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This paper explores how conflicting institutional logics shape the behaviors of macro- and micro-level actors in their use of a calculative practice. Thereby, this paper explains how quantification can undermine the intended purpose of a governance system based on a single number.

The study draws upon the literature on calculative practices and institutional logics to present the case of how a single number—specifically the conversion factor for Atlantic Cod, established by macro-level actors for the purposes of governance within the Norwegian fishing industry—is interpreted and used by micro-level actors in the industry. The study is based on documents, field observations and interviews with fishers, landing facilities, and control authorities.

The use of the conversion factor, while intended to protect fish stock and govern industry actions, does not always align with the institutional logics of micro-level actors. Especially during the winter season, these actors may seek to serve their interests, leading to potential system gaming. The reliance on a single number that overlooks seasonal nuances can motivate unintended behaviors, undermining the governance system’s intentions.

Integrating the literature on calculative practices with an institutional logics perspective, this study offers novel insights into the challenges of using quantification for the governance of complex industries. In particular, the paper reveals that when the logics of macro- and micro-level actors conflict in a single-number governance system, unintended outcomes arise due to a domination of the macro-level logics.

This paper aims to determine the implications of Covid-19 on the livelihood of marine fishermen. It gives a concrete picture of how vulnerable communities like marine fishermen are affected due to the lockdown policies. The paper examines these communities' present status and the extent of vulnerability during the post-Covid period.

The study uses an exploratory research design to find the solution to the research problem. 298 samples were collected and analysed within a sustainable livelihood theoretical framework. The scope of the study is limited to marine fishermen in Kerala, residing in six districts out of the nine coastal districts. The impact of the lockdown on income was analysed using paired t-test and results linked with the theory.

The study has done an empirical analysis for three periods: before lockdown, lockdown and after lockdown, to identify the impact of lockdown on marine fishermen. The study's significant findings are that these fishermen's livelihood is at risk during the post-lockdown period, and many families are moving into a “debt-trap”.

Policymakers can develop appropriate policy strategies to enhance the livelihood assets of vulnerable communities to include them in a sustainable framework.

Only a few studies are highlighting the impact of Covid-19 on vulnerable communities in India. The effects of climate change on the marine ecosystem are already endangering marine fisher folks' livelihoods. In this light, it is vital to study the extent of the impact of income shock on the livelihood assets of marine fishermen due to the lockdown policy implemented in the State to prevent the spread of Covid-19.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0192

The study aims to analyse the race towards green development and United Nations sustainable development goals (SDGs) in the cases of Huawei and Shell. Both companies are the leaders in their respective industries. Huawei is an example case study representing the information and communications technology (ICT) industry whereas Shell is an example case study representing the oil and gas industry. The research analyses of the races in achieving UN SDGs were undertaken based on the innovation diffusion framework with the use of machine learning algorithms trained to extract data on sustainability activities and initiatives.

The research analyses the two case studies of Huawei and Shell. The research was undertaken through the steps of training machine learning algorithms, industry benchmarking and evaluating the performance of the race. The analyses regarding the activities and initiatives of Huawei and Shell in contributing towards SDGs are based on the data in the past 10 years (Years 2010–2019) using machine learning to extract data on sustainability activities and initiatives. In the case of Huawei, 313 sustainability reports were fed to the unsupervised machine learning algorithms revealing 15,101 sustainability actions and initiatives related to UN SDGs in the ICT industry. In the case of Shell, 2,015 sustainability reports were fed to the unsupervised machine learning algorithms revealing 47,365 sustainability actions and initiatives related to UN SDGs in the oil and gas industry.

The analyses of findings revealed that Huawei and Shell performed very well in progressing towards the UN SDGs. Huawei had strong performance in the ICT industry with regard to SDGs No. 3, 4, 7, 8, 11, 12 and 16 while Shell had strong performance in the oil and gas industry with regard to SDGs No. 3, 4, 6, 7, 8, 12 and 16. Both companies had placed a focus on achieving SDG 12 responsible consumption and production, SDG 7 affordable and clean energy and SDG 4 quality education. The synthesised business model innovations of Huawei and Shell had shown their environmental, social and governance strategies – Huawei’s 2030 vision for green development and Shell’s 2050 vision for net zero emissions.

The five pillars of people, planet, prosperity, peace and partnership according to the UN 2030 agenda for sustainable development have shown the way a company operates to promote sustainable eco-systems. The extent to which both Huawei and Shell link corporate strategies to the UN SDGs has reflected their implementation progress. Furthermore, the business model innovations of Huawei and Shell provides a useful framework which can be applied to encourage other companies/organisations in various industries to undertake ESG activities in practice.

The main contribution of this research is the application of machine learning algorithms and the innovation diffusion model in analysing the SDGs performance. The study applies the innovation diffusion framework to explore strategic actions and initiatives of Huawei and Shell in transitioning towards sustainability. The use of machine learning algorithms has identified their sustainability approach in achieving the UN SDGs.

How an entrepreneurial organisation sets the problem space determines the future venturing mode. However, the factors that contribute to differences in problem space are still not well-developed. Based on sensemaking theory, this study explores the influence mechanism and boundary conditions of organisational sensemaking on effectual problem setting.

The study is based on survey data from 162 entrepreneurial organisations in China. Hierarchical regression is used for analysing the data and testing the hypotheses.

Organisational sensemaking has a negative effect on effectual problem setting and a positive impact on outside-in entrepreneurial marketing capability; outside-in entrepreneurial marketing capability has a negative effect on effectual problem setting; outside-in entrepreneurial marketing capability plays a partially mediating role in the relationship between organisational sensemaking and effectual problem setting. Organisational size negatively moderates the relationship between organisational sensemaking and outside-in entrepreneurial marketing capability. It also negatively moderates the indirect effect of organisational sensemaking on effectual problem setting through outside-in entrepreneurial marketing capability.

First, this study contributes to the research on effectual problem setting by introducing organisational sensemaking as an antecedent. Second, this study extends the literature on organisational sensemaking by showing how organisational sensemaking affects entrepreneurial uncertainty, instead of treating uncertainty as an exogenous shock. Third, this study introduced the outside-in entrepreneurial marketing capability to reveal the mediating mechanism between organisational sensemaking and effectual problem setting.

New ventures often encounter legitimation challenges due to their liability of newness and foreignness. This particularly applies to the legitimacy beyond the local entrepreneurial ecosystem (EE). The present study examines how new ventures’ local legitimacy influences legitimacy diffusion beyond the local EEs. It considers both the direct relationship between new venture local legitimacy and its diffusion beyond the EE and the moderating effects of legitimacy brokerage and network activities on this relationship.

A hierarchical multiple linear regression is employed to test a series of hypotheses using the data of 228 Finnish firms which was collected with an online survey.

Firms that garner active local legitimacy have a greater chance to diffuse that legitimacy beyond an existing ecosystem. Results also reveal that network activities and legitimacy brokerage enhance (positively moderate) the association between (passive and active) local legitimacy and its diffusion.

The present study contributes to and extends the literature at the intersection of new venture legitimacy and legitimacy diffusion beyond the existing EE – an aspect which has not been sufficiently studied.

Over the past two decades, the study of team resilience has evolved from focusing primarily on team performance to recognizing its importance in various aspects of team functioning, including psychological health, teamwork, and overall Well-Being. This evolution underscores the need for a broader, more inclusive understanding of team resilience, advocating for a shift from a narrow performance-centric view to a holistic perspective that encompasses the multifaceted impact of resilience on teams.

In advocating for this holistic perspective, this chapter reviews the extant literature, highlighting that resilience is not merely about sustaining performance but also about fostering a supportive, adaptive, and psychologically safe environment for team members. Significant areas for further exploration, including the nuanced nature of adversities teams face, the processes underpinning resilient behaviors, and the broad spectrum of outcomes resilience can influence beyond task performance are also discussed.

The chapter serves as a call to action for a more inclusive examination of how resilience manifests and benefits teams in organizational settings. The proposed shift in perspective aims to deepen understanding of team resilience, promoting strategies for building resilient teams that thrive not only in performance but in all aspects of their functioning.

Identifying the flow regime is a prerequisite for accurately modeling two-phase flow. This paper aims to introduce a comprehensive data-driven workflow for flow regime identification.

A numerical two-phase flow model was validated against experimental data and was used to generate dynamic pressure signals for three different flow regimes. First, four distinct methods were used for feature extraction: discrete wavelet transform (DWT), empirical mode decomposition, power spectral density and the time series analysis method. Kernel Fisher discriminant analysis (KFDA) was used to simultaneously perform dimensionality reduction and machine learning (ML) classification for each set of features. Finally, the Shapley additive explanations (SHAP) method was applied to make the workflow explainable.

The results highlighted that the DWT + KFDA method exhibited the highest testing and training accuracy at 95.2% and 88.8%, respectively. Results also include a virtual flow regime map to facilitate the visualization of features in two dimension. Finally, SHAP analysis showed that minimum and maximum values extracted at the fourth and second signal decomposition levels of DWT are the best flow-distinguishing features.

This workflow can be applied to opaque pipes fitted with pressure sensors to achieve flow assurance and automatic monitoring of two-phase flow occurring in many process industries.

This paper presents a novel flow regime identification method by fusing dynamic pressure measurements with ML techniques. The authors’ novel DWT + KFDA method demonstrates superior performance for flow regime identification with explainability.

This study aims to examine whether energy poverty impacts gender inequality and CO₂ emissions in African countries with the biggest economies by gross domestic product (GDP) per capita from 1996 to 2020. Additionally, this study examines the existence of the gender Kuznets curve (GKC) and the environmental Kuznets curve (EKC) theories. Furthermore, it evaluates the connection between economic development and carbon emissions, on the one hand, and economic development and gender inequality on the other.

This study uses the augmented Dickey–Fuller and Phillip–Perron unit root tests to determine the degree of integration between the variables. It also uses the Pedroni and Fisher–Combine Johansen cointegration tests to assess a long-run relationship between the variables. The authors adopted the pooled mean group (PMG)-autoregressive distributed lag model and used the E-Views 12 software to run the analysis.

The empirical analysis approves the long-run correlation among the variables used in this study. Increased energy poverty and GDP increase CO₂ emissions, whereas income square hurts CO₂ emissions. These results are consistent with the EKC hypothesis, which proposes a non-linear relationship between CO₂ emissions and economic growth in the studied areas (similar to an inverted U shape). Long-term foreign direct investment (FDI) has a negative correlation with CO₂ emissions. On the contrary, energy poverty, GDPsq and FDI find a positive relationship with gender inequality, whereas GDP finds a negative association with gender inequality. The negative relationship between GDPsq and gender inequality establishes a “U”-shaped connection between income and gender inequality. Thus, it supports the hypothesis of the GKC. Therefore, this study proposes that decreasing energy poverty is vital for promoting a clean environment and mitigating gender inequality.

This study supports the hypothesis of the GKC. Therefore, this study proposes that decreasing energy poverty is vital for promoting a clean environment and mitigating gender inequality.

This study aims to examine the performance implications of an information governance (IG) framework for managing, controlling access to and securing information, focusing on (1) the performance benefits of an organization's IG orientation and (2) how the configuration of IG orientation and supply chain (SC) strategy type relate to performance outcomes.

This study leverages multiple secondary sources for US hospitals, serving as the context for the study. It also employs cluster analysis to develop an SC strategy taxonomy, namely sophisticated and delivery-focused SC strategies. The proposed research model is tested using a robust regression to mitigate the influence of outliers and produce more accurate estimates.

IG orientation is positively associated with financial performance and patient experience, and IG-oriented hospitals with a sophisticated SC strategy realize more financial benefits and achieve better patient care experiences compared to other configurations. Regardless of SC strategy type, IG-oriented hospitals offer better care experiences than non-IG-oriented hospitals.

This paper offers empirical evidence that a hospital's IG orientation and SC strategy jointly affect financial outcomes and patient experience. For hospitals, an organization-wide framework for governing information streamlines both intra- and inter-organizational information flows and improves care delivery throughout a patient's care experience.

This is one of a few studies that empirically examine the performance implications of governance of information in the domain of supply chain management (SCM). This study also develops an SC strategy taxonomy for the healthcare context and offers a springboard for research in service SC strategy.

Interim leaders often have little advance notice of their new assignments. Yet, they must skillfully lead their organizations, provide stability for staff and continue the direction of the mission and vision in a time of change. In addition, temporary leaders – often termed interim executive directors or interim chief executive officers (CEOs) – are frequently asked to guide the transition for a new and permanent leader.

This qualitative study presents the insights of 24 interim leaders, largely in the Chattanooga, Tennessee (TN) region, who participated in individual virtual interviews and a subsequent virtual focus group to address a protocol of questions concerned with all phases of carrying out the interim position.

The findings confirmed existing literature on how the interim was selected, the responsibilities of this leader and the costs and benefits for the organization of using an interim and extended findings with guidance for interim over their tenure.

The findings uncovered new insights into personal and career growth, along with unexpected personal and professional enrichment and satisfaction from the experience. The practical implications include providing detailed guidelines for interim leaders at each stage of their tenure, which can help them navigate the complexities of their roles more effectively. Additionally, the findings highlight the potential for significant personal and professional growth, offering interim leaders unexpected enrichment and satisfaction from their experiences.

The exploratory research validated the existing literature on interim leadership and added additional detail in practical guidance for beginning an interim position, carrying out the interim position and even ending the position. This study delineates practical guidelines at each stage of the interim lifecycle for both the temporary leader and the organization and provides areas for future research. Qualitative findings also identified key characteristics of an interim leader. This study also includes discussion of the political implications of interim CEOs.

The study presents original insights into the role of interim leaders by combining qualitative data from 24 participants in the Chattanooga, TN region with existing literature, thereby enhancing understanding of the challenges and successes these leaders face. It confirms previous findings regarding interim leadership and provides practical guidelines for navigating the interim lifecycle, highlighting aspects of personal growth and satisfaction that have not been extensively explored in prior research.