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Green entrepreneurship (GE) is a novel concept in business and enhances environmentally friendly production and operation activities for “sustainable development” (SD). The aim of this study is to determine the drivers that contribute to the growth and success of “micro, small, and medium enterprises” (MSMEs) in the manufacturing sector in India. The study also examines the mutual and cause-and-effect relationships among these identified drivers.

The study used integrated research methodology and identified nine key drivers of GE (GEDs) through extensive literature reviews, theoretical perspectives (i.e. “resource-based view” (RBV), “natural resource-based view” (NRBV) and “critical success factor theory” (CSFT)), and expert opinions. Further, “total interpretive structural modeling” (TISM) and “matrice d'impacts croisés multiplication appliquée á un classment” (MICMAC) analysis are used here to develop a hierarchical model and cluster the drivers, and fuzzy “decision-making trial and evaluation laboratory” (fuzzy-DEMATEL) is used to develop causal relationships among the drivers. Further, a sensitivity analysis is conducted to ensure the robustness of the results.

Results indicated that green manufacturing and operation capability development, green business process management and attitudes toward developing sustainable business models significantly impacted GE and SD. The findings of this study help managers, policymakers, and practitioners gain an in-depth understanding of the drivers of GE.

The study considers a limited number of drivers and is specific to Indian manufacturing MSMEs only. Further, a limited number of experts from different enterprises are considered for data analysis. This study is also based on interrelationships and their relative importance based on multicriteria decision-making techniques. This study aids government decision-making, policy formulation and strategic decision-making for manufacturing businesses in achieving SD goals. In addition, this research also encourages green entrepreneurs to start eco-driven companies and facilitate the use of environmentally friendly goods to offset environmental challenges and accomplish sustainable development goals.

This study proposes an integrated methodology that will benefit managers, practitioners and others in developing strategies and innovations to improve and develop green practices. This study further helps with responsive, sustainable business development in various manufacturing MSMEs.

This study aims to address the critical challenge of implementing lean manufacturing (LM) in emerging economies, where sustainability complexities on the production floor hinder production efficiency and the transition towards a circular economy (CE). Addressing a gap in existing research, the paper introduces a path analysis model to systematically identify, prioritize and overcome LM implementation barriers, aiming to enhance performance through strategic removal.

The authors used a mixed-method approach, combining empirical survey data with literature reviews to pinpoint key LM barriers. Using the grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL) along with the Network Knowledge (NK) method, they mapped causal relationships and barrier intensities. This formed the basis for developing a path simulation algorithm, integrating heuristic considerations for practical decision-making.

This analysis reveals that the primary barriers to LM adoption is the negative perception and inadequate understanding of lean tools and CE principles. The study provides a strategic framework for managers, offering new insights into barrier prioritization and overcoming strategies to facilitate successful LM adoption.

This research provides a strategic pathway for overcoming LM implementation barriers, empowering managers in emerging economies to enhance sustainability and competitive advantage through LM and CE integration. It emphasizes the significance of structured barrier management in the manufacturing sector.

This research pioneers a systematic exploration of LM implementation barriers in the CE context, making a significant contribution to the literature. It identifies, evaluates barriers and proposes a practical model for overcoming them, enriching sustainable manufacturing practices in emerging markets.

Prior research has extensively explored the dynamics of knowledge creation and transfer within entrepreneurial ecosystems (EEs). However, the research on knowledge integration within EEs, particularly by entrepreneurs, remains scant. Garnering and effectively using knowledge in such a dynamic and complex environment can provide entrepreneurs with a valuable asset for gaining a competitive advantage. To address this gap, this study aims to explore how entrepreneurs garner and capitalise on knowledge within the EE environment by using a transactive memory system lens.

This study is based on 26 semi-structured interviews with different actors and members of the same ecosystem – the northern Finnish health tech ecosystem. The data were analysed using the Gioia methodology.

This study results found that transactive memory processes (i.e. knowledge specialisation, credibility and coordination) and structures (i.e. differentiated-, shared- and meta-knowledge) influence knowledge organising in EEs.

This study provides a conceptual interplay between the EE and the transactive memory system’s processes and structures.

Entrepreneurial action under uncertainty has captured the interest of scholars and practitioners alike. However, this growing body of research has yet to connect entrepreneurial action with actual actions of entrepreneurs. We combine insights from effectuation theory and the psychology of entrepreneurship to investigate drivers of entrepreneurial actions involved in starting and running ventures, particularly optimism, self-efficacy and the use of causal and effectual logics.

The study employs a unique mixed-method approach combining a survey with experience sampling data. After measuring demographics, preference for effectual or causal logics and psychological variables, the 197 US entrepreneurs sampled entrepreneurs logged their daily actions in the form of asks during 60 consecutive days.

Results suggest that self-efficacy and causal logics are key drivers of entrepreneurial actions, while optimism serves as a deterrent. Interestingly, the impact of self-efficacy on actions is moderated by the entrepreneur’s experience level, measured both in years and past asking experience.

The potential of the ask as the basic mechanism for entrepreneurial actions is explored. Based on the findings, the authors offer new and fertile insights by linking psychological traits to entrepreneurial actions, causal and effectual logics and entrepreneurial expertise development.

The current study aims to explore the determinants of user intentions towards fitness YouTube channels, employing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and Uses and Gratifications Theory (UGT) as theoretical frameworks.

Symmetric and asymmetric analyses were employed for data analysis, utilizing partial least squares-structural equation modeling (PLS-SEM) for symmetric analysis and fuzzy-set qualitative comparative analysis (fsQCA) for asymmetric analysis.

The study revealed significant impacts of most UTAUT2 determinants and all UGT determinants on user intentions. Additionally, the fsQCA results supported the concept of equifinality, indicating that various configurations of causal combinations can predict a high level of behavioral intention. These findings underscore the significance of comprehending user motivations and factors related to technology and social media in the context of maintaining or increasing followership and viewership for fitness content providers.

The findings suggest that individuals with high expectations and facilitating conditions, as per UTAUT, and heightened hedonic and socializing motivations, in line with UGT, are more inclined to follow fitness YouTube channels. This study offers valuable insights for fitness content creators and marketers navigating the complexities of the digital age.

Urban villages are prevalent informal settlements within Chinese cities, arising from urban expansion. These areas frequently face systematic demolition during urban renewal due to their disorderly layout and outdated appearance. Urban village renovation (UVR) entails balancing diverse interests and navigating complex conflicts, particularly within China’s dual property rights system encompassing urban and rural land. The purpose of this study is to avoid the fierce interest conflict of UVR.

This study utilized the theoretical framework of value co-destruction. Initially, text mining and literature analysis were employed to identify concept nodes and interaction relationships. Subsequently, the structural equation model (SEM) was used to verify the causal model. Finally, the fuzzy cognitive map (FCM) was developed to dynamically simulate value co-destruction scenarios within UVR across various hypothetical situations.

The concept nodes influencing value co-destruction in UVR form a complex system with multiple levels. This includes three cause nodes and one result node. Among these, actor-to-actor emerges as a primary and underlying cause influencing value co-destruction in these projects. Furthermore, strategies for UVR should prioritize integrated interventions that enhance actor-to-actor relationships.

This study introduced a novel mixed methodology aimed at systematically simulating the dynamic process of value co-destruction during UVR. It also provided a fresh perspective on reverse assessment to mitigate the prevalent interest conflicts in UVR, thereby contributing to theoretical advancements and practical strategies for UVR.

This study aims to answer the following research questions: (1) How do features of sports and fitness live streaming content influence individuals’ viewing experiences? (2) How do these antecedents interact with each other to influence individuals’ intentions to exercise in the context of sports and fitness live streaming?

We employed both symmetric (PLS-SEM) and asymmetric (fsQCA) analyses using data from 886 participants. A mixed approach addresses the complex nature of the decision-making process among sports and fitness live streaming users.

The findings reveal that individuals’ appraisal of their interactions with sports and fitness streamers (i.e. instant feedback, interactivity) significantly affects their perceptions of telepresence, entertainment, and flow. These, in turn, positively influence their intention to exercise in live sports and fitness streaming sessions. The study also uncovers various combinations of causal conditions leading to exercise intention, a detail overlooked by the PLS-SEM method alone.

This research contributes to the literature on cognitive appraisal theory, particularly in the context of sports and fitness live streaming, by integrating symmetric and asymmetric analyses. Practically, strategic implications are provided for practitioners in sports and fitness industry.

This study aims to explore how managers exercise agency in strategic investment decisions (SIDs) by drawing on their knowledgeability of the strategic context. Specifically, the authors address the role of position–practice relations and irresistible causal forces in this conduct.

The authors examine SID-making (SIDM) practices in four case organisations operating in highly competitive markets, conducting interviews with managers at various levels and analysing company documents. Drawing on strong structuration theory, the authors show how managerial decision makers draw upon their knowledge of organisational context when exercising agency in SIDs.

The authors provide insights into how SIDM behaviour, specifically agents’ conduct, is shaped by a combination of position–practice relations and the agents’ comprehension of their organisation’s context.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice.

The authors extend the SIDM literature by surfacing the issue of how actors’ conjuncturally-specific knowledge of external structures shapes the general dispositions they draw on in exercising agency in practice. Particularly, the authors contribute to this literature by identifying irresistible causal forces and illuminating why actors might not resist in SIDM processes, despite having the potential to do so.

The objective of this study is to reevaluate the correlation among pharmaceutical consumption, per capita income, and life expectancy across different age groups (at birth, middle age, and advanced age) within the OECD countries between 1998 and 2018.

We employ a two-step methodology, utilizing two independent approaches. Firstly, we con-duct the Dumitrescu-Hurlin pairwise panel causality test, followed by Machine Learning (ML) experiments employing the Causal Direction from Dependency (D2C) Prediction algorithm and a DeepNet process, thought to deliver robust inferences with respect to the nature, sign, direction, and significance of the causal relationships revealed in the econometric procedure.

Our findings reveal a two-way positive bidirectional causal relationship between GDP and total pharmaceutical sales per capita. This contradicts the conventional notion that health expenditures decrease with economic development due to general health improvements. Furthermore, we observe that GDP per capita positively correlates with life expectancy at birth, 40, and 60, consistently generating positive and statistically significant predictive values. Nonetheless, the value generated by the input life expectancy at 60 on the target income per capita is negative (−61.89%), shedding light on the asymmetric and nonlinear nature of this nexus. Finally, pharmaceutical sales per capita improve life expectancy at birth, 40, and 60, with higher magnitudes compared to those generated by the income input.

These results offer valuable insights into the intricate dynamics between economic development, pharmaceutical consumption, and life expectancy, providing important implications for health policy formulation.

Very few studies shed light on the nature and the direction of the causal relationships that operate among these indicators. Exiting from the standard procedures of cross-country regressions and panel estimations, the present manuscript strives to promote the relevance of using causality tests and Machine Learning (ML) methods on this topic. Therefore, this paper seeks to contribute to the literature in three important ways. First, this is the first study analyzing the long-run interactions among pharmaceutical consumption, per capita income, and life expectancy for the Organization for Economic Co-operation and Development (OECD) area. Second, this research contrasts with previous ones as it employs a complete causality testing framework able to depict causality flows among multiple variables (Dumitrescu-Hurlin causality tests). Third, this study displays a last competitive edge as the panel data procedures are complemented with an advanced data testing method derived from AI. Indeed, using an ML experiment (i.e. Causal Direction from Dependency, D2C and algorithm) it is believed to deliver robust inferences regarding the nature and the direction of the causality. All in all, the present paper is believed to represent a fruitful methodological research orientation. Coupled with accurate data, this seeks to complement the literature with novel evidence and inclusive knowledge on this topic. Finally, to bring accurate results, data cover the most recent and available period for 22 OECD countries: from 1998 to 2018.

Advances in autonomous technology have transformed customer experience. Most prior research has investigated the effect of augmented reality (AR) on purchase intention, yet few research has discussed the effect of semiautonomous AR in the context of service use. Semiautonomous AR recognizes content in the present reality, inserts and adjusts virtual content, supervises the users and enables them to feel in control of the virtual content overlaid in observed reality resulting in enriched user experience and thereby augmentation experience. This research demonstrates how perceived control of virtual content leads to higher perceived augmentation experiences among semiautonomous AR users than among non-AR users. In addition, this research examines the mediation effects of enriched user experience and perceived augmentation experience on user satisfaction and users’ willingness to continue using AR. Results also indicate that AR users perceive a higher augmentation experience than non-AR users. However, users’ willingness to continue using AR is not significantly different between AR and non-AR users.

This study derives six hypotheses and uses a preliminary study, a field study and a lab study to evaluate the hypotheses. A field study was conducted in a car dealership to test the hypotheses, and a lab experiment was conducted in a controlled setting to corroborate the results obtained in the field study and test the underlying causal effects.

Semiautonomous AR can constantly sense, plan and not necessarily always act over the virtual content to sustain the interaction with its users. Perceived control of virtual content enhances perceived augmentation experience, and its effect of perceived control of virtual content on perceived augmentation experience is higher among semiautonomous AR users than among non-AR users. Perceived control of virtual content is a key to enriched user experience, augmentation experience and thereby users’ attitude and behavior. In addition, results showed that enriched user experience mediates the effect of perceived control of virtual content on perceived augmentation. User satisfaction mediates the effect of perceived augmentation experience on users’ willingness to continue using AR. The theoretical and practical contributions are comprehensively discussed.

Some limitations of the studies are ascertained. First, a larger sample size might be required to achieve generalizability and a strong test of the applied theory. Second, new field studies can reflect customers’ real attitudes and behaviors so as to reveal realistic interactions between the device properties and the human will in solving actual problems. The user is interested in participating in the solution within the sensing-planning-acting process as depicted by this research. Third, new research to test AR’s capabilities in bounded and symbiotic conditions can illustrate the level of autonomy each type requires, providing additional insights into why supervised AR autonomy best reflects semiautonomous AR. The pioneering structural model offered in this study (perceived control of virtual content-perceived augmentation experience-users’ satisfaction-users’ willingness to continue using AR) should be tested with new samples in other industries, aside from including other variables that may enrich the model and increase its explanatory power. In addition, future research might use other AR devices such as smart glasses to explore the effects of AR on perceived control of virtual content, enriched user experience and perceived augmentation experience. Future studies can investigate the effect of auditory and visual augmentation on enriched user experience and perceived augmentation experience, and involve features of artificial intelligence (AI) to assist users in decision-making. Regarding context, this research showed that age and gender differences did not affect the results. Nonetheless, age and gender, and perhaps additional demographic characteristics, may concern future studies.

Some recommendations for technology developers are derived from this research. AR is revolutionizing service experience. As technologies are becoming autonomous, developers seek ways to design experiences to enhance consumers’ sense of control over their interaction with such systems. Companies cannot create customer experience (Becker and Jaakkola, 2020), yet they can leverage the level of autonomy in AR to sustain ongoing interaction with customers. It is vital to design an autonomous AR that focuses on users’ needs, desires and well-being (de Bellis and Johar, 2020) that drive novel experiences (Novak and Hoffman, 2019). This study recommends AR developers design autonomous features in AR that enable customers to interact with the virtual contents generated by AR and extend their own capabilities to perform a task and feel expanded. While designing a fully autonomous system may hinder users to feel in control of their choice (Schmitt, 2019), service companies can develop an AR system that sustains an interaction, involves the user in value co-creation and guides the user (Alimamy and Gnoth, 2022). AR can sustain an interaction with the users by continuously scanning the objects in the reality and providing sensory feedback such as product size recommendations (e.g. eyeglasses) that facilitate customers’ information processing (Poushneh, 2021b; Heller et al., 2019). To achieve this, developers may focus on technology qualities such as “image recognition,” a subset of AI. With image recognition, AR can effectively provide instruction as if the customer is in a real setting. The proper incorporation of image recognition in the design of AR while enabling users to interact with 3D virtual images sustains their interaction with AR and makes them feel in control of their interaction with AR. Service companies need to ensure users feel in control of their interaction and expand their capacities to engage in the service experience with AR to accomplish their desired tasks. AR’s capacities enable users to expand their abilities to fix their basic service problems without referring to or speaking to a service provider agent in a service context. Therefore, instead of taking their car back to the dealership, customers can use AR mobile applications or glasses provided by car manufacturers to learn and fix basic vehicle problems.

This research advances the marketing literature on how users feel in control of virtual content when they interact with a semiautonomous AR that subsequently influences enriched user experience, perceived augmentation experience, attitudes and behavior.