safety, speed, economy, and aesthetics in tendering for stealth construction.

This study aims to explore the constituents of artificial intelligence (AI)-augmented knowledge management (AIKM) capability and its impact on clinical performance (CP) in the health-care sector. It further examines the mediating role of absorptive capacity (Abs Cap) and discusses the implications of these findings for marketing strategies, highlighting how enhanced CP through AIKM can lead to more effective and patient-centered marketing approaches.

This research uses a mixed-method design. A qualitative study through semi-structured interviews was conducted to explore the facets of AIKM. The synthesis of qualitative findings infused with the relevant literature to develop a hypothesized model of AKM, Abs cap and CP metrics (e.g. diagnostic accuracy, patient satisfaction and treatment effectiveness). A survey of health-care professional in India was conducted to assess the proposed model by using structural equation modeling (PLS-SEM).

The results demonstrate a significant positive relationship between AIKM and CP. Moreover, Abs Cap mediates this relationship partially, highlighting its crucial role in translating improved knowledge access and analysis enabled by AI into enhanced clinical outcomes.

The findings suggest that health-care organizations should invest in developing AIKM alongside strengthening Abs cap to maximize the positive impact of AI on CP and ultimately improve patient care. Future research can explore specific AIKM components and Abs cap facets influencing different aspects of CP.

This study represents a pioneering effort to conceptualize AIKM within the health-care context and empirically establish it as a higher-order factor. The inclusion of marketing strategies underscores the potential of AIKM not only in improving clinical outcomes but also in transforming health-care marketing. The mediating role of Abs Cap emphasizes the importance of organizational structures and processes that facilitate the absorption and utilization of knowledge, thereby contributing to both clinical and marketing excellence.

Small-to-medium-sized enterprises (SMEs) in e-commerce often invest in information technology (IT) to stay competitive. However, whether and how IT capability (ITC) translates into financial performance requires further research. This paper examines the role of ITC in enabling value proposition innovation (VPI) as an important mechanism that improves financial performance for Chinese e-commerce SMEs during the COVID-19 pandemic. We argue that ITC is critical for enabling innovation because it elevates SMEs’ understanding of changing customer needs, especially when SMEs operate on multiple e-commerce platforms (multihome).

We used partial least squares structural equation modeling (PLS-SEM) and tested the hypotheses that ITC mediated by VPI and moderated by multihoming increases the financial performance of e-commerce SMEs through a survey among 206 Chinese SMEs operating on Taobao.

We find that not only higher levels of ITC lead to better financial performance, but also that the effect is fully mediated by VPI. Moreover, the effect of ITC on innovation is enhanced when vendors operate on multiple platforms.

The study identifies VPI as an important mechanism through which SMEs can leverage their ITC to adapt, innovate and thrive in competition. Our work suggests that using technology to develop innovative ideas and identify opportunities (which are reflected in VPI) is key to success and that doing so is more likely when vendors multihome. Thus, this study contributes to the innovation literature by explicating a concrete link between ITC, multihoming, VPI and increased financial performance. Different e-commerce stakeholders, including SME owners, IT and service providers and e-commerce platforms, can benefit from the findings of this work.

This study aims to understand how product attributes (object stimuli), social influences (social-psychological stimuli) and internal factors (internal stimuli) contribute to Chinese Generation Z’s purchase intentions (responses) for new Chinese style apparel (NCSA) through NCSA attitudes (cognitive state) and cultural pride (affective state) based on the stimulus-organism-response (S-O-R) model.

Data were collected from 989 respondents aged between 18 and 29 years through self-administrated questionnaires via a professional survey panel, Credamo, in China. Data were analyzed using structural equation modeling.

Results showed that among the seven stimuli, NCSA’s design, online social networking communities, cultural identity and personal norms significantly influenced Generation Z’s purchase intentions through both NCSA attitudes and cultural pride. Further, NCSA’s cultural connotations and celebrity influences elicited purchase intentions merely through the affective state – cultural pride. In contrast, NCSA’s functionality did not have a significant influence on NCSA attitudes and adversely affected cultural pride.

This study fills the research gap and extends the application of the S-O-R model within the NCSA context. The findings of this study shed light on the practical implications for marketers, brands and policymakers with regard to a better understanding of Chinese Generation Z’s NCSA consumption.

This study explores the impact of digital technologies and digitalization management on digitalization performance in Lithuanian manufacturing firms, aiming to unravel the dynamics between digital technology adoption and managerial capabilities in enhancing digitalization performance.

Employing partial least squares structural equation modeling (PLS-SEM), the research analyzes data from a survey of 506 Lithuanian manufacturing firms, focusing on their digitalization strategies and outcomes.

The findings reveal that while digital technologies alone do not directly influence digitalization performance, digitalization management significantly mediates this relationship, highlighting the pivotal role of managerial practices in maximizing the benefits of digital technologies.

The study acknowledges limitations in its scope, primarily focusing on Lithuanian manufacturing firms, which may affect the generalizability of its findings to other sectors or geographical contexts.

The study offers valuable insights for practitioners and managers, underscoring the importance of strategic management in leveraging digital technologies for enhanced digitalization performance and providing a roadmap for more effective digital transformation practices.

This research elucidates the intricate dynamics between digital technologies, digitalization management and digitalization performance, revealing a pivotal mediating role of digitalization management. It notably demonstrates that digital technologies, contrary to expectations, do not directly influence digitalization performance, underscoring the essential function of digitalization management in harnessing digital technologies for enhanced performance.

This research paper aims to explore the added value of knowledge management (KM) and its antecedents for innovation and organizational performance (OP) in marginal healthcare organizations.

Using insights from the resource-based view and knowledge-based theory of the firm, the model explains the effects of technology capabilities (TC) and organizational culture (OC) on the KM process, process innovation (PIN), administrative innovation (AIN) and OP. The authors used partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to analyze data collected from 168 healthcare practitioners in Cameroon using a survey.

The authors reveal that TC and OC positively impact some KM components. Knowledge sharing (KS), knowledge acquisition (KA) and responsiveness to knowledge (RK) influence PIN, while only PIN and KA influence OP. FsQCA provided several configurations that lead to high OP within healthcare centers. As a result, the results are adaptable to any healthcare center that wishes to set up one or more KM processes.

Given that the results will help the health workforce make concerted decisions about medical care, the authors contribute significantly to the definition and optimization of KM in healthcare by implementing various processes and policies to ensure the continued existence of high-quality and outstanding healthcare systems. The KM propositions will enable healthcare centers to: (1) improve the quality of patient care through collegiality in medical practice; (2) optimize processes in the patient care chain; and (3) leverage knowledge gained though knowledge sharing among the medical team. The propositions open up avenues for future research in addition to providing practical implications for healthcare center practitioners.

This study sheds new empirical light on the relationships between KM antecedents and processes, innovation and OP in healthcare centers. This research is one of the few to examine the relationship between TC, OC, KM processes, innovation and OP in developing countries. This paper aims to fill this gap and inform future research concerning KM in the healthcare sector. Further, this study goes beyond testing the PLS-SEM approach's hypotheses by applying fsQCA to provide practical and comprehensive knowledge on how to increase the efficiency of a healthcare center through KM.

The purpose of our research is to explore the role of employee AI identity in influencing employee proactive behavior and its boundary conditions in AI workplace.

Based on the IT identity theory and motivation theory, our research discusses the effects of employee AI identity on employee proactive behavior and regarded the proactive work intention as a mediating variable. Meanwhile, we considered organization inducement as a boundary condition and discussed the moderating effects of it and its two sub-dimensions (development rewards and material rewards). Data were collected from 326 employees and partial least squares structural equation modeling was used to analyzed and draw the conclusions.

Findings showed that employee AI identity significantly affects employee proactive behavior, in which the proactive work intention play a mediating role. Moreover, three subdimensions (relatedness, emotional energy, dependence) of employee AI identity have different effects on formation of employee AI identity. And organization inducement acts as a positive moderating role, development rewards and material rewards play different roles in the formation of organization inducements.

Our research explores the different paths that influence employee proactive behavior and their boundary moderation, while analyzing the results of these influences in different subdimensions, deepening the research on employee AI identity and organization inducement. Our research is conducive to the development of the identity theory and organizational behavior research and provide suggestions for managers to improve their organizational management level.

Sustainability indicators that allow integrated farm assessments have received increasing attention. However, limited evidence is available for the use of the same when assessing the agricultural sustainability of farming systems, especially in regions practising incessant monoculture. Therefore, this study aims to develop a holistic index to assess alternative farming systems based on a stock-and-flow framework.

A composite metric was developed by aggregating the economic, social and environmental indicators. The methodology involved estimation, normalisation, hierarchical weighting and progressive aggregation of indicators to form the Comprehensive Farm Assessment Index (CFAI). The CFAI was applied to assess the farming practices of 88 organic and 90 conventional farming plots across three agro-climatic zones over two cropping seasons in selected districts of Punjab, India.

Results showed statistical mean differences between the organic and conventional farming systems in terms of key production costs and income for wheat, rice and cotton crops. The normalised values of the selected social indicators were higher for the organic farming system. Similarly, in the environmental dimension, more biodiversity and less water contamination were found in organic farms. Except for paddy cultivation in the North–East region, the CFAI for organic farming is higher than that for conventional farming, even under the mono-cropping system with a single-crop rotation.

The CFAI has ubiquitous applications and can be used to assess alternate sustainable approaches and practices across crops and regions. It provides a perspective on the social viability and ecological sustainability of agriculture, which would enable contextual and effective policy analysis and implementation.