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In the field of digital entrepreneurship, achieving high growth in digital start-ups is crucial. This paper aims to explore how causal conditions at the individual, organizational and environmental levels interact in the growth process of digital start-ups. Furthermore, it uses a configurational approach to conduct a holistic analysis of the cross-level interaction mechanisms that enable digital start-ups to achieve high growth.

Based on a holistic perspective, the data collection included 57 representative cases of digital start-ups in China in the past decade (2014–2023). A fuzzy set qualitative comparative analysis was conducted to explore the cross-level interaction mechanism of the three-dimensional causal conditions of the environment, organization and individual entrepreneurs on high growth among digital start-ups.

This study found three models for digital start-ups to achieve high growth. These models − the resource network orchestration model, the innovation resource development model and the entrepreneurial spirit coherence model, respectively, reflect the multiple paths of high growth achieved by various digital start-ups based on their entrepreneurial environment, organizational capability and the personality of the founder. This reflects that digital start-ups face different conditions and entrepreneurial situations, with differing cross-level interaction mechanisms for achieving high growth.

First, digital start-ups should focus on strengthening their digital resource integration capabilities to lay the foundation for their subsequent high-growth path selection. Second, entrepreneurs need to adopt a holistic perspective to change or strengthen the causal conditions required to achieve high growth. Third, emphasis should be placed on the coherence between the entrepreneur’s need for achievement and the internal entrepreneurial culture.

First, this study contributes to the literature on high growth among digital start-ups by introducing a cross-level interaction mechanism comprising environmental, organizational and entrepreneurial causal conditions. Second, it reveals that individual factors at the environmental, organizational and entrepreneurial levels are not necessary conditions for high entrepreneurial growth and that digital resource integration capabilities play a more universal role in achieving high digital start-up growth. Finally, the study provides a cross-level holistic explanation of how digital start-ups can achieve high growth and reveals various configuration models conducive to high growth, thus offering practical insights for businesses.

Gamification has been widely applied in mobile fitness apps to motivate users to exercise continuously. Based on the affordances–psychological outcomes–behavioral outcomes framework, this study explores the roles of three specific gamification affordances (competition, visibility of achievement and interactivity) in self-health management (continuous use behavior and health behavior) from the perspectives of achievement satisfaction and gamification exhaustion.

We test the research model using a structural equation model (SEM) with 505 self-reported data points. Furthermore, we apply fuzzy-set qualitative comparative analysis (fsQCA) to explore configurations of gamification affordances associated with self-health management behavior, reinforcing the SEM results.

Results indicate that competition, visibility of achievement and interactivity can enhance achievement satisfaction, which further boosts self-health management behavior. However, competition and interactivity can also cause gamification exhaustion, which undermines self-health management behavior to some extent. Overall, the positive impacts of the three affordances outweigh the negative impacts.

This study provides new insights for relevant practitioners on designing gamification affordances, aiding the sustainable development of mobile fitness apps and their long-term effects on self-health management. Visibility of achievement should be emphasized, and competition and interactivity should be thoughtfully designed to minimize their negative effects.

This study extends the affordances–psychological outcomes–behavioral outcomes framework and the literature on gamification and health management by applying both SEM and fsQCA methodologies to examine the relationship between specific gamification affordances and self-health management behavior.

This study explores whether the peer effects of internationalization exist within the subdivision industry of enterprises in the engineering field and assesses the imitation paths for the peer engineering enterprises within the industry when implementing internationalization strategies under the peer effects.

This study collected secondary and objective data on 38 Chinese engineering enterprises from the Engineering News-Record's list of the top 250 international contractors between 2013 and 2021. It employed a regression analysis to test the research hypotheses.

The findings reveal that in the process of internationalization: (1) peer effects exist within the subdivision industry of internationalization of engineering enterprises; (2) engineering enterprises within the same industry and region imitate each other; (3) non-state-owned engineering enterprises imitate state-owned engineering enterprises within the same industry; and (4) in the industry follower–leader imitation process, industry followers imitate leaders according to enterprise size and return on assets.

The results contribute to a better understanding of how peer effects influence engineering enterprises' internationalization process. This study also proposes imitation paths based on the law of imitation to provide recommendations for engineering enterprises' better development in the international market.

In a reflection of individuals’ interest in maintaining a healthy lifestyle, nutraceutical restaurants, which provide health benefits, have emerged on the market. However, little is known about the underlying factors and mechanisms of the consumption of nutraceutical foods. Therefore, grounded in an extended cognitive–affective–conative model, this study examines the role of dining motivations and restaurant attributes in explaining an integrated model that focuses on customers’ loyalty formation process.

Data were collected from 893 Chinese customers who had recently dined at traditional Chinese medicine restaurants. Using partial least squares structural equation modeling, this study examined the structural relationships among dining motivations, restaurant attributes, customers’ perceived benefits, overall satisfaction, place attachment and revisit intentions.

The results of a confirmatory factor analysis revealed that two main motivations (i.e. health and traditional culture) and five restaurant attributes (i.e. food, service staff food recommendation, service staff service quality, furniture and tableware and atmosphere) are stimuli that influence customers’ perceived benefits. This study also revealed that four types of perceived benefits (functional, emotional, social and epistemic) significantly affect overall satisfaction and place attachment, which determine revisit intentions.

The findings of this study help identify not only important dining motivations and restaurant attributes but also their roles in loyalty formation with respect to traditional Chinese medicine restaurants. Thus, the results contribute to an improved understanding of how to satisfy customers’ dining motivations and efficiently manage restaurant attributes to strengthen customer loyalty.

This study is among the first to simultaneously examine the effects of customer motivation and restaurant attributes and to explain how they affect customer loyalty behaviors at traditional Chinese medicine restaurants.

This paper aims to explore the underlying mechanisms and boundary conditions through which equipment manufacturing enterprises can capture market value from digital transformation, with a specific focus on the roles of knowledge search and knowledge recombination.

This study uses a double fixed-effects model to test the hypotheses, using a unique data set of “firm-year” observations from 739 publicly listed equipment manufacturing companies in China, spanning the period from 2018 to 2022.

Digital transformation drives market value creation in equipment manufacturing enterprises through both breakthrough knowledge recombination (BKR) and progressive knowledge recombination (PKR). In addition, the analysis of marginal conditions reveals that diversified knowledge search serves as a substitute for digital transformation in promoting BKR, while also positively moderating the relationship between digital transformation and PKR.

Grounded in the knowledge-based view theoretical framework, this study introduces the novel concepts of BKR and PKR and systematically examines how digital transformation impacts market value in equipment manufacturing enterprises.

There is a clear gap in the literature regarding the factors that determine social conductivity (extent of interactions) in project relationships. This study aims to use social capital theory to answer the research question – What factors determine social conductivity in project relationships?

In the study, the authors use fuzzy synthetic evaluation based on the findings from a survey of 203 project practitioners to quantify the impacts of three principal components of factors determining social conductivity in project relationships.

The study findings reveal the structural, relational and cognitive dimensions of project social capital are all significant (impact levels exceeding 3.50) for determining social conductivity in project relationships. However, the study’s main finding reveals – issues relating to the cognitive dimension of project social capital are the most critical factors determining social conductivity in project relationships (a criticality index of 4.326).

This study provides evidence of varieties of ways social capital can boost the conductivity of project relationships.

The key contributions of this study are linked to the manner in which project social capital determines social conductivity in project relationships. The findings add to previous research by extending the dimensions of the factors that increase social conductivity from relational project social capital to include two new dimensions (the cognitive and structural dimensions of project social capital).

This study aims to investigate the relationship between corporate governance characteristics and the financial performance of both Islamic and conventional banks in the context of an emerging market, i.e. Malaysia.

This study includes 300 bank-year observations from Islamic and conventional banks over the period 2010–2021. The dynamic panel model (generalized method of moments [GMM]) was considered the primary estimation model that solves simultaneity, endogeneity and omitted variable problems as most governance variables are endogenous by nature. Hence, static models are considered biased after conducting the DWH test of endogeneity, and considering dynamic panel GMM is valid proven by Sargan and Hensen and first-order (ARI) and second-order (ARII) tests.

Based on the regression results, the authors discovered that board size, female participation in the board and director remuneration have a significant positive impact on bank performance, whereas board meetings have a significant negative impact. Furthermore, the board governance structure of commercial banks is found to be more passive than that of Islamic banks.

The study’s findings added a new dimension to governance research, which could be a valuable source of knowledge for policymakers, investors and regulators looking to improve existing governance mechanisms for better performance of conventional and Islamic banks.

The goal of this study is to add to the existing literature by focusing on the impact of female board participation and other board governance mechanisms in both conventional and Islamic banks on bank performance.

The purpose of the study is to investigate, synthesize and critically evaluate empirical research findings on the behavioral traits of fund managers from 1994 to 2024. The ultimate goal is to provide a unified body of literature on three broad topics: first, fund managers' demographic and professional characteristics, such as age, gender, level of education and years of industry experience; second, fund managers' social and political connections; and third, fund managers' behavioral biases that lead to irrational investment decisions.

The relevant papers from selected journals were discovered and manually validated using the Scopus database. From 317 retrieved documents, 57 relevant articles were chosen and analyzed after the forward and backward search of the existing articles.

This paper presents a categorized summary of behavioral factors that have gained a foothold in influencing the behavior of fund managers in fund management research, with several studies demonstrating their significance leading to improved prediction and model precision, as this review indicates. In addition, the study summarized the contributions of prior empirical studies within the aforementioned three major categories and illustrated their consequences.

The present study contributes to the understanding of the effects of behavioral finance theories on fund managers by providing meaningful explanations of their behavioral traits based on empirical evidence and existing trends and knowledge gaps, both of which can influence the future direction of research.

Service robots with advanced artificial intelligence (AI) can collect data on customer preferences, understand complex requests, improve services, and tailor marketing strategies. This study examined how perceived relatedness, perceived warmth, and customer–AI-assisted exchanges (CAIX) of service robots affect customer service competencies and brand love through service-robot intimacy.

A brand love model was developed based on the AI device using acceptance and an emotional perspective. Data were collected from customers who had dined in robot restaurants; 415 questionnaires were completed, and partial least squares analysis was adapted to the proposed model.

The results demonstrate that the perceived relatedness, perceived warmth and CAIX of service robots affect the intimacy of robot restaurants. Customers who feel friendly and satisfied with a restaurant’s service robot will recommend it to their friends.

This study draws on theory and existing literature to identify principal factors in robot restaurant service capabilities. Future research can include service robot data analysis capabilities and adoption process factors as the direction of customer relationship management research while also exploring the influence of AI computing on restaurant supply chains. Likewise, the agility of service robots in the stages of innovation can be discussed in future research based on different theories, which will bridge unique insights.

The findings of this study emphasize the relationship between service robots and restaurant brand love and propose specific practice areas for restaurants.

This study expands the main issue of current brand love research from traditional restaurant operations to the novel field of humanoid service robot restaurants. It enriches our understanding of how consumers’ emotional fondness for a brand affects their behavioural intentions.

A tightly coupled global navigation satellite system (GNSS)-Vision-IMU-wheel odometer (GVIWO) system is proposed, which can realize robust positioning in extreme environments. The purpose of this study is to achieve adaptive initialization in complex environments, sensor anomaly detection and processing, and adaptive robust localization in extreme environments.

Adaptive initialization includes traditional dynamic and static initialization and extreme condition initialization. To deal with the unstable visual features in the state of excited motion, a method of wheel odometer assisted initialization is designed. According to the abnormal condition of the sensor, the anomaly detection and attenuation mechanism are designed to realize the accurate positioning of the sensor under abnormal condition.

Tight coupling optimization of GNSS signals, RGB+Depth Map cameras, inertial measurement units and wheel odometers ensures accurate positioning in both indoor and outdoor environments. Through open data sets and field validation experiments, the proposed tightly coupled system has strong adaptability, especially in extreme environments.

A new framework is proposed by integrating GNSS, visual, inertial measurement unit (IMU) and wheel odometer sensors to form an efficient positioning solution. An adaptive initialization method is proposed to enhance the robustness and real-time performance of the positioning system in complex and dynamic environments. A mechanism for detecting and attenuating sensor anomalies is designed, enabling quasideterministic positioning under sensor anomalies.