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Based on the perspective of knowledge management capability, this paper aims to reveal the internal mechanism of the digital empowerment of mobile social platforms to improve the operational performance of Chinese traditional retail enterprises. Such improvements have crucial theoretical value and practical implications for Chinese traditional retail enterprises to achieve transformation and sustainable development.

This study applied the typical analysis method, selected China’s leading mobile social platform, WeChat, as a typical case, and observed and analyzed the public data of the traditional retail industry and social platforms and interviews with relevant enterprises. On this basis, this study used the inductive and deductive methods of qualitative research to conduct an in-depth analysis of the mechanism by which WeChat’s digital empowerment improves the operational performance of Chinese traditional retail enterprises. It also discussed the critical role and path knowledge management capabilities play in this mechanism.

This research demonstrated that mobile social platforms empower Chinese traditional retail enterprises to build diversified digital channels, enhance the knowledge acquisition capability of enterprises and thus improve their performance; empower Chinese traditional retail enterprises to build digital community networks, enhance the knowledge diffusion capability of enterprises and thus improve their performance; and empower Chinese traditional retail enterprises to integrate online and offline businesses, enhance the knowledge integration capability of enterprises and thus improve their performance.

This study clarifies the internal mechanism of how the digital empowerment of mobile social platforms can improve the performance of Chinese traditional retail enterprises. This mechanism implies that knowledge management capabilities (knowledge acquisition, diffusion and integration capability) are the underlying logic for Chinese traditional retail enterprises to achieve higher performance levels. This has important practical implications for managers of Chinese traditional retail enterprises to leverage the digital infrastructure of mobile social platforms to achieve the sustainable development of enterprises.

This study provides an in-depth analysis of how the traditional retail industry uses digital social platforms to improve operational performance from the perspective of knowledge management capabilities, which can further promote the theoretical research and practical development of digitalization and knowledge management. At the same time, this study explored the research on the operational performance of Chinese traditional retail enterprises from the perspective of knowledge management capabilities and expanded the research on knowledge management in related fields. The authors have initially sorted out the impact of knowledge management capabilities on the operational performance of Chinese traditional retail enterprises in the digital era. This will help better understand the role and function of knowledge management in strategic transformation and expand the application of knowledge management theory.

Although the use of artificial intelligence (AI) has been estimated to be up to 56% in the last decade, the adoption rate of AI for communication activities is still low. The lack of in-depth literature on the subject, and the limited sharing of the experience gained by companies, limits the creation, dissemination and consolidation of understanding in this area. The purpose of this study is to solve the problem of the absence of knowledge, identification, skills development and introduction of an innovation (such as the AI in the business communication) in the company, with the principles of knowledge management (KM).

This study adopts the perspective of KM to provide guidelines for the definition of standards and facilitate the introduction of AI in business communication.

To the best of the authors’ knowledge, this study is the first to relate the perspectives of business communication, AI and KM, activating a virtuous circle between KM and AI. At the centre of the proposed model are people, processes and technologies, based on which KM represents the ideal perspective to define the implementation of AI. This is primarily from the perspective of augmented intelligence, owing to the inability of AI to completely replace humans in the business communication processes, as it lacks, among others, emotional intelligence.

This study finds in KM a possible strategy to solve the problems faced so far in applying AI in business communication processes, providing a model capable of transforming and adapting itself to the context, thanks to the open approach.

This study contributes to the literature by linking the introduction of emerging technology (AI) in a specific process, such as business communication, from the KM perspective.

This study aims to examine the impact of the COVID-19 pandemic on knowledge-sharing drivers in small- and medium-sized family firms within the restaurant and fast-food industry. The pandemic has led to significant changes in business culture and consumer behaviour, accelerating digital transformation, disruptions in global supply chains and emerging new business opportunities. These changes have also influenced knowledge sharing (KS) and its underlying drivers.

To address the research objectives, a two-phase study was conducted. In the first phase, an exploratory analysis using the Delphi method was used to identify the essential drivers and factors of KS in family businesses (FBs). This phase aimed to establish a conceptual model for the study. In the second phase, confirmatory factor analysis was conducted to analyse the impact of the COVID-19 pandemic on the identified knowledge-sharing drivers. The study examined both the pre-pandemic and post-pandemic periods to capture the shifts in attitudes towards KS.

The findings indicate a significant shift in attitudes towards knowledge-sharing drivers. Before the pandemic, organisational drivers played a central role in KS. However, after the emergence of the pandemic, technological drivers became more prominent. This shift highlights the impact of the COVID-19 pandemic on KS within FB.

The research contributes to understanding knowledge-sharing in the context of FBs and sheds light on the specific effects of the COVID-19 pandemic on knowledge-sharing drivers. The insights gained from this study can inform strategies and practices aimed at enhancing KS in similar organisational settings.

The purpose of this paper is to satisfy a clear gap in the main field of open innovation research whereabouts a very little scholarship try to analyze the mechanisms of innovative milieu down smart cities environments by applying through innovative projects that seem to support efficiently the entry of private firms and citizens in public collaborations.

The research performed an exploratory and qualitative evaluation based on the case study method built on the evaluation of organizational behavior and urban boosting innovation through smart city initiatives. In doing so, after a literature review in smart city as well in lean methodology fields, the case of Turin Smart City follows.

As acknowledged by international literature, the paper shows how a lean approach enables local government to define and realize smart projects and initiatives in a faster and more effective way. Particularly, the government in one of the main cities in Italy, id est Turin, combines a lean methodology with the job-to-be done approach, according a new concept of smart initiatives involving a startup mentality for the lead users which enables interesting predictions relating the human aspects of open collaborations.

The specificity of this inquiry highlights valuable insights from double-gate smart cities’ innovation, social and urban as well. The research is largely interpretative and exploratory and while this provides a solid scientific foundation for further research, it does not, itself, subject any hypothesis to statistical testing and validation.

Since the city approached the smart city subject in a lean way, it was able to realize some projects in a faster way. Through specific initiatives, the city acquires the ability to involve more and better all its stakeholders such as citizens, companies, and public employees, among others. In this regard, the paper invigorates managerial debates concerning the urban and social aspects of open innovation ecosystems which represent in our minds a superior level of open innovation, testbeds of positive knowledge, and stimulus of knowledge dissemination process around the city.

The aim of this work is to increase awareness of the potential of the technique of text mining to discover knowledge and further promote research collaboration between knowledge management and the information technology communities. Since its emergence, text mining has involved multidisciplinary studies, focused primarily on database technology, Web-based collaborative writing, text analysis, machine learning and knowledge discovery. However, owing to the large amount of research in this field, it is becoming increasingly difficult to identify existing studies and therefore suggest new topics.

This article offers a systematic review of 85 academic outputs (articles and books) focused on knowledge discovery derived from the text mining technique. The systematic review is conducted by applying “text mining at the term level, in which knowledge discovery takes place on a more focused collection of words and phrases that are extracted from and label each document” (Feldman et al., 1998, p. 1).

The results revealed that the keywords extracted to be associated with the main labels, id est, knowledge discovery and text mining, can be categorized in two periods: from 1998 to 2009, the term knowledge and text were always used. From 2010 to 2017 in addition to these terms, sentiment analysis, review manipulation, microblogging data and knowledgeable users were the other terms frequently used. Besides this, it is possible to notice the technical, engineering nature of each term present in the first decade. Whereas, a diverse range of fields such as business, marketing and finance emerged from 2010 to 2017 owing to a greater interest in the online environment.

This is a first comprehensive systematic review on knowledge discovery and text mining through the use of a text mining technique at term level, which offers to reduce redundant research and to avoid the possibility of missing relevant publications.

This study aims to identify and assess the key ethical challenges associated with integrating artificial intelligence (AI) in knowledge-sharing (KS) practices and their implications for decision-making (DM) processes within organisations.

The study employs a mixed-methods approach, beginning with a comprehensive literature review to extract background information on AI and KS and to identify potential ethical challenges. Subsequently, a confirmatory factor analysis (CFA) is conducted using data collected from individuals employed in business settings to validate the challenges identified in the literature and assess their impact on DM processes.

The findings reveal that challenges related to privacy and data protection, bias and fairness and transparency and explainability are particularly significant in DM. Moreover, challenges related to accountability and responsibility and the impact of AI on employment also show relatively high coefficients, highlighting their importance in the DM process. In contrast, challenges such as intellectual property and ownership, algorithmic manipulation and global governance and regulation are found to be less central to the DM process.

This research contributes to the ongoing discourse on the ethical challenges of AI in knowledge management (KM) and DM within organisations. By providing insights and recommendations for researchers, managers and policymakers, the study emphasises the need for a holistic and collaborative approach to harness the benefits of AI technologies whilst mitigating their associated risks.

The primary objective of this research is to draw a comparative analysis between Turkey and Italy in terms of how festival events function as catalysts for the endorsement of regional culinary delicacies. The study endeavours to elucidate the role of these festivals in fortifying the regional gastronomic landscape of both nations.

Adopting a comprehensive comparative methodology, this study meticulously scrutinises the gastronomy festivals spanning diverse geographical locales in both Turkey and Italy. Consideration is given to the standout food and beverage items spotlighted at these events and the venues where they are hosted. The research design takes into account the extensive cultural and geographical spectrum that characterises Turkey and Italy. The primary research method comprises web content analysis techniques. This method involves analysing textual data from online sources pertaining to gastronomy festival events in both countries. Web content analysis is instrumental in evaluating how such festivals are deployed in promoting indigenous gastronomic products and exploring the intricate dynamics between brand identity and brand image.

The research outcomes underscore the pivotal role that festival events play in elevating regional gastronomic products' profile in Turkey and Italy. It highlights the top 10 festivals and the most popular local culinary items on digital platforms. Additionally, the study offers a side-by-side comparison of the most celebrated gastronomic products in Turkey versus those that receive prominence in Italy.

This study enriches academic understanding by dissecting the nuances of how festivals contribute to the promotion of local gastronomic treasures. By juxtaposing Turkey and Italy, this research provides valuable insights into the influence of festivals on regional culinary promotion across diverse cultural milieus. This study makes substantial contributions to the fields of gastronomy, tourism, and brand promotion.

Massive open online courses (MOOCs), a Taylorist attempt to automate instruction, help make course delivery more efficient, economical and better. As an implementation of Digital Taylorism Implementation (DTI), MOOCs enable individuals to obtain an occupation-oriented education, equipping them with knowledge and skills needed to stay employable. However, learning through online platforms can induce tremendous amounts of technology-related stress in learners such as complexity of platforms and fears of redundancy. Thus, the aim of this paper is to study how student perceptions of DTI and technostress (TS) influence their perceived employability (PE). The role of TS as a mediator between DTI and PE has also been studied.

Stratified sampling technique has been used to obtain data from 305 students from 6 universities. The effect of DTI and TS on PE, and the role of TS as a mediator, has been examined using the partial least squares (PLS) structural equation modelling approach with SMART PLS 4.0. software. Predictive relevance of the model has been studied using PLSPredict.

Results indicate that TS completely mediates the relationship between DTI and PE. The model has medium predictive relevance.

Learning outcomes from Digitally Taylored programs can be improved with certain reforms that bring the human touch to online learning.

This study extends Taylorism literature by linking DTI to PE of students via technostress as a mediator.

The importance of knowledge-based assets and the capability to leverage them has been the subject of scholarly interest in entrepreneurial orientation literature. The authors attempt to understand the dominant themes in the prior literature and propose directions for future research.

The authors performed a systematic review of 79 studies to answer the research questions: (1) What are the predominant themes in the literature on the role of intellectual capital and entrepreneurial orientation? (2) What are the potential fields of future research?

The findings suggest that current research engages the topics of intellectual capital, the capability to leverage knowledge assets and entrepreneurial orientation. The thematic analysis reveals the role of knowledge management, organizational learning, intellectual capital and absorptive capacity in entrepreneurial firms. The authors propose a theoretical model to explain how intellectual capital and its management influence firm-level entrepreneurial behavior.

Understanding the association between intellectual capital and the capability to leverage knowledge assets is crucial in a dynamic business environment. Effective deployment of knowledge is vital while searching for new entrepreneurial opportunities.

The purpose of this paper is to contribute to the ongoing debate regarding the relationship between relational capital (RC) and firm performance, by investigating the moderation effect of firm size and its key role in defining conditions for competitive advantage.

The paper uses the interpretative lens of the resource dependence theory, and refreshes consolidated studies rooted in RC. It identifies a set of variables to measure the influence of RC on firm performance, including the cost of goods sold, interest expenses and earnings per share. Content analysis was used to capture specific features of corporate disclosure tools using 51 items pertinent to RC. The authors used a specific disclosure index drawing on data collected from 73 listed firms in France, Germany, Italy and the UK. Data covering the period from 2011 to 2013 were analyzed using six regression models.

Firm size has a moderating effect on the relationship between RC and some variables linked to firm performance.

The study combines an internal and external perspective to investigate the interplay between firms and market environments, and therefore, enriches the ongoing debate concerning the relationship between RC and firm performance. It outlines possible ways through which RC can become an effective source of competitive advantage.