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The purpose of this study is to propose a framework for the convergence of maturity model and education and evaluation in accounting.

The present research was conducted in two phases. In the first phase, to determine the indicators of convergence of the maturity model and education and evaluation in accounting, a Meta-Synthesis method was used. The conceptual model includes two dimensions of “Teaching and learning processes” and “Evaluation methods"; five levels of initial, repeatable, defined, managed and optimized; and a total number of 35 indicators. In the second phase, a questionnaire was developed, and academics as accounting faculty members in Iranian public universities were employed to fill out the questionnaire electronically and present a final framework. Having received the questionnaires, 66 questionnaires were analyzed statistically.

The results showed that the two dimensions of “Teaching and learning processes” and “Evaluation methods” considering initial, repeatable, defined, managed and optimized levels include 35 indicators, which form a framework for the convergence of maturity model and education and evaluation in accounting. The results show that both dimensions have positive and significant regression path coefficients in the convergence model. Moreover, the dimension of teaching and learning processes has the highest regression path coefficient indicating a greater impact on the convergence model. Besides, all five levels have positive and significant regression path coefficients with dimensions. Finally, in this study, all indicators were prioritized according to five levels.

Due to the success of maturity models and the urgent developments that require transformative improvements in accounting education, maturity models can respond to the challenges associated with education and learning in accounting. Thus, conceiving an image of the convergence of maturity model, education and evaluation in accounting seems imperative which has been scarcely investigated previously.

Recognizing novel entrepreneurial opportunities arising from a crisis is of paramount importance for firms. Hence, understanding the pivotal factors that facilitate firms in this endeavor holds significant value. This study delves into such factors within a representative empirical context impacted by a crisis, drawing insights from existing literature on opportunity recognition during such tumultuous periods.

The authors conducted a qualitative inspection of 14 Italian firms during the COVID-19 pandemic crisis. The authors collected a rich body of multi-source qualitative data, including 34 interviews (with senior managers and entrepreneurs) and secondary data (press releases, videos, web interviews, newspapers, reports and academic articles) in two phases (March–August 2020 and September–December 2020).

The results suggest the existence of a process model of opportunity recognition during crises based on five entrepreneurial influencing factors (entrepreneurial knowledge, entrepreneurial alertness, entrepreneurial proclivity, entrepreneurial personality and entrepreneurial purpose).

Various scholars have highlighted that, in times of crises, it is not easy and indeed very challenging for entrepreneurs to identify novel entrepreneurial opportunities. However, recent research has shown that crises can also positively impact entrepreneurs and their capacity to identify new entrepreneurial opportunities. Given these findings, not much research has analyzed the process by which entrepreneurs identify novel entrepreneurial opportunities during crises. This study shows that some entrepreneurial influencing factors are very important to identify new entrepreneurial opportunities during crises.

This study aims to investigate how employee perspectives on the role of business, specifically capitalist beliefs, affect the corporate social responsibility (CSR)–reputation–employee behavior relationship.

A conceptual model was developed, and to test the model empirically, survey data were collected over two phases from 192 working professionals. Data were analyzed in SAS using Hayes’s PROCESS approach.

Results of this study reveal that the positive employee outcomes (i.e. affective commitment and reduced turnover intentions), resulting from CSR, through perceived employer reputation (i.e. an employee’s perception of how others view their firm), are diminished when employees have strong capitalist beliefs.

Building on the signaling and person–organization fit literatures, this study highlights the theoretical and managerial importance of recognizing employees’ ideological differences as well as the value of considering employee perceptions of reputation. Although many stakeholders value social responsibility, not all do, and a firm’s intended outcomes will vary depending on employees’ beliefs.

This study demonstrates that CSR not only affects institutional-level corporate reputation, as previously studied, but also affects employees’ behaviors through “perceived employer reputation”, or employee beliefs about how other stakeholders perceive the firm. Moreover, this study highlights the importance of understanding employee differences, including ideological differences, prior to engaging in certain types of CSR.

The relationship between industrial policy and exploratory innovation is imperfect.

The authors use Chinese high-tech enterprise identification policy (HTEP) as a natural experimental group to test policy impacts, spillover effects and mechanisms of action.

First, HTEP promotes exploratory innovation. In addition, HTEP has a greater impact on non-exploratory innovation. Second, HTEP has spillover effects in two phases: HTEP (2008) and the 2016 policy reform. HTEP affects exploratory innovation in nearby non-high-tech firms, and the policy effect decreases monotonically with increasing distance from the treatment group. Third, HTEP affects innovation capacity through financing constraints, technical personnel flow and knowledge flow, which explains not only policy effects but also spillover effects. Fourth, the analysis of policy heterogeneity shows that the 2016 policy reforms reinforce the positive effect of HTEP (2008). By deducting the effects of other policies, the HTEP effect is found to be less volatile. In terms of the continuity of policy identification, continuous uninterrupted identification has a crucial impact on the improvement of firms’ innovation capacity compared to repeated certification and certification expiration. Finally, HTEP has a crowding-out effect in state-owned enterprises and large firms’ innovation.

This paper contributes to the existing literature in several ways. First, the authors enrich the literature on industrial policy through exploratory innovation research. While previous studies have focused on R&D investment and patents (Dai and Wang, 2019), exploratory innovation helps firms break away from the inherent knowledge mindset and achieve sustainable innovation. Second, few studies have explored the characteristics of industrial policies. In this paper, the authors subdivide the sample into repeated certification, continuous certification and certification expiration according to high-tech enterprise identification. In addition, the authors compare the differences in policy implementation effects between the 2016 policy reform and the 2008 policy to provide new directions for business managers and policy makers. Third, innovation factors guided by industrial policies may cluster in specific regions, which in turn manifest externalities. This is when the policy spillover effect is worth considering. This paper fills a gap in the industrial policy literature by examining the spillover effects. Finally, this paper also explores the mechanisms of policy effects from three perspectives: financing constraints, technician mobility and knowledge mobility, which can affect not only the innovation of beneficiary firms directly but also indirectly the innovation of neighboring non-beneficiary firms.

The main objective of this paper is to analyse the relationship between innovation and traditional concepts to explain the phenomenon of traditional food with innovation from a market and consumer behaviour perspective in the Mexican context.

The research is carried out in two phases: (1) analysis of the offer in distribution and (2) consumer research. First, a mixed observation technique in the offer of traditional foods with innovation was carried out. The data were recollected from 24 companies' websites and was complemented with information from main distribution chains of the city of Hermosillo (Mexico). Second, a survey was carried out with 310 Mexican consumers. The data obtained were analysed using bi-variable and multivariable techniques.

The findings from the websites showed that there are 19 traditional products with innovation that are marketed through this medium, while 39 traditional products with innovation are offered in distribution chains. Of all foods, 61% showed innovations in ingredients and materials. Also, the consumer evaluations identified three segments: the consumers orientated towards innovations, convenience and health (42.2%), those orientated towards sensory innovations (39%), and those more inclined towards innovations in marketing and availability (18.7%).

The research considers a partial perspective of the agri-food chain and not an integral vision, it is limited to a specific area and to certain traditional foods.

The symbiosis between innovation and tradition is identified from the perspective of supply and demand. The trend that exists in the market regarding the types of innovations and the gaps that exist regarding environmental elements are recognized.

The data obtained in the research generate information for business decision-making and entrepreneurship; in addition indicates new dietary and consumption patterns. It also provides knowledge about innovation and tradition, and highlights the relevance of traditional food.

This study tries to fill a gap in the literature by focusing on the market and consumer behaviour perspective for traditional food with innovation.

This conceptual paper aims to explore government regulatory responses of social networking platforms (SNP) and tourism destination evangelism. This research draws on a two-phase data source review of government legislations that guarantee social media users and empirical papers related to social media platforms. The results revealed that Ghana has adopted specific legislations that manage and control SNP. To the best of the author’s knowledge, this study is the first of its kind that synthesized government legislation and empirical papers on social networking platforms in evangelising destinations which have been missing in extant literature.

This study explores how problem-based learning (PBL) programs can address Sustainable Development Goals (SDGs) via the higher education (HE) curriculum, teaching materials and relevant assessments, supporting learning at scale for HE institutions.

Employing SDGs and their indicators as the coding framework, our two-phase study evaluates the curriculum and teaching materials of seven PBL programs at a leading higher education institution (HEI). The first phase involved a content analysis to assess the degree of sustainability integration in 156 relevant courses. The second phase applied a semi-automated mapping protocol to analyze learning and teaching materials in 120 relevant courses.

The school aligns with 17 SDGs (100%), covering 94 indicators (55.62%). On average, each program within the school addresses over ten of these goals and incorporates more than 24 associated indicators. However, the study reveals an imbalance in the incorporation of SDGs, with some goals not yet deeply and comprehensively embedded in the curriculum. While there is a substantial focus on sustainability theories, the practical implications of SDGs in emerging countries, particularly through case studies and assessments, require significant enhancement.

Mapping SDGs allows HEIs to identify strengths and gaps in SDG integration, thereby improving the PBL approach to enhance student work readiness in sustainability-focused careers.

Through the lens of transformative learning theory, this study provides evidence of SDG integration into PBL curricula. It highlights a mapping methodology that enables HEIs to evaluate their sustainability readiness in curriculum, teaching materials and relevant assessments.

As the competition to retain current and attract new mobile payment app users intensifies, meeting users’ needs has become fundamental for mobile payment app service providers to stay competitive. This study aims to investigate the relationship between users’ needs, users’ attitude towards mobile payment apps and users’ continuance intention to use mobile payment apps.

Following an exploratory sequential mixed methods research design, this study first conducted three focus groups in the qualitative phase to investigate issues or concerns faced by current users of mobile payment apps. The study then conducted an online questionnaire survey in the quantitative phase to collect responses from users of mobile payment apps. Partial least squares structural equation modelling was used to analyse 110 valid responses.

Findings show that usefulness (modelled as a second-order reflective construct consisting of three first-order reflective constructs, i.e. ease of use, acceptability and responsiveness), traceability and security had a statistically significant relationship with attitude towards mobile payment apps (which in turn had a statistically significant relationship with continuance intention to use mobile payment apps). It was also found that attitude towards mobile payment mediated the relationships between usefulness, traceability and security; and continuance intention to use mobile payment apps.

The findings of this study can help mobile payment app service providers and developers design apps that offer the functions and features that their users need.

Although some recent studies have investigated the adoption of mobile payments in the Malaysian context, few of these studies examined current users’ continuance intention to use mobile payment apps.

Although there is a growing body of literature on how celebrity involvement impacts the effectiveness of destination marketing, the underlying mechanisms of that relationship are still underexplored. Based on the affect transfer and meaning transfer theories, this study aims to examine the impact of celebrity attachment on customer delight toward K-culture and K-culture attachment, affective and cognitive images of Korea, and the intention to visit Korea.

Online survey data were collected from 2,614 US residents, representing various demographic characteristics. For the data analysis, the partial least squares-structural equation modeling was conducted to evaluate the structural model and test the hypotheses.

The results showed that celebrity attachment is positively related to customer delight toward K-culture and K-culture attachment, which, in turn, positively influences affective and cognitive images of Korea. Additionally, K-culture attachment positively influences cognitive and affective images of Korea, which are positively related to the intention to visit Korea.

By using the affect transfer theory and meaning transfer theory, this study provides valuable insights into how consumer’s attachment to celebrities has spillover effects on the decision-making process. This study also adds a new concept, customer delight connected to cultural experience, in the context of destination marketing.

By understanding the importance and influence of people’s intimacy with media characters, practitioners can apply parasocial relationship theory, affect transfer theory and meaning transfer theory to their marketing strategies.

As one of the few empirical studies that examines the impact of celebrity attachment on consumers’ perceptions and behaviors, this study can make significant contributions to the destination marketing literature.

Nature’s evolution has shaped intelligent behaviors in creatures like insects and birds, inspiring the field of Swarm Intelligence. Researchers have developed bio-inspired algorithms to address complex optimization problems efficiently. These algorithms strike a balance between computational efficiency and solution optimality, attracting significant attention across domains.

Bio-inspired optimization techniques for feature engineering and its applications are systematically reviewed with chief objective of assessing statistical influence and significance of “Bio-inspired optimization”-based computational models by referring to vast research literature published between year 2015 and 2022.

The Scopus and Web of Science databases were explored for review with focus on parameters such as country-wise publications, keyword occurrences and citations per year. Springer and IEEE emerge as the most creative publishers, with indicative prominent and superior journals, namely, PLoS ONE, Neural Computing and Applications, Lecture Notes in Computer Science and IEEE Transactions. The “National Natural Science Foundation” of China and the “Ministry of Electronics and Information Technology” of India lead in funding projects in this area. China, India and Germany stand out as leaders in publications related to bio-inspired algorithms for feature engineering research.

The review findings integrate various bio-inspired algorithm selection techniques over a diverse spectrum of optimization techniques. Anti colony optimization contributes to decentralized and cooperative search strategies, bee colony optimization (BCO) improves collaborative decision-making, particle swarm optimization leads to exploration-exploitation balance and bio-inspired algorithms offer a range of nature-inspired heuristics.