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Much of the existing research conducted on dynamic capabilities and the microfoundations of innovation has focused either on individual or organizational factors without considering mechanisms. This paper aims to address this “process” gap by developing an integrated conceptual framework based on individual, processual and structural microfoundations as well as the interaction between and among them with respect to innovation.

To understand the theoretical and empirical landscape in building our conceptual model, we conducted a content analysis of existing research microfoundations, dynamic capabilities and innovation. Using NVivo 12, we identified and examined the individual and organizational behavior microfoundations and their interplay to propose possible processual mechanisms. We framed these process mechanisms using the sensing, seizing and reconfiguring dynamic capabilities framework.

The study emphasizes certain microfoundations that facilitate innovation-dynamic capabilities at various organizational levels. It is posited that both formal and informal strategic intelligence processes, along with directed and undirected information research methods, constitute crucial microfoundations for identifying opportunities for innovation. For the internal capture and seizing of these opportunities, we assert that the diversity of individual internal networks and the mechanisms for social integration will prove to be critical. Furthermore, the paper suggests that reconfiguring microfoundations, specifically an organization’s flexible structure and the involvement of external directors with diverse experiences, are pivotal in spurring innovation.

We combine the microfoundations approach (individual, structural and processual) with the dynamic capabilities theory (sensing, seizing and reconfiguring) to offer an integrated conceptual framework underlying innovation’s dynamic capabilities. This sets us apart from existing research by both introducing processual aspects and their multilevel interactions.

This paper seeks to understand kaizen in practice as it travels through time and space in the organisational setting.

A qualitative case study was carried out at a multinational company using mainly interviews for the data collection that were analysed from an actor-network theory (ANT) perspective.

This paper finds that the company deals with a series of paradoxes while managing the kaizen process. Efficiency and quality paradoxes are the basis for starting kaizen projects. Furthermore, intrinsic, and extrinsic motivation, emerge in these processes, and paradoxes relate to how spontaneous ideas emerge in a deliberated context of cost-saving objectives. The supply chain finance team coordinates kaizen projects with the collaboration of plant managers, promoting the paradox of autonomy and control. In addition, as kaizen mobilises and enrols the actors, some trials of strength emerge, showing actors who oppose the kaizen network and create competing networks that mutually exist in the firm.

This study presents valuable insights for professionals to successfully implement kaizen methodologies that take advantage of developing a network for problem-solving in organizations.

This study highlights the supply chain finance team's role in enrolling the actors within a network built by practitioners engaged in kaizen projects. Usually, engineers, quality, or manufacturing teams lead kaizen projects, and only occasionally, accounting and financial teams participate, including multidisciplinary teams.

Previous studies have focused on explaining the developmental paths and the relevant skills necessary for smart factories, based on an extensive review of the literature. Unfortunately, there is a deficit of empirical analyses that present an in-depth overview of smart factory development. Although the literature supports the benefits of smart factories, it remains unclear whether there should be government intervention (GI) to facilitate or regulate such adoption. This study will provide an in-depth empirical analysis of smart factory adoption (SFA) and its role in manufacturing performance (MP) and sustainable manufacturing (SM).

This study used non-probability convenience and referral sampling techniques for data collection. This approach considered production managers from each company that participated in the survey questionnaire; thus, each production manager represented one firm. A total of 240 managers from several manufacturing companies participated in the study. This study employed direct and moderating hypotheses tested using PROCESS Macro, which Andrew Hayes developed for SPSS.

The study identified three fundamental elements of a smart factory: manufacturing big data (MBD), process automation (PA) and supply chain integration (SCI) and analyzed them individually to see how they affect MP. According to the results, building a smart factory has positive and significant impacts on MP and SM. Furthermore, this study explores the role of GI in promoting smart factory deployment for both production performance and sustainable production. The study found that GI did not have a significant moderating effect but did have a positive relationship with SM.

This study contributes to the literature on smart factories by examining the impact of SFA on MP and SM. This provides a more comprehensive overview of the potential benefits of smart factories across various aspects, such as the application of big data, adoption of automation technology and integration of the supply chain. This study suggests that managers and decision-makers consider investing in smart factory implementation to improve factory productivity and enhance sustainability. Policymakers and government officials can promote the adoption of smart factories by providing incentives, funding, and resources to manufacturing firms.

There is a scarcity of research measuring the actual performance of manufacturing firms that have already adopted smart factories, and this study seeks to address this gap in the literature. This study focuses on the implementation of manufacturing big data, process automation and supply chain integration and how the adoption of these technologies improves MP and provides a SM environment by conducting a real-time study of manufacturing organizations. This study presents an initial effort to explore the role of government involvement in promoting smart factories.

This study aims to explore the influence of creative tourist experiences (CTE) on tourists’ recommendation intentions (RCI) toward creative tourist destinations. This study examines the roles of tourist engagement and satisfaction in this relationship, proposing a sequential mediation model based on the cognitive-affective-conative model.

The research surveyed travelers to Kinnaur, Himachal Pradesh, India, using a structured questionnaire. Through purposive sampling data were collected from 413 generation Z (Gen Z in short) tourists. The study used exploratory factor analysis, confirmatory factor analysis and sequential mediation analysis. The present research used Model 6 by Andrew Hayes in the SPSS process macro to test the serial mediation.

The findings emphasize the importance of active engagement in creative tourism and its potential to transform cultural heritage into enriching experiences, thereby influencing tourists’ recommendation behaviors. Results of sequential mediation analysis show that there is a significant and positive impact of CTE on tourist’s RCI. Further, results showed the sequential mediation effect of tourist engagement and satisfaction on the relationship between CTE and RCI.

The findings offer valuable insights for destination managers and policymakers in creative tourism. Enhancing tourist engagement and satisfaction through creative experiences can effectively increase RCI, contributing to the sustainable management of cultural resources and preventing the over-commercialization of cultural heritage.

This research contributes to the literature on creative tourism by empirically testing the sequential mediation model and highlighting the pivotal role of tourist engagement and satisfaction in transforming creative experiences into positive behavioral outcomes. This study provides a nuanced understanding of the factors influencing tourists’ RCI in creative tourism contexts.

Losing indigenous knowledge is to lose the future and impoverish the societies because indigenous knowledge is considered one of the cornerstones and survival of communities, societies and economies. This study, thus, aims to explore and assess the contextual enablers of indigenous knowledge and their role in developing and sustaining the Ewe communities in Ghana.

The qualitative research design, which enabled the researcher to engage the participants in an interview process and observation, was used in this study. It was augmented with a quantitative design using structured questions. Data analysis was guided by the basic principles of grounded theory. The coding system was aided by NVivo to analyze the qualitative data, while the quantitative data was analyzed using the SPSS. Descriptive analysis and graphs were deployed in the presentation of the findings.

The study discovered that the communities are in possession of several types of indigenous knowledge, ranging from tacit to explicit knowledge, which are embedded in their cultural and traditional systems and unique to every community; the culture of trust among the citizens and motivation to create and share knowledge in communities was high. Same time, family heads, farmer groups, libraries and museums played key roles in the preservation and management of indigenous knowledge in the communities. On the other hand, information officers and institutions like churches and police posts played insignificant roles in the management and preservation of knowledge in the communities just as the absence of a culture of willingness by the community members to create and share knowledge. Additionally, there was an absence of technological infrastructure, platforms, databases and policies to aid the management and preservation of knowledge in the communities. The study concludes that indigenous knowledge plays a vital role in the development and sustainability of communities in Ghana.

Community leaders and political leaders need to invest in systems and structures that will promote the management and preservation of indigenous knowledge for the development of the communities and the state as a whole.

The study demonstrates its originality in terms of scope, setting, population and empirical evidence by focusing on the role of indigenous knowledge in the sustainability and development of Ewe communities in Ghana.

Using a dynamic capability view, this study examined the relationships between big data analytics capability (BDAC), entrepreneurial orientation (EO) and sustainable supply chain performance (SSCP) by exploring the moderating role of trust among supply chain partners.

Questionnaires were collected from 300 manufacturing organizations using snow sampling. The moderating connections and direct relationships were examined using Hays' process macro and structural equation modeling.

BDAC was positively related to EO and SSCP. When supply chain partners experienced low levels of trust, an increase in BDAC did not enhance SSCP. As trust increased, the relationship between BDAC and SSCP became more positive, underpinning the moderating effects of trust. Moreover, trust did not moderate the relationship between BDAC and EO. The moderating effect of trust on the relationship between EO and SSCP showed a positive relationship between EO and SSCP when trust was low; however, the relationship became negative when trust was high.

Developing technology alone may not be sufficient, as supply chain managers need to establish a strong business relationship based on mutual trust. However, they also need to be aware of the dangers of high levels of trust because these may negatively affect performance. Therefore, supply chain managers need to achieve an optimal level of trust that is neither excessive nor insufficient.

Advances in technology and entrepreneurial drive for supply chain sustainability make it pertinent to examine trust levels among supply chain partners and the varying impact on BDAC, EO and SSCP. The current study shows the negative aspects of too much trust among supply chain partners.

The purpose of this study is to identify the dynamic parameters of journal bearings in asymmetric rotor systems without additional test runs or excitations.

An asymmetric rotor-bearing test rig was set up for the identification experiment. Comparations were made between the measured response of the asymmetric rotor and the symmetric rotor. The mathematical model of the asymmetric rotor is established by the finite element method. The identification algorithm is based on the model of the rotor and the measured vibration response to identify bearing parameters. The influence of modeling error and measurement noise on the identification results are numerically analyzed. The dynamic parameters of the journal bearings under different rotational speeds are identified and compared with the theoretical values calculated by the perturbation method.

The experiment results show that the vibration characteristics of the asymmetric rotor and the symmetric rotor are different. The numerical evaluation of the identification algorithm shows that the algorithm is accurate and has good robustness to modeling error and measurement noise. The identified dynamic parameters agree reasonably well with the parameters derived from the theoretical bearing model.

The proposed identification method uses the unique vibration characteristics of asymmetric rotors to identify the bearing dynamic parameters. As the method does not require excitations or additional test runs, it is suitable for the field test.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0096/