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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.

The main goal of this study is to develop accounting students’ solidarity with and sensitivity to cooperation for sustainable development. This study also aims to analyze the role of participatory learning activities in developing the dimensions of involvement, critical reflection and thinking analysis.

This empirical study analyzes a case study activity conducted in accounting seminars with students from different universities in Spain. After completing the activity, the students completed a questionnaire divided into four areas: sociodemographic information, involvement, critical reflection and creativity. Students also answered an open-response question that asked them to propose new activities to enhance their learning experience and contribute more to sustainable development. The study thus used mixed methods, complementing quantitative analysis with qualitative data.

The multivariate analysis obtained significant results showing that female students were more willing to help and that most students said they were more sensitive to these issues after the participatory learning activity. Furthermore, the items and dimensions analyzed revealed a positive impact of involvement, critical and creative thinking and participatory learning on accounting students’ commitment to cooperation for sustainable development. When students answered the open-response question, they proposed more activities to enhance their learning and improve the functioning of the Non-Governmental Organization’s (NGO’s) beneficiary. HEIs must design more transversal courses aligned with the Sustainable Development Goals in their social science degrees.

The study not only examines university education in sustainable development but goes a step further in trying to involve students in a real development project from a financial and accounting point of view. The study also focuses on education for sustainability, and the project invites the students to think critically, reflect and assess real situations.

There is currently a gap in the research regarding the effect of corporate culture on corporate innovation capability. Based on cultural hierarchy theory, in this paper, we explore the interactions between cultural factors and innovation capability in emerging market firms (EMFs). We discuss the mechanisms by which incentive, institutional, and vibrant corporate cultures influence corporate innovation capability. Furthermore, we consider the transformation of artificial general intelligence (AGI) from a tool into a colleague and how this affects the relationship between corporate culture and innovation capability.

An online questionnaire was distributed to corporate employees to explore their attitudes towards AGI and corporate culture. In total, 523 valid questionnaires were empirically analysed using partial least squares structural equation modelling and multigroup analysis (MGA).

The results showed that incentive culture, institutional culture, and vibrant culture had a positive impact on corporate innovation capability. MGA revealed significant differences between employees who considered AGI a tool and those who considered it a colleague. Employees who treated AGI as a colleague were likely to be influenced by a vibrant culture, whereas employees who treated AGI as a tool were likely to be influenced by an incentive or institutional culture.

Building on cultural hierarchy theory, our study provides a new theoretical framework to enrich current research on the relationship between corporate culture and AGI. The study can help EMF managers adjust incentive and institutional cultures before AGI shifts from being a tool to a colleague and negatively impacts innovation capacity.

Promoting electric vehicles (EVs) is an effective way to achieve carbon neutrality. If EVs are widely adopted, this will undoubtedly be good for the environment. The purpose of this study is to analyze the impact of network externalities and subsidy on the strategies of manufacturer under a carbon neutrality constraint.

In this paper, the authors propose a game-theoretic framework in an EVs supply chain consisting of a government, a manufacturer and a group of consumers. The authors examine two subsidy options and explain the choice of optimal strategies for government and manufacturer.

First, the authors find that the both network externalities of charging stations and government subsidy can promote the EV market. Second, under a relaxed carbon neutrality constraint, even if the government’s purchase subsidy investment is larger than the carbon emission reduction technology subsidy investment, the purchase subsidy policy is still optimal. Third, under a strict carbon neutrality constraint, when the cost coefficient of carbon emission reduction and the effectiveness of carbon emission reduction technology are larger, social welfare will instead decrease with the increase of the effectiveness of emission reduction technology and then, the manufacturer’s investment in carbon emission reduction technology is lower. In the extended model, the authors find the effectiveness of carbon emission reduction technology can also promote the EV market and social welfare (or consumer surplus) is the same whatever the subsidy strategy.

The network externalities of charging stations and the subsidy effect of the government have a superimposition effect on the promotion of EVs. When the network effect of charging stations is relatively strong, government can withdraw from the subsidized market. When the network effect of charging stations is relatively weak, government can intervene appropriately.

Comparing previous studies, this study reveals the impact of government intervention, network effects and carbon neutrality constraints on the EV supply chain. From a sustainability perspective, these insights are compelling for both EV manufacturers and policymakers.

Currently, innovation performance (IP) and innovation quality (IQ) are essential intertwined constructs that help small- and medium-sized enterprises (SMEs) thrive in a competitive business environment and achieve long-term success and sustainability. This paper aims to examine the effect of top management knowledge values (TMKVs), knowledge-oriented culture (KOC) and rewards on IP and IQ through knowledge sharing.

The authors used a deductive cross-sectional data approach and a standardized questionnaire adopted from the literature to obtain responses from the employees of Egyptian manufacturing SMEs. The authors based this study’s findings on 316 usable samples by applying the purposive sampling technique.

Using structural equation modeling (SEM) with path analysis using SmartPLS4, the findings of this study demonstrate that TMKV positively affects IP but not IQ. On the one hand, the KOC and knowledge-sharing process (KSP) are positive enablers of IP and IQ. On the other hand, knowledge-based reward (KBR) has an insignificant effect on IP and IQ. Moreover, while KSP mediates TMKV’s and KOC’s connections with IP and IQ, it does not mediate KBR’s relationship with IP and IQ.

This study’s findings will help policymakers and planners create strategies through knowledge management to improve employees’ vision, commitment and dedication, culminating in a favourable impact on IP and IQ. These findings highlight the need to foster a knowledge-based culture that promotes communication networks, establishes trust and enables individuals to make decisions to enhance organizational success, IP and IQ.

In the case of a developing country, this study helps to fill the gaps by offering an integrated framework that simultaneously explores knowledge management enablers, IP and IQ.

This study investigates the effect of asset specificity, inter-firm ecosystem and firm adaptability on supply chain integration. The study also investigates the mediation effect of firm adaptability on the relationship between asset specificity and supply chain integration and inter-firm ecosystem and supply chain integration.

This research applied a quantitative research methodology to investigate the interdependencies between study variables. A disproportionate stratified simple random sampling technique was used to select the firms that participated in the study. As a result, 103 food processing firms were selected from a total population of 345 firms located in Kampala district.

The findings reveal that the direct relationship between asset specificity and supply chain integration and inter-firm ecosystem and supply chain integration was found positive but insignificant. Both asset specificity and inter-firm ecosystem are associated positively with firm adaptability. A partial mediation was established between asset specificity and SCI while a full mediation effect was found in inter-firm ecosystem and SCI.

The study used perceptual measures to obtain responses on the various constructs investigated and how these constructs relate. To avoid biasing the results, key suppliers and customers were not involved due to multi-level relationships that they maintain with various firms.

This study contributes to existing studies by applying two theories. First, the study applies the Transaction Cost Theory to study the effect of asset specificity on supply chain integration. Secondly, the Complexity Adaptive System Theory was applied to examine the influence of firm adaptability and inter-firm ecosystem on supply chain integration. Few studies have focused on the effect of inter-firm ecosystem in the supply chain; yet, SCI involves network of various player making supply chains complex This study is among the few studies that have focused on adaptability in the food processing sector in a developing country like Uganda.

The present research aims to study the behavioural intention to use the digital currencies issued by the central bank through the lens of technology acceptance and switching behaviour perspective. The study also proposes to analyse the role of financial constructs to explain the adoption intention.

The current study develops a model by integrating the unified theory of acceptance and use of technology (UTAUT) and the push–pull–mooring (PPM) theory of switching behaviour. It amends the same by including financial literacy, financial inclusion and trust. A sample data of 419 respondents has been collected through a structured questionnaire and the PLS-SEM approach has been used for data analysis.

The findings suggest that UTAUT and PPM models can significantly predict individuals' readiness to adopt the central bank digital currency (CBDC). More precisely, performance expectancy, social influence, government support, relative advantage and task-technology fit jointly determine the adoption behaviour. Besides, the financial constructs also affect the intention to use CBDC.

The study is largely based on a quantitative approach with cross-sectional data from an Indian sample. Thus, the findings may benefit from a longitudinal approach with mixed-method data analysis. However, the study elaborates on several implications for policymakers and research scholars.

The present study uniquely integrates the technology adoption perspective with switching behaviour applied to the migration studies. Given the nascent stage of CBDC implementation in many countries, the current study uses a triangulation approach to enhance the understanding of its adoption behaviour.

The adoption of energy-efficient systems is crucial for Pakistan to meet its growing energy demand and address its energy challenges. However, adoption of these systems in Pakistan is hindered by several barriers, including economic constraints, lack of awareness and social attitudes toward sustainable development. Therefore, the purpose of this study is to explore adoption of energy-efficient household systems and the associated social influence.

The study incorporates social influence as a mediating factor to examine the relationships between awareness of consequences, perceived consumer effectiveness and attitudes toward the adoption of energy-efficient systems. A quantitative survey method was used to collect data from households from Faisalabad, Pakistan. A total of 203 valid questionnaires were received and data analyzed through SmartPLS 4 for structural equation modeling.

The results revealed that awareness of consequences positively impacts compliance, social identification and internalization, while perceived consumer effectiveness has a positive relationship with social identification and internalization. Moreover, the positive association of social identification and internalization with attitude were supported but relationship of compliance with attitude was unsupported.

The results may also be used to develop compelling marketing campaigns focusing environmental conservation and social influence for positive attitude development.

The study contributes to theoretical literature by examining the empirical relationships between specific individual characteristics and societal pressure that play a critical role in shaping attitudes toward the acceptance of energy-efficient systems. Additionally, the study's findings offer actionable implications for policymakers and marketers, contributing to the development of targeted interventions for promoting sustainable consumption.

This research aims to understand the smartphone security behavior using protection motivation theory (PMT) and tests the current PMT model employing statistical and predictive analysis using machine learning (ML) algorithms.

This study employs a total of 241 questionnaire-based responses in a nonmandated security setting and uses multimethod approach. The research model includes both security intention and behavior making use of a valid smartphone security behavior scale. Structural equation modeling (SEM) – explanatory analysis was used in understanding the relationships. ML algorithms were employed to predict the accuracy of the PMT model in an experimental evaluation.

The results revealed that the threat-appraisal element of the PMT did not have any influence on the intention to secure smartphone while the response efficacy had a role in explaining the smartphone security intention and behavior. The ML predictive analysis showed that the protection motivation elements were able to predict smartphone security intention and behavior with an accuracy of 73%.

The findings imply that the response efficacy of the individuals be improved by cybersecurity training programs in order to enhance the protection motivation. Researchers can test other PMT models, including fear appeals to improve the predictive accuracy.

This study is the first study that makes use of theory-driven SEM analysis and data-driven ML analysis to bridge the gap between smartphone security’s theory and practice.

This paper represents the first attempt to examine investor behavior for green stocks through the lens of return co-movement, and provides evidence indicating that green investment practices have gained traction after 2012.

We empirically test the hypotheses that the stock returns of firms with similar carbon dioxide emissions levels move together and, if so, whether this co-movement has increased over time as people become more “carbon-conscious.” Our baseline sample, based on carbon emissions data from public company disclosures, suffers from limited coverage, particularly before 2016, leading to low statistical power and sample selection bias. To address this, we employ machine learning methodologies to forecast the carbon emissions of firms that do not disclose such information, nearly quadrupling the sample size. Our findings indicate that stocks with similar carbon emissions exhibit higher co-movement in stock returns in both the baseline and augmented data samples. Furthermore, this co-movement has increased during the 2012–2020 period compared to the 2004–2011 period, suggesting that green investment has gained traction over time.

We find that stocks with similar carbon emissions exhibit higher co-movement in stock returns in both the baseline sample and the augmented data sample, and the co-movement has increased in the 2012–2020 period compared to the 2004–2011 years, suggesting that green investment has gained traction over time.

(1) We use machine learning methodology to augment carbon emissions sample which goes back to 2004. Our approach almost quadruples the original data, enabling large-sample testing. (2) We are the first paper to examine how green companies' stock returns co-move and thus provide complementary results on the research on expected returns and carbon emissions.