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The purpose of this study is to identify the factors that contribute to the successful implementation and management of sustainable innovation in research-intensive sectors such as the life sciences industry.

The study was conducted through a combination of two methods. The first was qualitative interviews of 21 sustainability experts and leaders in the life sciences industry who were responsible for implementing sustainable innovation. They were selected through nonprobabilistic purposive sampling. The second method was thematic content analysis using the MAXQDA software.

The study identified that successful implementation of sustainable innovation in research-intensive firms begins with the alignment of the executive vision for sustainability with the business objectives of the research-intensive firm. Furthermore, implementation of sustainability practices is identified as a function of organizational reconfigurations that facilitate purposeful inflow and outflow of ideas and knowledge between internal firm resources and external stakeholders, anchored by the objectives of the research-intensive firm.

The study explicated factors only within life sciences industry based on qualitative interviews. The study offers scope for cross-sector quantitative evaluation.

To the best of the authors’ knowledge, this study is among the first studies to systematically delineate the underlying factors that govern successful implementation of sustainable innovation in research-intensive industries, through integration of the resource-based view and stakeholder theory and thereby provide a framework for research-intensive organizations to implement sustainable innovation practices.

This paper aims to look at the implementation of project-funded research governance and its potential to induce organisational learning on responsible research and innovation (RRI). This paper analysed what types of organisational learning and change can take place within organisations of an Europe-funded project and to what extent. This paper examined whether and how change occurs and how it is shaped and co-produced with other orderings.

The paper is based on materials and evidence collected while working on the internal evaluation of a Horizon 2020-funded project. Analysis of the results of the mixed methods evaluation design was used to characterise occurrences of organisational learning and change.

The authors identified different forms of learning (single-loop learning, double-loop learning, reflexive and reflective learning and situational learning). The extent of learning that could lead to long-lasting organisational change was limited. This was due to the project-based and organisational design, the key-based definition of RRI and the indeterminacy of what constitutes learning and change – both at the level of funding and performing the project. For organisational change to occur, the authors argue for governance mechanisms based on reflexive learning that consider a range of structural conditions and measures.

Organisational learning plays an important role in change processes, which has so far been given too little consideration concerning the governance and implementation of RRI through project-based funding. The authors argue for a restructuring of governance and funding mechanisms to create more space for reflexivity and learning.

The purpose of this conceptual paper is to explore the role of strategic leadership under conditions of uncertainty and unpredictability. The authors argue that highly improbable, but high-impact events require the upper echelons of management, traditionally the custodians of strategy formulation to offer a new kind of strategic leadership focused on new mindsets, organizational capabilities, more in tune with high uncertainty and unpredictability.

Drawing on strategic leadership, and complexity leadership theory, the authors review the literature and present a conceptual framework for exploring the nature of strategic leadership under uncertainty. The authors conceptualize organizations as complex adaptive systems and discuss the imperatives for developing new mental models for emergent leadership.

Strategic leaders have a key role to play in preparing their organizations for episodic disruptions. These include developing their adaptive capabilities and building resilient organizations to ensure their organizations cannot only bounce back after a disruption but have the capacity for transformation to new fitness levels when necessary. Strategic leaders must engage with complexity leadership by seeing their organizations as complex adaptive systems, reconfigure their leadership approaches and organizations to build strategic adaptive capability.

This is a conceptual paper and the authors cannot make any claims of causality.

Organizational leaders need to reconfigure their mental models and leadership approaches to reflect the new normal of uncertainty and unpredictability. Developing the strategic adaptive capability of organizations should prepare them for dealing with high impact events. To assure business continuity in the face of disruptions requires building flexible, adaptable business models.

The paper focuses on how managers can offer strategic leadership for a new normal that challenges some of our most cherished leadership and strategic management paradigms. The authors explore the new mental models and leadership models in an era of great uncertainty.

Replication is a primary self-correction device in science. In this paper, we have two aims: to examine how and when the results of replications are used in management and organization research and to use the results of this examination to offer guidelines for improving the self-correction process.

Study 1 analyzes co-citation patterns for 135 original-replication pairs to assess the direct impact of replications, specifically examining how often and when a replication study is co-cited with its original. In Study 2, a similar design is employed to measure the indirect impact of replications by assessing how often and when a meta-analysis that includes a replication of the original study is co-cited with the original study.

Study 1 reveals, among other things, that a huge majority (92%) of sources that cite the original study fail to co-cite a replication study, thus calling into question the impact of replications in our field. Study 2 shows that the indirect impact of replications through meta-analyses is likewise minimal. However, our analyses also show that replications published in the same journal that carried the original study and authored by teams including the authors of the original study are more likely to be co-cited, and that articles in higher-ranking journals are more likely to co-cite replications.

We use our results to formulate recommendations that would streamline the self-correction process in management research at the author-, reviewer- and journal-level. Our recommendations would create incentives to make replication attempts more common, while also increasing the likelihood that these attempts are targeted at the most relevant original studies.

Data science industry is a multidisciplinary field that deals with a large amount of data and derives useful information for taking routine and strategic business decisions. The purpose of this article is to examine the relationship between pricing models, engagement models, and firm performance (FP). This study also aims at uncovering the most effective pricing model and engagement model for improving FP.

Indian data scientists were the respondents of the study. A total of 213 responses were carefully chosen. The data were analyzed using structural equations on Statistical Package for Social Sciences-Analysis of Moment Structures (SPSS-AMOS) version 25 software.

The findings of the study suggested the positive and significant impact of pricing models and engagement models on FP. Value-based pricing strategies have the maximum impact on FP. On the other hand, managed services have a higher influence on FP.

By developing a multi-faceted framework, this study is a novel contribution to the field of business strategy, especially for the data science industry.

Despite rapid growth in blockchains, there was limited discussion about non-technical and technical factors on blockchain governance in the extant literature. This study aims to contribute new knowledge to the literature on potential factors affecting the adoption, governance and scale-up of blockchain technologies in the health-care and energy sectors, presented in a holistic framework.

This study adopts the qualitative case study research methodology to research blockchain governance in practice. The authors contacted a national blockchain consortium to conduct their research on the governance issue of blockchain. Two leading case organizations, one from the health-care industry and another from the energy industry, were deliberately selected for their study for their active role and reputation in the consortium and practical experience in blockchain governance.

The developed framework helps identify potential research gaps or concerns on adopting a blockchain as well as assessing blockchain implementation and governance in other industries. Depending on the circumstances, some of the factors can be either drivers or obstacles to further blockchain development. The different forces may also be more or less evident over time as blockchains develop. The two real-world case studies contribute to the information technology governance literature on blockchain governance.

The results of this case studies will be beneficial for developing theories and empirical models to determine antecedents for achieving consensus and trust in blockchain and testing the relationship between these factors and blockchain governance at different levels. As a result, theories related to the governance of blockchain technologies could be further developed.

This study aims to investigate the claim that there is no coherent and homogeneous body of concepts and practices that can be classified as “Islamic accounting”.

The study focuses specifically on Islamic accounting and uses a qualitative historical documentary analysis methodology to study an original manuscript from the 14th century.

The analysis of the manuscript argues that religious accounting can be seen as a value-based system for achieving social good and that in the context of Islamic accounting, it can be conceptualised as a coherent body of ideas and practices.

Firstly, the study conceptualises Islamic accounting as a homogeneous discipline with its own knowledge, concepts and practices. Secondly, it contributes to current accounting literature by examining an ancient manuscript from the 14th century, which serves as a foundation for understanding the Islamic accounting system within the context of accounting, religion and spirituality. The paper further contributes by arguing that this conceptualisation of religious accounting as a value-based approach enables its practitioners to evaluate their own accountabilities in delivering on socioeconomic objectives related to inter-human/environmental, social and financial transactions within the context of religious accounting practices.

Interdependence on the global economy and rapid technological changes raised the degree of uncertainty and complexity, leading to innovation challenges. Innovation depends on knowledge, and the solution might rest on how sound firms manage it, particularly in emerging markets such as India. The purpose of this paper is to examine how firms implement knowledge management (KM) in highly innovation-oriented firms (biotechnology and pharmaceuticals) and the factors affecting its implementation by examining knowledge interactions between individuals.

This study consists of a systematic literature review, a case study with embedded units and the use of grounded theory to analyse the data. The factors emerging from the results were examined from an individual and organisational lens. Next, complexity theory (CT) was used to understand the impact of these factors in KM by facilitating its incorporation as a system.

The findings of this paper suggest that constant technology adoption increases human-to-technology interaction, higher circulation of existing knowledge and more controlled environments, discouraging individuals from learning or sharing knowledge. From a system perspective, results of this paper suggest that firms self-organise around technology, indicating that innovation decreases as knowledge creation and sharing tend to reduce with lesser social interactions. This study shows the usefulness of using CT in analysing KM for innovation. The performance of the system is analysed based on its constituents and interactions.

This study contributes to advancing CT in KM in the context of innovation in highly knowledge-intensive firms, as few studies were found in the literature.

Human resource analytics (HRA) is an HR activity that companies and academics increasingly pay attention to. Existing literature conceptualises HRA mostly from an objectivist perspective, which limits understanding of actual HRA activities in the complex organisational environment. This paper therefore draws on the practice-based approach, using a novel framework to conceptualise HRA-as-practice.

The authors conducted a systematic literature review of 100 academic and practitioner-oriented publications to analyse existing HRA literature in relation to practice theory, using the “HRA-as-practice” frame.

The authors identify the main practices involved in HRA, by whom and how these practices are enacted, and reveal three topics in nomological network of HRA-as-practice: HRA technology, HRA outcomes and HRA hindrances and facilitators, which the authors suggest might actualize enactment of HRA practices.

The authors offer HR function and HR professionals a basic ground to evaluate HRA as a highly contextual activity that can potentially generate business value and increase HR impact when seen as a complex interaction between HRA practices, HRA practitioners and HRA praxis. The findings also help HR practitioners understand multiple factors that influence the practice of HRA.

This systematic review differs from the previous reviews in two ways. First, it analyses both academic and practitioner-oriented publications. Second, it provides a novel theoretical contribution by conceptualising HRA-as-practice and comprehensively compiling scattered topics and themes related to HRA.

Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.

This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.

Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.

The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.

The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.

The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.

The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.