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Artificial intelligence (AI) can help in defining preventive strategies in taking decisions in complex situations. This paper aims to research how workers might deal with intervening AI tools, with the goal of improving their daily working decisions and movements. We contribute to deepening how workers might deal with intervening AI tools aiming at improving their daily working decisions and movements. We investigate these aspects within a field, which is growing in importance due to environmental sustainability issues, i.e. waste management (WM).

This manuscript intends to (1) investigate if AI allows better performance in WM by reducing social security costs and by guaranteeing a better continuity of service and (2) examine which structural change is required to operationalize this predictive risk model in the real working context. To achieve these goals, this study developed a qualitative inquiry based on face-to-face interviews with highly qualified experts.

There is a positive impact of AI schemes in helping to detect critical operating issues. Specifically, AI potentially represents a tool for an alignment of operational behaviours to business strategic goals. Properly elaborated information, obtained through wearable digital infrastructures, allows to take decisions to streamline the work organization, reducing potential loss due to waste of time and/or physical resources.

Being a qualitative study, and the limited extension of data, it is not possible to guarantee its replication and generalizability. Nevertheless, the prestige of the interviewees makes this research an interesting pilot, on such an emerging theme as AI, thus eliciting stimulating insights from a deepening of information coming from respondents’ knowledge, skills and experience for implementing valuable AI schemes able to an align operational behaviours to business strategic goals.

The most critical issue is represented by the “quality” of the feedback provided to employees within the business environment, specifically when there is a transfer of knowledge within the organization.

The study focuses on a less investigated context, the role of AI in internal decision-making, particularly, for what regards the interaction between managers and workers as well as the one among workers. Algorithmically managed workers can be seen as the players of summarized results of complex algorithmic analyses offered through simpleminded interfaces, which they can easily use to take good decisions.

Small and medium enterprises (SMEs) significantly contribute to economic growth, development, exports and employment of the nations. To maintain competitiveness in today's market, SMEs must explore and identify enablers to enhance their digital transformation process. This paper aims to shed light on some essential enablers SMEs can use to implement digital resilience successfully.

The quantitative assessment and validation of the enablers have been done using powerful and novel techniques, namely, the Delphi method, “fuzzy interpretive structural modelling” (F-ISM) method and “cross-impact matrix multiplication applied to classification (MICMAC)” analysis. The F-ISM model is developed using the information drawn from digital transformation experts and practitioners involved in the digital transformation process for SMEs. Furthermore, the F-ISM model provides four paths to complete the pathway to digital resilience.

The F-ISM and MICMAC analysis revealed four ways to enhance the digital transformation process in SMEs. These enterprises can utilise these path assessments to become digitally resilient in the present dynamic scenario. To enhance digital resilience among SMEs, the study identified ten enablers. Among these, “management competencies” was the most crucial, followed by “knowledge management” and “monitoring and controlling”.

The present study is limited in that the data used to develop the models were collected from a small group of industry experts whose opinions may not exhibit the comprehensive views of the population.

The findings can help SMEs enhance the digital transformation process by taking up different pathways to integrate the various enablers of digital resilience depending on resource availability.

The results indicate the most critical and influential enablers for enhancing digital resilience among SMEs. This research can be valuable to academicians, industry practitioners and researchers for guiding their future work.

The purpose of this study is to examine how the pandemic impacted on business-to-business (B2B) cooperation and coordination, as well as on firms' financial and operational performance, from the B2B context in the era of knowledge economy.

With the help of social network theory, coordination theory and existing literature, a theoretical model was developed conceptually. Later, the conceptual model was validated using structural equation modelling technique with consideration of 712 respondents from different firms who are engaged in managing B2B relationships on behalf of their firms.

The study found that the COVID-19 pandemic has had a considerable moderating impact on the relationship between B2B cooperation and coordination with B2B relationship satisfaction. The study also highlighted that there is a degradation of financial and operational performance of firms due to the impact of COVID-19 pandemic on their B2B relationship management.

There is a challenging and ever-evolving global economy caused by the COVID-19 pandemic. Although it is argued that the pandemic has accelerated the growth of some online firms, it has also had a catastrophic effect, culminating in many firms failing. This study has developed a new business model which helps in improving financial as well as operational performance of the firms in post COVID-19 scenario, especially in the era of knowledge economy.

This is a unique study as this study (1) develops a unique theoretical model with high explanative power, (2) demonstrates how digital reliance and new business model help the firms in post COVID-19 pandemic and (3) adds to the body of literature in the domain of digital reliance, knowledge economy and B2B relationship management.

The purpose of the study was to maximize team members' collaboration and develop relationships in a newly formed team to engage with internal and external partners to achieve open innovation (OI) in product development. The authors examine the role of collaborative human resource management (HRM) and relational leadership (RL) in this process.

The study took a two-stage qualitative methodological approach to examine relational leadership as it emerges in a newly formed cross-functional team at a large German fashion house. In stage one, 10 interviews were conducted with members of the new project team over three months and in stage two six external knowledge exchange partners were interviewed.

Collaborative HRM promotes greater social exchange, trust and commitment of team members internal and external to the organization to support the emergence of RL, which is critical for OI. The authors found that collaborative HRM practices such as team-based recruitment, team-based training, team-based performance management with rewards systems and job design support the emergence of RL. Moreover, RL practices such as congruence and commitment towards team goals subsequently promoted the development of knowledge sourcing and sharing (KSS) to support OI.

The study is the first to demonstrate how collaborative HRM enables RL practices to help newly formed teams overcome challenges with achieving KSS to successfully engage with internal and external partners for OI. The authors contribute to HRM theory development of the relationship between HRM and OI by conceptualizing the OI process as a social construction through collaborative HRM and relational leadership.

This study aims to examine how different uses of performance measurement systems (PMS) enable or hinder organizational ambidexterity (OA), intended as the simultaneous pursuit of exploitation and exploration.

Following a qualitative research design, we gathered data through semi-structured interviews, observations and reviews of documents at four departments of an automotive firm.

We contribute to operations management research and practice by demonstrating how PMS, which are typically associated with exploitation, can also foster exploration and enable organizations to become ambidextrous. Specifically, we show how PMS can be structured and used in more agile ways and, in relation to innovation, we identify which PM practices should be introduced and with what effects and those that should be avoided. We also contribute to organization theory by highlighting how a single management tool can promote the achievement of both exploration and exploitation.

In investigating PMS uses and their effects, we identify several positive practices. For example, we show how managers can use PMS more effectively and how targets could be deployed to stimulate creativity and innovation. We also emphasize the need for managers to opt more often for team incentives rather than individual ones to encourage the collaboration needed for OA.

We provide in-depth insight into how PM tools affect an organization’s ability to pursue exploitation and exploration, thus contributing to research in operations, innovation and organization theory.

This study introduces the Digital Maturity Assessment Model (DMAM), a model tailored to assess the digital maturity of SMEs, tracing its development from addressing business challenges to establishing a comparative analysis framework grounded in Resource Dependence Theory (RDT).

DMAM is based on positivist philosophy and objectivist epistemology, supported by Design Science Research (DSR) and Capability Maturity Model Integration (CMMI). The methodology involves iterative development, from problem identification to creating a practical solution for assessing SMEs' digital maturity and guiding digitalization efforts.

DMAM offers a clear and specific methodology, distinguishing itself by addressing the unique needs of SMEs, particularly resource-dependent ones. The model’s development fills critical gaps in existing literature and provides a practical artifact for SMEs' digitalization.

DMAM is original in its focus on the specific needs of resource-dependent SMEs, offering actionable recommendations and addressing shortcomings in existing models. It serves as a foundational framework for SMEs' digital transformation, making a significant contribution to the digital maturity assessment literature.

The purpose of this paper is to provide a systematic review of literature on corporate engagement with start-ups (CEWS) by identifying the modes, contexts, antecedents, barriers and outcomes. As an emerging field, CEWS presently has no such review available which will help in building consensus within the field and shape future research directions.

The study followed a two-phased systematic review of literature. Three research databases (i.e. Web of Science, ScienceDirect and SCOPUS) were accessed to gather and conduct the review. Of the total 379 papers retrieved, 63 total relevant papers were studied and analysed. The exhaustive review of literature helped to uncover the contexts, perspectives, antecedents, outcomes and barriers reported across the different modes of CEWS.

The study highlighted the five prominent modes of CEWS favoured by large corporations and start-ups. It found that the large corporations and start-ups associate with one another on the basis of complementarities of activities, resources and motives to pursue their strategic orientations. The engagements also face barriers on the ground, such as incompatibility of goals, power imbalances, cultural differences and weak engagement plans. Most important contexts seen were the high-technology industries in the developed economies like the USA and Europe. It also found that ecosystem creation, accessing innovation and corporate strategy have been preferred as the most productive modes of CEWS in the literature.

This review provides practitioners with a detailed list of the modes and drivers of CEWS. Subsequently, the barriers that need to be managed to successfully execute a specific mode of engagement. This shall enable the practitioners in developing and adopting the best practices while engaging with the start-ups to better facilitate the outcomes of CEWS.

To the best of the authors’ knowledge, there is no systematic literature review available in the domain of CEWS – thus, this study makes an important methodological contribution to the field. By consolidating the fragmented yet growing knowledge on CEWS, the study presents a detailed understanding of what drives and obstructs the engagement between large corporations and start-ups.

The research aims to investigate how digital transformation (DT), entrepreneurial orientation (EO) and socioemotional wealth (SEW) impact the financial performance of family firms in uncertain business environments. Drawing from existing literature, we propose that DT and EO drive firm performance. Additionally, we suggest a new role for SEW, which positively moderates this relationship in family firms, especially in terms of risk behavior and innovation for survival.

We used the STEP Consortium’s 2020–2021 database, derived from a global survey that explored how family businesses responded to environmental shocks. Following STEP’s definitions, we proposed three hypotheses and tested two models using structural equation modeling.

The findings show that EO significantly enhances the impact of DT on family firm performance. Family businesses exhibit a notable willingness to take strategic venture risks to protect their SEW. These findings align with conclusions drawn in related literature, supporting all hypothesized relationships proposed.

The study has made an applied contribution by challenging the misconception that family firms are outdated and provides insights into supporting their approach to entrepreneurship, innovation and transgenerational entrepreneurship. Furthermore, it provides business families and consultants with a new view of SEW as a strategic asset.

Our study adds to the literature by showing how entrepreneurial orientation catalyzes the positive impact of digital transformation on firm financial performance. We also highlight the contextual influence on family firm decision-makers' risk propensity, which affects SEW development and firm outcomes. This context dependency of SEW can hinder or enhance performance, offering new research and support avenues for family firms.

Entrepreneurial ecosystems (EEs) contribute to organisational success through enabling actors to restructure businesses, stimulating exchanges of resources as well as applications and improvements to technological approaches. Hence, the purpose of this paper is to study the impact of EE micro-level variables on digital transformations.

Based on data spanning 5,000 Portuguese firms, the authors selected a random sample of 300, including businesses in the industrial, retail and service sectors. The authors deployed the multiple linear regression statistical method to validate the hypotheses.

As a result, the authors may conclude the organisation and the micro-level actors of EEs, owners and their members of staff produce influences on digital transformation processes.

This study contributes to completing the gap in the literature regarding the shortage of quantitative empirical studies approaching micro-level EE variables from the perspective of their relationships with digital transformation processes.