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The purpose of the study is applying and comparing models that predict optimal time for new product exit based on its demand pattern and survivability. This is to decide whether or not to continue investing in new product development (NPD).

The study investigates the optimal time for new product exit within the hi-tech sector by applying three models: the dynamic learning demand model (DLDM), the generalized Bass model (GBM) and the hazard model (HM). Further, for inter- and intra-model comparison, the authors conducted a simulation, considering Weiner and exponential price functions to enhance generalizability.

While higher price volatility signifies an unstable technology, greater investment into research and development (R&D) and marketing results in higher product adoption rates. Imitators have a more prominent role than innovators in determining the longevity of hi-tech products.

The study conducts a comparison of three different models considering time-varying parameters. There are four scenarios, considering variations in advertising intensity and content, word-of-mouth (WOM) effect, price volatility effect and sunk cost effect.

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.

Process mining (PM) specialises in extracting insights from event logs to facilitate the improvement of an organisation's business processes. Industry trends show the proliferation and continued growth of PM techniques. To address the minimal attention given to developing empirically supported frameworks to assess the nature of impact in the PM domain, this study proposes a framework that identifies the key categories of PM impacts and their interrelationships.

The qualitatively derived framework is built, re-specified and validated from a diverse collection of 62 PM case reports. With multiple rounds of coding supported by coder corroborations, inductively extracted concepts relating to impact from a first set of 12 case reports were grouped into themes and sub-themes to derive an a-priori framework by adopting the balanced scorecard as a theoretical lens. Concepts from the remaining 50 case reports were deductively grouped to re-specify and validate the proposed PM impacts framework. Further analysis identified interrelationships between impacts, which extends our understanding of the identified PM impacts.

The proposed framework captures PM impacts in four main categories: (a) impact on the process, (b) customer impact, (c) financial impact, and (d) impact on innovation and learning. The authors extended this analysis to identify the interrelationships between these categories, which vividly demonstrates how impact on the process mediates the attainment of the other three impact types.

The need for a deeper understanding of PM impacts within the context of contemporary PM practice is addressed by this work. The PM impacts framework provides a classification of PM impacts into four categories with 19 subcategories. It also identifies direct, moderating and mediating relationships between categories and subcategories whilst highlighting the role of impact on the process as a precursor to the other types of PM impact.

Although scaling is considered a “hot topic”, very little is known about how knowledge management (KM) assists in scaling social impact. To fill this gap, the authors draw on knowledge-based and social capital theories and investigate how various KM practices and external networks (e.g. bridging social capital) affect scaling social impact in developing countries.

Applying structural equation modeling (SEM) with AMOS version 23, the authors conducted a survey with 354 women leaders who are working in women-led social enterprises in Dhaka, Bangladesh.

The authors found that knowledge codification, training and mentoring, and bridging social capital are positively and significantly associated with scaling social impact.

This is one of the pioneering study that explore how KM impacts scaling social impact for women-led social enterprises in the context of a developing country. The authors also extend knowledge-based theory by applying it at the individual level. Finally, the authors enhance the understanding of women entrepreneurship by showing that women entrepreneurs in developing countries are also utilizing bridging social capital to overcome challenges associated with scaling social impact.

The purpose of this paper is to provide a comprehensive review of scholarly literature on community-based enterprise (CBE) through a bibliometric analysis and to comprehend the qualitative dimensions of research in this specific field.

The study is based on scholarly papers indexed in Scopus from 1990 to 2021. The bibliometric analysis focuses on journals, documents, writers, organizations and countries. VOSviewer is used for network visualization mapping of citation, co-citation, bibliographic coupling and co-occurrence of keywords.

The analysis of the bibliometric aspects of CBE literature reveals an upward trend in publication of CBE documents, with a significant increase of research productivity in the past few years. This behaviour shows that CBE is becoming increasingly popular among academics and practitioners. The document “Toward a theory of community based enterprise” by Ana Maria Peredo is the most cited document. USA has so far published the maximum number of documents in this field.

This study provides an overview of the current state of research in the subject as well as the primary themes explored in this burgeoning discipline, with the potential to help the researchers identify new topics and gaps that need to be investigated further.

This work contributes to the literature by conducting a bibliometric analysis that has not yet been explored. It gives an overview of the field’s organization as well as specifics on the major issues explored in this discipline.

The purpose of this paper is to structure existing research on knowledge management (KM) in small- and medium-sized enterprises (SMEs) to offer a comprehensive overview of research strands and topics in KM in SMEs to determine their evolution over time.

The paper, which is considered a follow-up literature review, is based on a systematic literature review that covers 180 scientific papers that were published since the review paper by Durst and Edvardsson in 2012 that covered 36 papers.

The findings of this review and those of the aforementioned review are brought together in the form of an overview that structures research on KM in SMEs based on themes that, in turn, allow the derivation of promising research directions and research questions aimed at structuring future research on KM in SMEs.

By combining the findings of this review with the findings from the review published in this journal in 2012, this paper offers, to the best of the authors’ knowledge, the most comprehensive literature review on KM in SMEs produced to date.

The purpose of this study is to offer the bibliometric analysis of the Journal of Knowledge Management (JKM) to understand how the literature has developed over time.

This study used bibliometric approaches to analyze a sample of 669 studies from 1997 to 2021. This study focused on performance analysis and scientific mapping of articles using the R package.

The results indicate that the number of publications during the period has significantly increased which shows a growing interest of researchers in the JKM. This study highlights new emerging themes such as change management, change readiness, product innovation and digital libraries which uncover exciting avenues for new research opportunities. USA and UK were the most productive countries in terms of the number of citations followed by few European countries including Spain, Finland, Germany and Sweden. However, it is worth noting that India was the most productive country in the emerging economies.

This study will act as a guide for researchers of various fields to evaluate the development of scientific publications in a particular theme over time, especially for those who are in the field of knowledge management (KM).

This study aims to accomplish the systematic bibliometric analysis of the JKM for more than two decades, providing useful insights into the key developments in the field of KM. This study is more rigorous and comprehensive in terms of the analytical techniques used.

The purpose of this study is to identify the relationship between collaborative innovation and the financial performance of information technology (IT) firms through the mediating role of strategic agility and absorptive capacity. Customer knowledge management capability (CKMC) is also explored as a potential moderator.

Data were collected from 300 respondents working in different small to medium IT enterprises operating in different cities around Portugal. The simple random sampling method was used for data collection, and Smart partial least squares-structural equation modeling (Smart PLS-SEM version 3.2.8) was used to test the hypotheses.

The findings demonstrate that collaborative innovation contributes significantly to the financial performance of IT firms in Portugal. The results also indicate that absorptive capacity and strategic agility both positively and significantly affect the relationship between collaborative innovation and firms’ financial performance. However, while the moderating role of CKMC has a positive and significant effect on the relation between collaborative innovation and strategic agility, CKMC insignificantly moderates the relation between collaborative innovation and absorptive capacity.

Few studies have explicitly connected collaborative innovation with firms’ financial performance; this study attempts to fill that gap. Moreover, this research investigates the mediating role of strategic agility and absorptive capacity in the relationship between collaborative innovation and financial performance. Finally, by discussing the moderating effect of CKMC, which leads to enhanced financial performance, this study proposes that when complex and unpredictable situations occur, managers should focus on customer-oriented strategies and innovation at the same time to outpace their competitors.

The purpose of this study was to ascertain organizational factors that impacted the performance of social enterprises.

For this research study, a structured close-ended survey questionnaire was prepared based upon literature inputs. The data was collected from 370 executives in social enterprises in India. The data was analysed through structural equation modelling.  The data was analysed towards hypothesis development as well as model development explicating the success of social enterprises.

This research study’s findings developed a model towards explicating firm level performance in social enterprises. The antecedent factors were organizational commitment (OC), organizational orientation (OO), employee empowerment (EE) and top management support (TMS). The factor business innovation capability (BIC) was the mediating variable, whereas the firm performance (FP) of social enterprises was the dependent variable. Business innovation creativity had full mediation effect.

In this research study, the variable influencing the performance of social enterprises were ascertained. TMS and EE were independent organizational variables in any social enterprise along with the two organizational factors of OC as well as OO that did matter for enhancement of BIC of social enterprises. BIC had full mediating effect based upon the mentioned factors of OC, organization orientation, EE and TMS, which subsequently manifested in superior social enterprises FP.

Social enterprises had to balance the twin objectives of social good (doing good for society) as well as earning economic benefits for the enterprise.  Given this challenge, social enterprises had to develop an organizational context in which employees were empowered towards undertaking social issues proactively. Furthermore, top management team must provide support for such causes. When this aspect coupled with the presence of OC and OO then in the social enterprise, BIC got developed.  With the presence of BICs, it became easier for social enterprises to undertake innovation that were also socially oriented and led to superior FP.

It has often been observed in developing countries like India that social innovation and entrepreneurial ventures associated with these have become a necessity. However, such ventures often do not to scale up. Hence, its case for business continuance and sustenance have been challenging. This study provided insights regarding the existential aspect of social enterprises in terms of its performance.

This study was one of the first research studies that integrated the factors of OC, OO, EE and TMS in building organizational capability towards innovation in social enterprises. This in turn contributed towards the improvement of FP of social enterprises.

This study aims to show the inconsistency of the approach to the development of artificial intelligence as an independent tool (just one more tool that humans have developed); to describe the logic and concept of intelligence development regardless of its substrate: a human or a machine and to prove that the co-evolutionary hybridization of the machine and human intelligence will make it possible to reach a solution for the problems inaccessible to humanity so far (global climate monitoring and control, pandemics, etc.).

The global trend for artificial intelligence development (has been) was set during the Dartmouth seminar in 1956. The main goal was to define characteristics and research directions for artificial intelligence comparable to or even outperforming human intelligence. It should be able to acquire and create new knowledge in a highly uncertain dynamic environment (the real-world environment is an example) and apply that knowledge to solving practical problems. Nowadays artificial intelligence overperforms human abilities (playing games, speech recognition, search, art generation, extracting patterns from data etc.), but all these examples show that developers have come to a dead end. Narrow artificial intelligence has no connection to real human intelligence and even cannot be successfully used in many cases due to lack of transparency, explainability, computational ineffectiveness and many other limits. A strong artificial intelligence development model can be discussed unrelated to the substrate development of intelligence and its general properties that are inherent in this development. Only then it is to be clarified which part of cognitive functions can be transferred to an artificial medium. The process of development of intelligence (as mutual development (co-development) of human and artificial intelligence) should correspond to the property of increasing cognitive interoperability. The degree of cognitive interoperability is arranged in the same way as the method of measuring the strength of intelligence. It is stronger if knowledge can be transferred between different domains on a higher level of abstraction (Chollet, 2018).

The key factors behind the development of hybrid intelligence are interoperability – the ability to create a common ontology in the context of the problem being solved, plan and carry out joint activities; co-evolution – ensuring the growth of aggregate intellectual ability without the loss of subjectness by each of the substrates (human, machine). The rate of co-evolution depends on the rate of knowledge interchange and the manufacturability of this process.

Resistance to the idea of developing co-evolutionary hybrid intelligence can be expected from agents and developers who have bet on and invested in data-driven artificial intelligence and machine learning.

Revision of the approach to intellectualization through the development of hybrid intelligence methods will help bridge the gap between the developers of specific solutions and those who apply them. Co-evolution of machine intelligence and human intelligence will ensure seamless integration of smart new solutions into the global division of labor and social institutions.

The novelty of the research is connected with a new look at the principles of the development of machine and human intelligence in the co-evolution style. Also new is the statement that the development of intelligence should take place within the framework of integration of the following four domains: global challenges and tasks, concepts (general hybrid intelligence), technologies and products (specific applications that satisfy the needs of the market).