Search results

To construct a scientific and reasonable indicator system, it is necessary to design a set of standardized indicator primary selection and optimization inspection process. The purpose of this paper is to provide theoretical guidance and reference standards for the indicator system design process, laying a solid foundation for the application of the indicator system, by systematically exploring the expert evaluation method to optimize the index system to enhance its credibility and reliability, to improve its resolution and accuracy and reduce its objectivity and randomness.

The paper is based on system theory and statistics, and it designs the main line of “relevant theoretical analysis – identification of indicators – expert assignment and quality inspection” to achieve the design and optimization of the indicator system. First, the theoretical basis analysis, relevant factor analysis and physical process description are used to clarify the comprehensive evaluation problem and the correlation mechanism. Second, the system structure analysis, hierarchical decomposition and indicator set identification are used to complete the initial establishment of the indicator system. Third, based on expert assignment method, such as Delphi assignments, statistical analysis, t-test and non-parametric test are used to complete the expert assignment quality diagnosis of a single index, the reliability and validity test is used to perform single-index assignment correction and consistency test is used for KENDALL coordination coefficient and F-test multi-indicator expert assignment quality diagnosis.

Compared with the traditional index system construction method, the optimization process used in the study standardizes the process of index establishment, reduces subjectivity and randomness, and enhances objectivity and scientificity.

The innovation point and value of the paper are embodied in three aspects. First, the system design process of the combined indicator system, the multi-dimensional index screening and system optimization are carried out to ensure that the index system is scientific, reasonable and comprehensive. Second, the experts’ background is comprehensively evaluated. The objectivity and reliability of experts’ assignment are analyzed and improved on the basis of traditional methods. Third, aim at the quality of expert assignment, conduct t-test, non-parametric test of single index, and multi-optimal test of coordination and importance of multiple indicators, enhance experts the practicality of assignment and ensures the quality of expert assignment.

This paper aims to introduce a crowd-based method for theorizing. The purpose is not to achieve a scientific theory. On the contrary, the purpose is to achieve a model that may challenge current scientific theories or lead research in new phenomena.

This paper describes a case study of theorizing by using a crowd-based method. The first section of the paper introduces what do the authors know about crowdsourcing, crowd science and the aggregation of non-expert views. The second section details the case study. The third section analyses the aggregation. Finally, the fourth section elaborates the conclusions, limitations and future research.

This document answers to what extent the crowd-based method produces similar results to theories tested and published by experts.

From a theoretical perspective, this study provides evidence to support the research agenda associated with crowd science. The main limitation of this study is that the crowded research models and the expert research models are compared in terms of the graph. Nevertheless, some academics may argue that theory building is about an academic heritage.

This paper exemplifies how to obtain an expert-level research model by aggregating the views of non-experts.

This study is particularly important for institutions with limited access to costly databases, labs and researchers.

Previous research suggested that a collective of individuals may help to conduct all the stages of a research endeavour. Nevertheless, a formal method for theorizing based on the aggregation of non-expert views does not exist. This paper provides the method and evidence of its practical implications.

This study aims to explore how small and medium-sized accounting practices (SMPs) make sense of and position themselves against the changing demand for services. It is argued that changing demand for services from pure compliance to advisory acts as a trigger for sensemaking among SMP owners.

A qualitative multiple case study research approach is adopted, including semistructured interviews with key informants from seven Norwegian SMPs as well as document analysis.

The findings suggest that there is heterogeneity in the small practitioner segment of the accounting profession in making sense of changing demand for the nature of services. Three different situations emerged due to sensemaking, thus, the three distinct positions. Metaphors, namely, chameleons, turtles and bulls, are used to represent the positioning of SMPs. The sensemaking of actors as an adaptation led them to act as chameleons while distancing and resistance resulted in their positioning as turtles, and bulls, respectively.

Despite the richness of data indicating a clear variation in interpretation among actors, the study is case based, with a limited number of SMPs, and caution should be exercised when generalising its conclusions.

The centrality of people as a driving force for positioning among SMPs and diversity among SMPs in value creation provide insights for both SMPs and their customers.

This study highlights the meaning and patterns of value creation and the positioning of accounting firms according to their sensemaking within an under-studied segment of the accounting profession.

This paper aims to present the basic assumptions for creation of social Fröhlich condensate and attract attention of other researchers (both from physics and socio-political science) to the problem of modeling of stability and order preservation in highly energetic society coupled with social energy bath of high temperature.

The model of social Fröhlich condensation and its analysis are based on the mathematical formalism of quantum thermodynamics and field theory (applied outside of physics).

The presented quantum-like model provides the consistent operational model of such complex socio-political phenomenon as Fröhlich condensation.

The model of social Fröhlich condensation is heavily based on theory of open quantum systems. Its consistent elaboration needs additional efforts.

Evidence of such phenomenon as social Fröhlich condensation is demonstrated by stability of modern informationally open societies.

Approaching the state of Fröhlich condensation is the powerful source of social stability. Understanding its informational structure and origin may help to stabilize the modern society.

Application of the quantum-like model of Fröhlich condensation in social and political sciences is really the novel and original approach to mathematical modeling of social stability in society exposed to powerful information radiation from mass-media and Internet-based sources.

The purpose of this paper is to identify under what circumstances advisor gender and advice justification influence advice taking by managers.

The authors designed a quasirational managerial decision experiment with both analytic and intuitive cues. The design was a 2 × 2 between-subjects factorial, in which gender (male/female) and advice justification (intuitive/analytic) were crossed. The experiment involved two independent samples, taken from Amazon Mechanical Turk workers and Brazilian professionals.

Results suggest that, in general, analytic justification is more valued than intuitive justification. The findings also infer that depending on the advisees’ sample and providing that advice justification is analytic, quasirational scenarios seem to favor male advisors (MTurk sample) or both male and female advisors with “male values” (professional sample), as analysis is traditionally considered a “male value.”

Analytic justification will likely lead to more advice utilization in quasirational managerial situations, as it may act as a safeguard for the accuracy of the offered advice.

The results might signal an ongoing, but slow, process leading to the mitigation of gender stereotypes, considering that the male gender stereotype was active in the MTurk sample, but not in the professional one.

This study contributes to the advice-taking research field by showing the interplay between advisor gender and advice justification in a quasirational managerial decision setting with both analytic and intuitive cues. In advice-taking literature, observations are usually collected from students. However, as this study focused on managerial decisions, the authors collected independent samples from MTurk workers and Brazilian professionals.

Sustainable development requires multiple stakeholders to work and learn across practices, in other words, it requires boundary crossing competence. To prepare students for their future sustainability professions, higher education should facilitate the development of boundary crossing competence in its curricula. This study aims to confirm whether boundary crossing learning can be stimulated by workshop-based support in multi-stakeholder projects.

This quasi-experimental intervention study (N = 122) investigates the effect of a series of supporting workshops on students’ boundary crossing learning in multi-stakeholder projects. The workshops allowed students to adopt four learning mechanisms (identification, coordination, reflection and transformation) theorised to stimulate learning across boundaries between practices. Students followed zero, one, or two workshops. By analysing the student learning reports, the study examines the effect of the workshop intervention on students’ self-efficacy for stakeholder collaboration, the number of reported student-stakeholder collaborative activities and the reported boundary crossing learning mechanisms.

The results show that a series of two workshops increase the number of reported collaborative activities and activates the students’ boundary crossing learning in terms of reflection and transformation.

These findings support the evidence-based design of multi-stakeholder learning environments for sustainable development and contribute to the body of knowledge regarding learning across practices.

Boundary crossing competence receives increasing attention as an asset for sustainable development. The added value of this study lies in its confirmation that the boundary crossing theory can be translated into directed educational support that can stimulate students’ boundary crossing learning.

Focused feedback, such as mentoring and coaching, is a crucial ingredient for generating the intellectual capital needed for successful venture creation and has become a structural resource offered to entrepreneurs in business incubator/accelerator programs. Yet so far, literature has remained silent on the way that entrepreneurs differ in their engagement with focused feedback in such programs. This study poses the question of how focused feedback engagement shapes cognitive development during value creation (i.e. business opportunity development), aimed at the construction of a taxonomy of such feedback engagement.

Focusing on cognitive learning outcomes, we carried out a qualitative analysis using NVivo to perform content analysis on the logbooks of 70 entrepreneurs engaged in business opportunity development in a highly regarded accelerator program.

Results show that engagement with focused feedback and its effects relate to the state of tangibility of the entrepreneur’s value offer and to the amount of prior entrepreneurial experience. We also develop a promising taxonomy to classify entrepreneurs on their learning needs and outcomes (e.g. procedural versus declarative knowledge).

This study brings together types of human learning (types of knowledge acquired) with types of focused feedback. This connection has been speculated to exist in entrepreneurial settings; this study provides strong initial evidence that argues for more explicit consideration in practice. Adding the intellectual capital perspective further enabled this study to better address implications for practice as well as motivate powerful new directions for research.

The importance of sustainable development has become increasingly significant in today’s fast-paced world. The 17 sustainable development goals (SDGs) aim to solve a range of environmental, economic and social challenges, which requires global collaboration among governments and private organisations. In light of this, social entrepreneurship has garnered significant attention as it combines the social purpose of non-profits with the market-driven approach of for-profits to address SDG goals. Yet the cognitive processes underpinning the career decisions of social entrepreneurs remain underexplored. This study aims to develop and validate a scale to measure social entrepreneurial career decisions based on the appraisal of perceived challenges.

The study followed the steps of tool development and was carried out in three phases: item analysis, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

The final 20-item scale focuses on the appraisal components in pre-entry social entrepreneurial career decision-making and has four factors, which are relevance, coping potential, knowledge and resources and normative significance.

The study contributes to the literature on entrepreneurial cognition, specifically focusing on social entrepreneurship. The scale could guide model testing and quantitative research in social entrepreneurial cognition. The four-dimensional structure identified in the study may also have implications for researchers interested in the antecedents and effects of social entrepreneurial decision-making.

Accurate measurement of cognitive appraisal is necessary to understand the perceived challenges and thought processes of potential social entrepreneurs. The scale could be used to examine the cognitive appraisal patterns among students. Social entrepreneurship educators and policymakers can use the scale to design and assess educational programs.

Distinct from existing studies, this scale offers a multidimensional approach that captures the stages of career decision-making, providing a robust tool to enhance our understanding of the decision-making dynamics in social entrepreneurship.

The purpose of this paper is to discuss how enterprises can effectively perceive and use the digital opportunities brought about by digital technologies and dynamic environments and how they can enhance their capabilities to realize digital transformation and adapt to the development of the digital economy era.

Based on the windows of opportunity theory and strategic cognition theory, this paper conducts an empirical analysis of the questionnaire data of 268 enterprises and discusses the influence of external windows of opportunity and internal windows of opportunity on the digital transformation of enterprises, as well as the action mechanism of strategic cognition and entrepreneurship.

The results show that both the external windows of opportunity and the internal windows of opportunity have significant positive effects on the digital transformation of enterprises. Strategic cognition plays a partial mediating role in the external windows of opportunity and the internal windows of opportunity influencing the enterprise digital transformation process. Entrepreneurship plays a positive regulatory role in the process of external windows of opportunity and internal windows of opportunity influencing strategic cognition.

This paper deepens the relationship between internal and external windows of opportunity and enterprise digital transformation and contributes a new theoretical cognition. This paper integrates the strategic cognition theory to clarify the complex process mechanism of digital transformation using external situational opportunities and internal capabilities. This paper introduces entrepreneurship into the path mechanism of digital transformation and expands the characteristics of the study of digital transformation antecedents to the individual level within the enterprise.

This paper explores if and how Artificial Intelligence can contribute to marketing strategy formulation.

Qualitative research based on exploratory in-depth interviews with industry experts currently working with artificial intelligence tools.

Key themes include: (1) Importance of AI in strategic marketing decision management; (2) Presence of AI in strategic decision management; (3) Role of AI in strategic decision management; (4) Importance of business culture for the use of AI; (5) Impact of AI on the business’ organizational model. A key consideration is a “creative-possibility perspective,” highlighting the future potential to use AI not only for rational but also for creative thinking purposes.

This work is focused only on strategy creation as a deliberate process. For this, AI can be used as an effective response to the external contingencies of high volumes of data and uncertain environmental conditions, as well as being an effective response to the external contingencies of limited managerial cognition. A key future consideration is a “creative-possibility perspective.”

A practical extension of the Gartner Analytics Ascendancy Model (Maoz, 2013).

This paper aims to contribute knowledge relating to the role of AI in marketing strategy formulation and explores the potential avenues for future use of AI in the strategic marketing process. This is explored through the lens of contingency theory, and additionally, findings are expressed using the Gartner analytics ascendancy model.