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Strategic flexibility (SF) has become increasingly important for firms because of the fast changes in the external environment. In line with the practical importance of SF, an emerging research field has developed around it that has attempted to understand the nature of SF and the key relationships. The aim of this study is to unveil the semantic structure of the recent literature on SF and to suggest new promising areas for future research.

The authors conduct a systematic literature review with a bibliographic analysis technique, which allows authors to identify the main recent streams in the literature, as well as offer reflections and suggestions for future research.

The authors uncover three main emerging areas in the research on SF, namely SF as a dynamic capability, the role of knowledge management for SF and the relationship between a firm SF and the external environment. The authors put forward three avenues for future research on SF: Avenue 1. SF, business model innovation (BMI) and other dynamic capabilities (DC), Avenue 2. Digital technologies and SF/organizational agility and Avenue 3. SF and sustainability. Articles included in the special issue entitled “A strategic perspective on flexibility, agility and adaptability in the digital era” contribute to Avenue 2, thus paving the way for filling some of the identified gaps regarding the relationship between SF and digitalization.

To the best of authors’ knowledge, this is the first literature review on SF that uses a bibliometric approach to draw conclusions on the findings in the literature. The review contributes to the theoretical understanding of SF by illustrating and explicating core topics that have persisted over time, as well as by presenting three main avenues for further developing authors’ knowledge around SF.

Through the lens of resource-based view (RBV), knowledge-based view (KBV) and DCV, this paper aims to investigate the relationship of entrepreneurial leadership (EL) on the project success (PS) and further examines the mediating effect of knowledge infrastructure capability (KIC), knowledge-based dynamic capability (KBDC) and Big data analytic capability (BDAC).

The data were collected from 467 employees working on project in software companies. The data were evaluated using SMART-PLS, a structural equation modeling (SEM) tool.

The study revealed a significant impact of EL on the PS, the study also found the significant mediation role of KIC, KBDC and BDAC on the EL and PS relationship.

The research gives valuable insight into the effective role of EL as a contemporary leadership style in project-based firms. Also, this research is one of the first to examine knowledge-oriented dynamic capabilities (DC) as a knowledge fulcrum in project execution. These DC have been empirically proven to facilitate EL in achieving PS and support the firm in competing in an uncertain environment.

This study investigates the impact of entrepreneurial orientation (EO) and knowledge management (KM) on firm performance (PERF), as well as the mediating role of KM in the EO–PERF (EO-PERF relationship). In particular, this study aims to explain the impact of KM on the relationship between the EO dimensions and PERF; dimensions are risk-taking (RT), innovativeness (IN) and proactiveness (PR).

This study uses structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) methodologies to explore target relationships. The sample consists of 150 small furniture manufacturers operating in Poland (out of 1,480 in the population).

The study findings show that KM partially mediates the IN–PERF relationship. Furthermore, fsQCA reveals that KM accompanied by IN is a core condition that leads to PERF. Moreover, the absence of KM (accompanied by the absence of RT and IN) leads to the absence of PERF. In addition, the results show that all the variables examined (RT, IN, PR and KM) positively impact PERF.

This study explores the role of KM in the context of EO and its impact on PERF in the low-tech industry. The study uses simultaneously two methodologies that represent different approaches in the search for the expected relationships. The findings reveal that KM mediates the EO-PERF relationship.

By combining relevant literature and using quantitative methodology, this study aims to look into the role of knowledge management (KM) as a mediator between entrepreneurial competencies (ECs) and the sustainable performance (SP) of manufacturing small and medium-sized enterprises (SMEs).

The relationships in the proposed model were examined with data collected from 122 Malaysian SMEs using a cross-sectional technique and a standardized questionnaire and analyzed using structural equation modeling path analysis.

According to the findings, ECs have a positive and considerable impact on KM as well as the SP of manufacturing SMEs. Importantly, KM partially mediates between ECs and the SP of manufacturing SMEs.

This research provides a theoretical contribution through the integration of ECs, KM and SP within a unified framework that takes into account the viewpoints of the resource-based view, the knowledge-based view and the triple bottom line. The results corroborate that ECs directly affect SP and indirectly through KM. Nevertheless, the study’s use of cross-sectional survey data makes it impossible to draw conclusions about causes. This is because ECs, KM and SP all have effects on time that this empirical framework cannot account for.

The findings of this research provide valuable insights for managers and decision-makers in SMEs, who are expected to show an increasing interest in adopting KM processes into their companies through which ECs can be translated into SP.

By applying the proposed framework, SMEs can conduct their activities in ways that do not harm environmental and societal well-being while achieving appropriate economic performance at the same time.

As a result, the findings of this study can add to the literature on ECs and KM, as well as boost the chances of SME sustainability. Directions for future research are also provided in relation to a better understanding of the factors affecting the SP of SMEs.

The study directs attention to the psychological conditions experienced and knowledge management practices leveraged by faculty in higher education institutes (HEIs) to cope with the shift to emergency remote teaching caused by the COVID-19 pandemic. By focusing attention on faculty experiences during this transition, this study aims to examine an under-investigated effect of the pandemic in the Indian context.

Interpretative phenomenological analysis is used to analyze the data gathered in two waves through 40 in-depth interviews with 20 faculty members based in India over a year. The data were analyzed deductively using Kahn’s framework of engagement and robust coding protocols.

Eight subthemes across three psychological conditions (meaningfulness, availability and safety) were developed to discourse faculty experiences and challenges with emergency remote teaching related to their learning, identity, leveraged resources and support received from their employing educational institutes. The findings also present the coping strategies and knowledge management-related practices that the faculty used to adjust to each discussed challenge.

The study uses a longitudinal design and phenomenology as the analytical method, which offers a significant methodological contribution to the extant literature. Further, the study’s use of Kahn’s model to examine the faculty members’ transitions to emergency remote teaching in India offers novel insights into the COVID-19 pandemic’s effect on educational institutes in an under-investigated context.

Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.

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.

This study aims to assess the knowledge-sharing risks and controls in the government sector from the knowledge workers’ perspective.

This qualitative study combines two techniques. First, the study uses the Delphi technique to identify the risks and rank them. Second, the study used a follow-up interview approach to identify the needed controls to mitigate these identified risks.

The Delphi study revealed the top knowledge-sharing risks are related to organizational and individual risks. Furthermore, the study identified the top controls that needed to mitigate these identified risks from technology, process and people dimensions. The study findings suggested that implementing controls on people and processes is the most important, and the focus must be on them, especially in the government sector.

The study offers several practical implications for the government sector to establish a knowledge-sharing risks management strategy. Such study has been given little attention in previous research, especially in developing countries.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.

The design goal for the tracking interval of high-speed railway trains in China is 3 min, but it is difficult to achieve, and it is widely believed that it is mainly limited by the tracking interval of train arrivals. If the train arrival tracking interval can be compressed, it will be beneficial for China's high-speed railway to achieve a 3-min train tracking interval. The goal of this article is to study how to compress the train arrival tracking interval.

By simulating the process of dense train groups arriving at the station and stopping, the headway between train arrivals at the station was calculated, and the pattern of train arrival headway was obtained, changing the traditional understanding that the train arrival headway is considered the main factor limiting the headway of trains.

When the running speed of trains is high, the headway between trains is short, the length of the station approach throat area is considerable and frequent train arrivals at the station, the arrival headway for the first group or several groups of trains will exceed the headway, but the subsequent sets of trains will have a headway equal to the arrival headway. This convergence characteristic is obtained by appropriately increasing the running time.

According to this pattern, there is no need to overly emphasize the impact of train arrival headway on the headway. This plays an important role in compressing train headway and improving high-speed railway capacity.