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The socio-emotional wealth (SEW) framework and the resource-based theory (RBT) offer two valuable perspectives on innovation dynamics within family firms. Through the SEW lens, family firms may prioritize preserving their traditions and core values, potentially resisting the adoption of new technologies and modern business methods. In contrast, RBT suggests that family firms can gain a competitive edge by harnessing and nurturing their unique resources and capabilities, such as collective experiences, market reputation, and established networks, to foster innovation and secure a strong market position. By integrating these two perspectives, family firms can achieve sustainable competitive advantages by balancing the tensions between tradition and innovation. This comprehensive approach allows them to innovate while preserving their SEW, ensuring long-term success in the ever-evolving business landscape.

The study delves into the role played by cutting-edge data analytics, machine learning, and innovative technologies in reshaping traditional insurance practices. The primary goal of this review is to juxtapose findings from the literature sources, enabling a comprehensive analysis of the current state of implementation.

Systematic narrative review methodology has been applied to the present study. Scopus database has been used for the manuscripts ranging from year 2020 to 2024 considering the 5-year rule. 74 manuscripts were reviewed to navigate the landscape of data-driven revolution, unlocking the potential to elevate insurance operations to new heights. Two research questions about the impact of data alchemy on operational efficiency and insights and its contribution to reshaping the future landscape of insurance practices have been answered.

This approach captured the interplay between the theoretical potential for insurance and the practical realities of implementation of advanced practices, drawing upon the collective expertise within the field. By doing so, the article discerned the trajectory of the insurance sector concerning the advanced data alchemy observed in the industry.

The current research contributes to the broader area of data alchemy in the insurance industry. The transformative power of big data analytics lies in its capacity to turn vast and diverse datasets into valuable insights, driving innovation, informed decision-making, and improved business outcomes across various sectors. Notably, the research extends the body of literature exploring the impact of data alchemy on operational efficiency and insights, area where limited studies have been conducted.

The empirical study of factors related to digital transformation (DT) in the banking sector is still limited, even though the importance of the topic is universally evident. To bridge that gap, this paper aims to explore the role of digital leadership (DL), innovative culture (IC) and technostress inhibitors (TI) to support engagement for improved digital innovation (DI). Based on the literature, these variables are crucial aspects of digitalisation, even though there is no agreement on their conclusiveness.

This quantitative study tested a new conceptual model using survey data from five major banks in Libya. Partial least squares structural equation modelling was used to analyse the data from the 292 usable responses.

The results showed that DL and IC positively affect DI. Techno-work engagement (TE) mediated the relationship between leadership, culture and innovation. TI played a significant moderating role in leadership, culture and engagement relationships.

The research findings highlight critical issues about how leadership style and fostering organisational support in the banking sector can enhance DT. Leaders must demonstrate a commitment to long-term resource allocation to avoid possible negative effects from digital stress while pursuing DI through work engagement.

The study suggests that fostering organisational support can enhance DT in retail banks, potentially leading to improved customer experiences and increased access to financial services. These programs will help banks contribute to societal and economic development.

This timely study examines predictor mechanisms of innovation in retail banking that resonate within the restrictions of organisational and DI frameworks and the social exchange theory. Exploring the intervening effect of TE in the leadership, culture and innovation associations is unprecedented.

The purpose of this paper is to research the impact of digitalization on employees' future competencies and the conditional role of human resource development (HRD) in the relationship between independent and dependent variables.

Empirical research covered 1209 enterprises from all of Slovakia, Poland and the Czech Republic. The research was conducted from 2019 to 2021. Using structural equation modeling (SEM), a theoretical model was tested and verified.

Confirmatory factor analysis has shown a good fit for the tested model. The purpose and character of our data showed a good alignment with the SEM partial least squares method, as the goal is to predict a construct. The model showed that employee-oriented digitalization positively affected the employees' future competencies, with no impact of customer-oriented digitalization treated as a control variable. Also, the moderating role of HRD has not been shown to be significant for the “digitalization – competencies” relationship.

Previous studies on the development of personnel competencies treated these competencies as antecedents of digital transformation and examined the formal role of HRD in building the competencies. The novelty of this study lies in exploring the pattern of interactions among the impact of an environment built by innovative technologies and HRD on the competencies of the future. Also, the research embedded in the environment of Poland, the Czech Republic and Slovakia has contributed to the complex understanding of the transition to digitalization, as this region has often been omitted in the field of human resource management (HRM) research focused on exploring digital transformation.

There is currently a lack of comprehensive examination in the research field exploring the relationship between digitalization and environmental performance (EP) in manufacturing small and medium-sized enterprises (SMEs). This study investigates the relationship between digital technologies, digital organizational culture (DOC), environmental dynamism and EP through the mediation of innovation capacity (IC) and moderation of perceived environmental volatility and green strategic intent (GSI).

The data were gathered from 473 managers of manufacturing SMEs in Pakistan. Partial least square structural equation modeling (PLS-SEM) was applied to examine the mediation and moderation effects. Multiple regression analysis was used to see the influence of digital technologies, DOC, environmental dynamism, innovation capacity, perceived environmental volatility and GSI on SMEs environmental performance.

Results indicate a statistically significant direct relationship between digital technologies, environmental dynamism and EP. While there is an insignificant direct relationship between DOC and EP. Furthermore, the results reported a significant result between digital technologies, DOC, environmental dynamism and IC. Similarly, IC significantly mediated the relationship between digital technologies, DOC, environmental dynamism and EP. Moreover, results reported that perceived environmental volatility does not moderate the relationship between IC and EP, while GSI significantly moderates between IC and EP.

Policymakers must emphasize advancing digital integration to enhance manufacturing SMEs’ efficiency and environmental effectiveness.

This is the first research that incorporates digital technologies, environmental factors and innovation capacity to measure environmental performance in line of natural resource orchestration theory (natural ROT). All the variables significantly measure environmental performance instead of digital organizational culture. Perceived environmental volatility also does not moderate.

The current paper aims to discuss the implementation of Green Lean Six Sigma (GLSS) in the food industry to improve sustainable practices. The focus is more specifically on dairy processors to ascertain the current state of the literature and aid future research direction.

Utilising a systematic literature review (SLR), the paper addresses various terms and different written forms in the literature. The study characterises the current deployment of GLSS in the food industry and explains the reported benefits of this approach.

GLSS, a concept that has yet to be fully explored in the food industry, as in other sectors, holds significant potential to enhance the food industry’s sustainability practices. The dairy sector, a subsector of the food industry known for its high greenhouse gas emissions, is a prime candidate for the application of GLSS. In instances where it has been applied, GLSS has demonstrated its effectiveness in improving sustainability, reducing waste, lowering greenhouse gas emissions and minimising water usage. However, the specific tools used and the model for GLSS implementation are areas that require further study, as they have the potential to revolutionise food industry operations and reduce their environmental impacts.

Benchmarking of this research by the food industry sector and by academics can aid understanding of the practical application of GLSS tools and aid implementation of these practices to evolve the dairy processing sector in the next decade as sustainability champions in the sector.

This study extensively analyses GLSS in the food industry, with a particular focus on dairy processors.

The study aims to investigate the mediating impact of supplier quality integration on the operational performance of the pharmaceutical supply chain (PSCs) by comparing mature and evolving PSCs.

The study adopted a quantitative method where data were gathered through a survey instrument to identify the differentiators of dynamic capabilities and establish the extent of quality integration in PSCs. Thus, 310 questionnaires were collected from mature and evolving PSCs, where the PROCESS technique was used to analyse the data.

The results demonstrate the significant paths that enable companies to create, extend and modify the resources to develop their dynamic capabilities. The results reveal significant differences in internal and supplier quality implementation and their impact on operational performance between mature and evolving PSCs.

To the best of our knowledge, this is the first study to examine dynamic capabilities aspects of the pharmaceutical supply chain quality integration in mature and evolving PSCs, which extends the body of knowledge and makes a practical contribution.

The purpose of this paper is to fill a gap in the literature regarding the open innovation management approaches that small and medium-sized enterprises (SMEs) can use to access digital technologies and incorporate them into their organizational processes. The research question is: What organizational and process-level managerial actions do SMEs take to successfully access and implement digital technologies within their organizational processes?

Using Guertler et al.'s (2020) Action Innovation Management Research (AIM-R) framework, this study examines the digital transformation experiences of 10 European SMEs to gain insights into the managerial actions that foster successful digital transformation.

The findings of the paper reveal two major contributions. First, a digital transformation roadmap for SMEs is proposed, with a focus on accessing external resources and reconfiguring internal ones to ease their digital transformation journey. Second, three distinct paradoxes that influence the digital transformation process in SMEs are highlighted, providing useful insights into the challenges and tensions SMEs face during this journey.

This paper provides a unique perspective on the digital transformation of SMEs by examining the managerial actions required for successful technology adoption and revealing the paradoxes that may emerge during this transformative process. The findings form the basis for future research, deepening our understanding of digital transformation in SMEs and providing actionable advice to managers and practitioners navigating this journey.

This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).

A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.

Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.

The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.

Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.

This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.