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Decision comprehensiveness is an important process in determining the outcomes of strategic decision-making. While recent research began to explore its individual level antecedents, a fundamental aspect of organizational life, heterogeneous goals, have not been investigated for their effects on comprehensiveness. In this study, our purpose is to study the impact of goal heterogeneity on decision comprehensiveness and explore behavioral integration as a potential mediator in this relationship.

To test our hypotheses, we utilize a survey-based study with a sample of teams undertaking a business simulation. Our longitudinal data collection process captures team data across the initial-, mid-, and the ending-stages of the simulation.

Our findings show that goal heterogeneity negatively impacts behavioral integration and decision comprehensiveness. Moreover, the negative impact of goal heterogeneity on decision comprehensiveness is mediated through behavioral integration.

Given that many strategic decisions are undertaken by groups of individuals, it is imperative to understand the factors that impact team-level decision-making processes. Extending the literature, we empirically show the negative effects of goal heterogeneity on decision comprehensiveness. While doing so, we also show that behavioral integration – a team trait that can endure over time, as opposed to a one-time state – can be crucial in dampening this negative effect. Our findings suggest researchers, and managers, to be cautious in assuming decision comprehensiveness may easily be achieved in any given team context.

Even after establishing their business successfully, many business owners get demotivated, and it leads to unwillingness to grow. This study aims to propose a comprehensive model that represents interrelationships among various personal factors affecting “unwillingness to grow.”

The personal factors for unwillingness to grow were identified by extant literature, and expert interviews were conducted to establish the contextual relationships among these factors. The interrelationships among the filtered variables have been done using interpretive structural modeling (ISM) and MICMAC analysis was done to determine the importance of each factor in influencing “unwillingness to grow.”

In total, 30 personal attributes were identified from previous literature, out of which 15 were selected for the final study. The result identifies 7 variables having a strong impact on “unwillingness to grow.” These attributes are “absence of strong network,” “lack of vision,” “lack of proactiveness,” “reluctance to involve external consultants,” “absence of/small founding team,” “lack of ambition” and “improper attitude.”

The research attempts to create a bricolage of all the important personal factors affecting “unwillingness to grow.” Previous researches have used few attributes, but with the help of ISM, a graphical modeling technique, it became possible to draw interrelationship between 15 attributes. Further, with the help of MICMAC, the importance of each attribute was determined.

Before the onset of the COVID-19 pandemic, most employees worked from their employers' offices, and new team members were integrated into their roles through standard onboarding procedures. However, in response to the pandemic, organizations quickly reestablished new remote onboarding strategies. As hybrid employment gains popularity, the onboarding process has been affected by the digital transformation (DT) phenomenon, and organizations must now implement remote strategies to onboard new employees.

In this context, by considering the major changes that happen in the field, the purpose of this article is to provide a literature review of the onboarding process (OP), using the context-interventions-mechanisms-outcomes framework.

The review identifies four mechanisms describing the complexity of the OP and the impact of DT: basic onboarding, advanced onboarding, integration of newcomers and remote onboarding.

The findings have implications for both HR professionals concerned with onboarding strategy, and researchers studying the OP.

The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption of certain intelligent technologies and pedagogical designs applied in this domain.

A scoping review was conducted using six inclusive and exclusive criteria agreed upon by the author team. The collected studies, which focused on the adoption of AI in entrepreneurship education, were analysed by the team with regards to various aspects including the definition of intelligent technology, research question, educational purpose, research method, sample size, research quality and publication. The results of this analysis were presented in tables and figures.

Educators introduced big data and algorithms of machine learning in entrepreneurship education. Big data analytics use multimodal data to improve the effectiveness of entrepreneurship education and spot entrepreneurial opportunities. Entrepreneurial analytics analysis entrepreneurial projects with low costs and high effectiveness. Machine learning releases educators’ burdens and improves the accuracy of the assessment. However, AI in entrepreneurship education needs more sophisticated pedagogical designs in diagnosis, prediction, intervention, prevention and recommendation, combined with specific entrepreneurial learning content and entrepreneurial procedure, obeying entrepreneurial pedagogy.

This study holds significant implications as it can shift the focus of entrepreneurs and educators towards the educational potential of artificial intelligence, prompting them to consider the ways in which it can be used effectively. By providing valuable insights, the study can stimulate further research and exploration, potentially opening up new avenues for the application of artificial intelligence in entrepreneurship education.

This conceptual, multi-voiced paper aims to collectively explore and theorize family entrepreneuring, which is a research stream dedicated to investigating the emergence and becoming of entrepreneurial phenomena in business families and family firms.

Because of the novelty of this research stream, the authors asked 20 scholars in entrepreneurship and family business to reflect on topics, methods and issues that should be addressed to move this field forward.

Authors highlight key challenges and point to new research directions for understanding family entrepreneuring in relation to issues such as agency, processualism and context.

This study offers a compilation of multiple perspectives and leverage recent developments in the fields of entrepreneurship and family business to advance research on family entrepreneuring.

This study aims to enrich the field of entrepreneurial marketing (EM) by examining decision-making processes in the unique context of start-up ventures. To do so, it extends research on the distinct EM dimensions to the behavioral context by revealing how causation and effectuation principles shape entrepreneurs’ actions.

The study investigates EM behavior through 12 semi-structured interviews with 10 start-up founders and two founder associates in Germany. Use of established frameworks of the EM dimensions and causation/effectuation principles paves the way for an in-depth analysis. This methodology uncovers a distinct pattern of decision-making behaviors characterizing various activities within start-ups.

The findings show that causal logic prevails in start-ups’ EM, and effectual reasoning serves a complementary role. On the dimensional level, the findings reveal a predominant goal-driven focus on customer intensity and value-creation processes. Predictive logic guides opportunity focus, proactiveness and risk management, with nonpredictive behaviors providing adaptability. The principle of affordable loss is also evident in risk management. Finally, start-ups exhibit a blend of causal and effectual logic in innovativeness and resource-leveraging.

To the best of the authors’ knowledge, this study is the first to illuminate the interplay of behavioral logics in start-up firms’ EM by exploring the nuanced principles underpinning the decision-making processes of entrepreneurs. In doing so, it advances understanding of the marketing–entrepreneurship interface and enriches decision-making literature.

The purpose of this study is to explore how past and future temporal focus of CEOs in the hospitality industry influence their intention to invest in metaverse technology and the underlying mechanism under boundary conditions of perceived competitive pressure.

This multi-informant study collected data over three waves from a sample of 235 CEOs and their subordinates in India’s hospitality industry. A PLS-SEM was applied to the study data. Further, the study also used phenomenological interviews to capture CEOs’ perspectives on the study’s conceptual model.

Findings suggest that the past temporal focus of CEOs decreases technology orientation, and future temporal focus increases the technology orientation of firms, consequently impacting the intention to invest in the metaverse. CEOs’ perceived competitive pressure moderates the mediating relationship, such that the negative impact of past temporal focus on technology orientation is decreased and that of future temporal focus on the CEO is increased.

By exploring the role of a CEO’s past and future temporal focus on influencing technology orientation and, hence, adoption of new technology, the study extends upper-echelon theory to the field of metaverse adoption in the hospitality industry and responds to scholars’ calls to explore the industry’s technology adoption from the lens of the upper echelon.

The study has significant implications for the success of the adoption of metaverse technology in the hospitality industry. Findings imply that the board members should encourage CEOs to have future temporal focus.

The study provides novel insights into the adoption of metaverse technology by the hospitality industry, where CEO attributes such as their temporal focus influence intention to invest in metaverse.

The present study aims to investigate the non-linear relationship between trade and income inequality to address goal 10 of sustainable development goals (SDGs) using the Kuznets Curve (KC) framework for major emerging countries during 1991–2020.

For this purpose, recent econometric techniques, such as Common Correlated Effect (CCE) and Dynamic Common Correlated Effect (DCCE) estimators have been employed to deal with the cross-section dependence (CD) that arises in panel data, while the robustness of the study is checked through Driscoll–Kraay standard errors method.

The empirical results of the study confirm the existence of inverted “U-shaped” relationship between trade and income inequality suggesting evidence for the trade-led KC in the panel of emerging countries. Along with the non-linear model, the threshold value is estimated to be between 3.5 and 4% of gross domestic product (GDP).

The authors' findings support that trade contributes significantly toward reducing income inequality and helps in achieving goal 10 of SDGs. Hence, trade policies appear to be more egalitarian. The results widen the scope for further research and provide insights for regulators and policymakers in modeling trade policies and changing the status quo trade policy framework accordingly.

The present study is a pioneering attempt to examine the non-linear relationship between trade and income inequality under the KC framework in light of the Agenda 2030 for sustainable development. The study also considers other explanatory factors that have an impact on income inequality. Furthermore, the study considers other explanatory factors that have an impact on income inequality, and the attempt to estimate the threshold value for the trade-led KC is novel and interesting.

The objective of this paper is to advance research concerning the factors affecting the intentions to start-up. In this vein, scholars are more and more interested in perceptual variables, i.e. subjective perceptions that may affect individuals’ intentions to start-up. These can have an internal locus of control (PVIs), if they depend on personal cognitive styles, or an external locus of control (PVEs), if they depend on how individuals perceive environmental stimuli. Usually, scholars investigate them at a micro-level of analysis, by focusing on individuals in a country. Instead, this paper adopts a macro-level analysis. Thus, the research question at the basis of this paper is: whether the impact of perceptual variables (with an internal or external locus of control) on the intentions to start-up varies across countries.

Stochastic frontier analyses – SFAs are carried out since they allow disentangling technical and random inefficiencies and comparing statistical results. SFAs are based on data retrieved from the Global Entrepreneurship Monitor – GEM website and refer to PIGS (Portugal, Italy, Greece, and Spain) and BRICs (Brazil, Russia, India, and China) countries where entrepreneurship is a vibrant phenomenon, but cultural and economic differences are manifest.

Concerning the drivers of entrepreneurship, achieved results reveal that some differences exist across PIGS and BRICs countries, but they cannot be generalized so easily.

This paper reveals its originality in reference to the classification of the variables, the macro-level of analysis, and the results that – at the same time – are in line with previous ones, but also offer new insights about perceptual variables in entrepreneurship and – at a wider extent – about the drivers of entrepreneurship.

Social value creation (SVC) is the primary emphasis for unifying the various issues in contemporary social entrepreneurship (SE) literature and practice since it highlights the fundamental problem of sustainability in SE business. Accordingly, SVC as an outcome of SE represents the primary drive of social entrepreneurs (SEs). However, SEs encounter multi-dimensional challenges as they work to build their SE businesses and create social value. In the current context of digitally transforming entrepreneurship scenario, this study investigates the role of SE compassion and digital learning orientation (DLO) for SVC ability of SEs.

The study utilized a quantitative survey approach for primary data collection from social entrepreneurs in Saudi Arabia. A total of 158 valid replies from social entrepreneurs were obtained for the study. Using SmartPLS (3.0), partial least square structural equation modeling was used to analyze the data.

The results validated a model of SVC in which the SE compassion and DLO positively impact the SVC ability in SEs. However, the impact of DLO in moderating the SE compassion - SVC relationship in SEs was not proven.

The study established the role of SE compassion in explaining the distinctive SVC ability in SEs. Meanwhile, given the expanding necessity for SEs to leverage digital technologies for SE missions, the study provides implications for nurturing positive outcomes in terms of SE compassion and DLO outcomes among SEs. This organized knowledge can help entrepreneurs, educators and policymakers better incorporate these concerns in SE education, and social enterprises and entrepreneurs’ developmental initiatives.

This work is pioneering in that it conceptualizes and tests a theoretical framework that links SE compassion, DLO, and SVC in SEs. Meanwhile, the study is the first to operationalize the DLO in entrepreneurs. The study thus generates fresh insights about SVC in SE amid the digitally transforming entrepreneurship scenario.