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This study aims to investigate the relationship between religiosity, belief in a just world (BJW), trust and affinity fraud.

Using an online panel vendor, this study collected survey data from 1,030 participants. Participants are balanced based on US Census data.

This study finds evidence that religiosity and, to a lesser extent, trust were correlated with choosing an affinity investor but not BJW. Overall, this study adds to the literature on fraud by examining the potential processes of tricking a victim.

This study examines the complex decision-making around investing with fraudsters. This study disentangles the relationship between affinity fraud, decision-making, trust and religiosity. Furthermore, this consider the reasons why a shared affinity may increase trust through the lens of the decision-maker.

This study aims to examine the international market selection process of entrepreneurs operating internationally.

Four small and medium-sized comparative and rich-information case studies were purposefully selected from among Australian and Arabian firms. Data were collected via in-depth personal interviews, follow-up interviews and questionnaire instrument.

The results revealed that entrepreneurs used a four-stage systematic decision-making process to attain profitable foreign market choices. The decision process was influenced by cognitive boundaries as entrepreneurs relied on the availability experiential, anchoring and adjustment heuristic.

The research’s findings and the proposed decision model will, significantly, assist entrepreneurs, willing to expand internationally, in enhancing their decision-making to attain profitable foreign market choices. Further, it provides benefits to foreign investment policymakers in host countries by assisting them to attract more inward foreign direct investments, and, accordingly, enhance the economic and social development movement in their countries.

This study provides a significant theoretical contribution to the literature on the internationalization process of entrepreneurs and small- and medium-sized enterprises through developing a decision model for selecting and entering foreign markets by entrepreneurs in a cross-country context. Further, the study provides significant methodological contributions with regard to the effectiveness of the qualitative case study method in capturing elements of the foreign market selection process.

This paper aims to provide a novel explorative perspective on fund managers’ decisions under uncertainty. The current COVID pandemic is used as a unique reference frame to study how heuristics are used in institutional financial practice.

This study follows a grounded theory approach. A total of 282 diverse publications between October 2019 and October 2020 for 20 German mutual funds are qualitatively analyzed. A theory of adaptive heuristics for fund managers is developed.

Fund managers adapt their heuristics during a crisis and this adaptive process flows through three stages. Increasing complexity in the environment leads to the adaption of simplest heuristics around investment decisions. Three distinct stages of adaption: precrisis, uncertainty and stabilization emerge from the data.

This study’s data is based on publicly available information. There might be a discrepancy between publicly stated and internal reasoning.

Money managers can use the provided framework to assess their decision-making in crises. The developed adaptive processes of heuristics can assist capital allocators who choose and rate fund managers. Policymakers and regulators can learn about the aspects of investor decisions that their actions and communication address. Teaching can use this study to exemplify the nature of financial markets as adaptive systems rather than static structures.

To the best of the author’s/authors’ knowledge, this study is the first to systematically explore the heuristics of professional money managers because they navigate a large-scale exogenous crisis.

India liberalized its economy in 1991, which resulted in intense global competition, quality-conscious and demanding customers. Additionally, significant technological advancements lead to enhancements in products and processes. These forced Indian organizations to adopt innovative business strategies in the past 30 years. Meanwhile, the Lean Six Sigma methodology has significantly grown with vast applicability during the past 30 years. Thus, the purpose of this study is to develop the learning on Lean Six Sigma methodology in the Indian context through investigation of literature.

A three-stage systematic literature review approach was adopted to investigate the literature during the present study. In total, 187 articles published in 62 journals/conference proceedings from 2005 to 2022 (18 years) were shortlisted. The first part of the article summarizes the significant milestones towards the quality journey in the Indian context, along with the evolution of the Lean Six Sigma methodology. The second part examines the shortlisted papers on Lean Six Sigma frameworks, their applicability in industrial sectors, performance metrics, outcomes realized, publication trends, authorship patterns and leading researchers from the Indian perspective.

Lean Six Sigma has emerged as a highly acclaimed and structured business improvement strategy worldwide. The Indian economy has seen remarkable growth in the past decade and is one of the fastest-growing economies in the 21st century. Lean Six Sigma implementation in India has significantly increased from 2014 onward. The study revealed that researchers have proposed several different frameworks for Lean Six Sigma implementation, the majority of which are conceptual. Furthermore, the balanced applicability of Lean Six Sigma in manufacturing and service sectors was observed with the highest implementation in the health-care sector. Additionally, the widely adopted tools, techniques along with performance metrics exploring case studies were reported along with a summary of eminent and leading researchers in the Indian context.

This study is confined to reviewed papers as per the research criteria with a significant focus on the Indian context and might have missed some papers due to the adopted papers selection strategy.

The present study is one of the initial attempts to investigate the literature published on Lean Six Sigma in the Indian context, including perspective on the Indian quality movement. Therefore, the present study will provide an understanding of Lean Six Sigma methodology in the Indian context to graduating students in engineering and management and entry-level executives. The analysis and findings on Lean Six Sigma frameworks, research approach, publications details, etc., will be helpful to potential research scholars and academia. Additionally, analysis of case studies on Lean Six Sigma implementation by Indian industries will assist the managers and professionals in decision making.

The purpose of this study was to examine the preservice educational narratives of Black English teachers in an effort to determine their experiences within teacher education programs with assigned white cooperating teachers.

Drawing upon Black storytelling, testimony and breath in narrative analysis, this study showcases how Black preservice teachers navigated regularized surveillance and abandonment as part of student teaching practicum.

The authors argue that, in response to their treatment, these Black preservice teachers created resistance strategies as a way to fill the mentorship void and sustain their own future teaching careers.

The literature on Black preservice teachers does the critical work of examining how they experience their racial, linguistic and gendered identities in the classroom; however, this study focuses on their experiences with white cooperating teachers – an underresearched area in the past 10 years.

This study aims to propose a combined effect framework to explore the relationship between research and development (R&D) team networks, knowledge diversity and breakthrough technological innovation. In contrast to conventional linear net effects, the article explores three possible types of team configuration within enterprises and their breakthrough innovation-driving mechanisms based on machine learning methods.

Based on the patent application data of 2,337 Chinese companies in the biopharmaceutical manufacturing industry to construct the R&D team network, the study uses the K-Means method to explore the configuration types of R&D teams with the principle of greatest intergroup differences. Further, a decision tree model (DT) is utilized to excavate the conditional combined relationships between diverse team network configuration factors, knowledge diversity and breakthrough innovation. The network driving mechanism of corporate breakthrough innovation is analyzed from the perspective of team configurations.

It has been discerned that in the biopharmaceutical manufacturing industry, there exist three main types of enterprise R&D team configurations: tight collaboration, knowledge expansion and scale orientation, which reflect the three resource investment preferences of enterprises in technological innovation, network relationships, knowledge resources and human capital. The results highlight both the crowding-out effects and complementary effects between knowledge diversity and team network characteristics in tight collaborative teams. Low knowledge diversity and high team structure holes (SHs) are found to be the optimal team configuration conditions for breakthrough innovation in knowledge-expanding and scale-oriented teams.

Previous studies have mainly focused on the relationship between the external collaboration network and corporate innovation. Moreover, traditional regression methods mainly describe the linear net effects between variables, neglecting that technological breakthroughs are a comprehensive concept that requires the combined action of multiple factors. To address the gap, this article proposes a combination effect framework between R&D teams and enterprise breakthrough innovation, further improving social network theory and expanding the applicability of data mining methods in the field of innovation management.