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Academic research has intensively analyzed the relationship between market concentration or market power and banking stability but provides ambiguous results, which are summarized under the concentration-stability/fragility view. We provide empirical evidence that the mixed results are due to the difficulty of identifying reliable variables to measure concentration and market power.

Using data from 3,943 banks operating in the European Union (EU)-15 between 2013 and 2020, we employ linear regression models on panel data. Banking market concentration is measured by the Herfindahl–Hirschman Index (HHI), and market power is estimated by the product-specific Lerner Indices for the loan and deposit market, respectively.

Our analysis reveals a significantly stability-decreasing impact of market concentration (HHI) and a significantly stability-increasing effect of market power (Lerner Indices). In addition, we provide evidence for a weak (or even absent) empirical relationship between the (non)structural measures, challenging the validity of the structure-conduct-performance (SCP) paradigm. Our baseline findings remain robust, especially when controlling for a likely reverse causality.

Our results suggest that the HHI may reflect other factors beyond market power that influence banking stability. Thus, banking supervisors and competition authorities should investigate market concentration and market power simultaneously while considering their joint impact on banking stability.

Because family businesses are highly complex enterprises, researchers need appropriate theoretical and methodological tools to study them. The neoconfigurational perspective and its accompanying method, qualitative comparative analysis, are particularly well suited to phenomena characterized by complex causality, but their uptake in family business research has been slow and fragmented. To remedy this, the authors highlight their unique ability to address research questions for which other approaches are not well suited and discuss how they might be applied to family business phenomena.

The authors introduce the core tenets of the neoconfigurational perspective and how its set-theoretic epistemology differs from traditional approaches to theorizing and analysis. The authors then use a dataset of family firms to present a primer on conducting qualitative comparative analysis and interpreting the results.

The authors find that family firm resources can be combined in multiple ways to affect business survival, suggesting that resources are substitutable and complementary. The authors discuss how the unique features of the neoconfigurational approach, namely equifinality, conjunctural causation and causal asymmetry, can be fruitfully applied to break new ground in scholarly understanding of family businesses.

This article allows family business researchers to apply the neoconfigurational approach without first having to consult multiple and disparate sources often written for other disciplines. This article explicates how to leverage the theoretical and empirical advantages of the neoconfigurational approach in the context of family businesses, supporting a more widespread adoption of the neoconfigurational perspective in family business research.

This study employs Stein Rokkan's methodological approach to analyse state formation in the Greater Middle East. It develops a conceptual framework distinguishing colonial, populist and democratic pacts, suitable for analysis of state formation and nation-building through to the present period. The framework relies on historical institutionalism. The methodology, however, is Rokkan's. The initial conceptual analysis also specifies differences between European and the Middle Eastern state formation processes. It is followed by a brief and selective discussion of historical preconditions. Next, the method of plotting singular cases into conceptual-typological maps is applied to 20 cases in the Greater Middle East (including Afghanistan, Iran and Turkey). For reasons of space, the empirical analysis is limited to the colonial period (1870s to the end of World War 1). Three typologies are combined into one conceptual-typological map of this period. The vertical left-hand axis provides a composite typology that clarifies cultural-territorial preconditions. The horizontal axis specifies transformations of the region's agrarian class structures since the mid-19th century reforms. The right-hand vertical axis provides a four-layered typology of processes of external intervention. A final section presents selected comparative case reconstructions. To the authors' knowledge, this is the first time such a Rokkan-style conceptual-typological map has been constructed for a non-European region.

This paper aims to explore how leaders can develop value-based leadership for sustainable quality development in Lean manufacturing.

A qualitative meta-analysis was conducted using data from a three-year study of Lean manufacturing in Sweden using the Shingo business excellence model as an analytical framework.

This study demonstrates that leaders can develop value-based leadership to support Lean manufacturing by defining and articulating the organization’s values and accompanying behaviors that are needed to support the strategic direction; creating forums and time for leaders to identify the why behind decisions and reflect on their experiences to be able to lead a transformative process; and using storytelling to create a coaching culture to connect values and behaviors, to the processes and systems of work.

This paper contributes insights for developing value-based leadership to support a systemic approach to sustainable quality development in lean manufacturing. Findings are based on a limited case sample size of three manufacturing companies in Sweden.

The findings were derived using a unique methodological approach combining storytelling, appreciative inquiry and coaching with traditional data collection methods including surveys and interviews to identify, define and shape value-based leadership in Lean manufacturing.

This pan-Canadian study examines the information practices of STEM-trained immigrant women to Canada as they navigate workfinding and workplace integration. Our study focuses on a population of highly skilled immigrant women from across Canada and uses an information practice lens to examine their lived experiences of migration and labour market integration. As highly trained STEM professionals in pursuit of employment, our participants have specific needs and challenges, and as we explore these, we consider the intersection of their information practices with government policies, settlement services and the hiring practices of STEM employers.

We conducted a qualitative study using in-depth interviews with 74 immigrant women across 13 Canadian provinces and territories to understand the nature of their engagement with employment-seeking in STEM sectors. This article reports the findings related to the settlement and information experiences of the immigrant women as they navigate new information landscapes.

As immigrants, as women and as STEM professionals, the experiences of the 74 participants reflect both marginality and privilege. The reality of their intersectional identities is that these women may not be well-served by broader settlement resources targeting newcomers, but neither are the specific conventions of networking and job-seeking in the STEM sectors in Canada fully apparent or accessible to them. The findings also point to the broader systemic and contextual factors that participants have to navigate and that shape in a major way their workfinding journeys.

The findings of this pan-Canadian study have theoretical and practical implications for policy and research. Through interviews with these STEM professionals, we highlight the barriers and challenges of an under-studied category of migrants (the highly skilled and “desirable” type of immigrants). We provide a critical discussion of their settlement experiences and expose the idiosyncrasies of a system that claims to value skilled talent while structurally making it very difficult to deliver on its promises to recruit and retain highly qualified personnel. Our findings point to specific aspects of these skilled professionals’ experiences, as well as the broader systemic and contextual factors that shape their workfinding journey.

This study focuses on the triadic multilevel psychic distance (MPD) between the firm, target market and bridge-maker and its consequences for firm internationalization. Specifically, it spotlights the triadic psychic distance between firms, the levels of psychic distance in the target market (country and business) and the bridge-maker. Therefore, this study examines the triadic MPD among these three entities and its impact on firm internationalization.

This study uses qualitative and case study research approaches. It is based on 8 case companies and 24 internationalization cases. Secondary data were collected, and interviews with bridge-makers and industry experts were conducted.

The study found that MPD appeared in the triad. The MPD between firms and markets is related to country-specific differences and business difficulties. The MPD between the firm and the bridge-maker is based on the latter’s lack of knowledge vis-à-vis bridging the firm’s MPD. Finally, the MPD between bridge-makers and the market is based on the former’s lack of knowledge of the home country’s business difficulties.

This is the first study to develop and adopt a triadic multilevel psychic distance conceptualization that provides evidence for and sheds light on the triadic MPD and its effect on firm internationalization. This study identifies the reasons behind triadic MPD in connection to firm internationalization. Notably, firm internationalization is interdependent on the triadic MPD setting between the firm, bridge-maker and target market. It has theoretical value and contributes to the recent advancement in the understanding of MPD in international marketing literature.

Agriculture is the backbone of a country, contributing more than half of the sector of economy throughout the world. The need for precision agriculture is essential in evaluating the conditions of the crops with the aim of determining the proper selection of pesticides. The conventional method of pest detection fails to be stable and provides limited accuracy in the prediction. This paper aims to propose an automatic pest detection module for the accurate detection of pests using the hybrid optimization controlled deep learning model.

The paper proposes an advanced pest detection strategy based on deep learning strategy through wireless sensor network (WSN) in the agricultural fields. Initially, the WSN consisting of number of nodes and a sink are clustered as number of clusters. Each cluster comprises a cluster head (CH) and a number of nodes, where the CH involves in the transfer of data to the sink node of the WSN and the CH is selected using the fractional ant bee colony optimization (FABC) algorithm. The routing process is executed using the protruder optimization algorithm that helps in the transfer of image data to the sink node through the optimal CH. The sink node acts as the data aggregator and the collection of image data thus obtained acts as the input database to be processed to find the type of pest in the agricultural field. The image data is pre-processed to remove the artifacts present in the image and the pre-processed image is then subjected to feature extraction process, through which the significant local directional pattern, local binary pattern, local optimal-oriented pattern (LOOP) and local ternary pattern (LTP) features are extracted. The extracted features are then fed to the deep-convolutional neural network (CNN) in such a way to detect the type of pests in the agricultural field. The weights of the deep-CNN are tuned optimally using the proposed MFGHO optimization algorithm that is developed with the combined characteristics of navigating search agents and the swarming search agents.

The analysis using insect identification from habitus image Database based on the performance metrics, such as accuracy, specificity and sensitivity, reveals the effectiveness of the proposed MFGHO-based deep-CNN in detecting the pests in crops. The analysis proves that the proposed classifier using the FABC+protruder optimization-based data aggregation strategy obtains an accuracy of 94.3482%, sensitivity of 93.3247% and the specificity of 94.5263%, which is high as compared to the existing methods.

The proposed MFGHO optimization-based deep-CNN is used for the detection of pest in the crop fields to ensure the better selection of proper cost-effective pesticides for the crop fields in such a way to increase the production. The proposed MFGHO algorithm is developed with the integrated characteristic features of navigating search agents and the swarming search agents in such a way to facilitate the optimal tuning of the hyperparameters in the deep-CNN classifier for the detection of pests in the crop fields.

This study aims to contribute to the academic disciplines of entrepreneurship and management by developing a new theory that explains Founder-CEOs’ succession in family and non-family firms. Many scholars failed to generate a specific theory to describe the succession of Founder-CEOs. Family firms remain complex enterprises comprising interconnectedness of cultural interests in which corporate governance occurs by families, Founder-CEOs and sometimes a board of directors.

This study’s design/methodology/approach reflects post-modernist epistemological and ontological perspectives for conducting systematic literature reviews. To identify relevant studies in the review, the several databases (Australian Business Dean’s Council Journal Quality List; EBSCO Database, including PsycINFO and Psych studies; Web of Science) and a mix of ranked journals from entrepreneurship, management and psychology were used.

The findings and results in this paper reflect the purpose, methodology and literature analysis culminating in 1,582 peer-reviewed studies. A total of 182 peer-reviewed studies met the criterion for review. Throughout the research process, a systematic literature review uncovered management literature gaps overlooked for decades during the theory-building process. Hence, developing a theory of Founder-CEOs succession used a combination of systematic, inductive, comparative and interactive approaches.

A Theory of Founder-CEOs Succession explains the strategic process of replacing a founder systematically. The promotion of, and incentives for, internal executives have been topics of great interest and deliberation among scholars and practitioners for a long time. This study contributes research implications for theory building in the academic disciplines of entrepreneurship and management by offering scholars and practitioners a theory that does not exist to describe Founder-CEOs’ succession encompassing both strategic successes and failures. By incorporating successes and failures, this study provides realistic reflections of Founder-CEOs.

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.

This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.

This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.

This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.

This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.