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Customers' co-design behavior is an important source of knowledge for product innovation. Firms can regulate the focus of information interaction with customers to set goals and motivate their co-design behavior. Drawing on regulatory fit theory and construal level theory, the authors build a research model to study whether the fit between the regulatory focus of firms' task invitations (promotion focus vs prevention focus) and their feedback focus (self-focused vs other-focused) can enhance co-design behavior by improving customers' experiences (perceived meaning, active discovery and perceived empowerment).

The authors conducted two online between-subjects experiments to validate the proposed research model.

The two online experiments reveal that customers' experiences are enhanced when the feedback focus is congruent with the regulatory focus of the firm's task invitations. Specifically, self-focused feedback has a stronger positive effect on customers' experiences in the prevention focus context. Other-focused feedback has a stronger positive effect on customers' experiences in the promotion focus context. Moreover, customers' experience significantly and positively affects co-design behavior (i.e. co-design effort and knowledge contribution).

This work provides theoretical and practical implications for firms to improve the effectiveness of information interaction with their customers and eventually ensure the sustainability of co-design.

With the growing concern of various sectors of society regarding environmental issues and the promotion of sustainable development, green technology innovation is generally considered to be conducive to the long-term development of enterprises. However, because of the existence of agency problems, managers may have shortsighted behaviors. Then how will managers' shortsighted behaviors affect enterprises' green technology innovation?

This paper uses machine learning-based text analysis methods to construct a manager myopia index based on the data from A-share listed companies on the Shanghai and Shenzhen Stock Exchanges from 2015 to 2020. We examine the impact of manager myopia on green technology innovation in companies.

Our study finds that manager myopia significantly inhibits green technology innovation in companies. However, when multiple large shareholders coexist and the proportion of institutional investors' holdings is high, it can alleviate the inhibitory effect of manager myopia on green innovation. Heterogeneity tests show that the impact of manager myopia on green technology innovation is relatively significant in non-state-owned and manufacturing companies, as well as in the electricity industry. Robustness tests demonstrate that our conclusions remain valid after using propensity score matching to eliminate endogeneity problems.

From the perspective of corporate governance, this paper incorporates managers' shortsightedness, multiple large shareholders and institutional investors' shareholding ratios into the same logical framework, analyzes their internal mechanisms, helps improve corporate governance, enhances green innovation capabilities and has strong implications for the implementation of national innovation-driven development strategies and the achievement of “carbon peak” and “carbon neutrality” targets.

The purpose of this study is to empirically examine the direct effect of extra-industry network (EIN) and organization–stakeholder relationships (OSR) on absorptive capacity (ACAP). In addition, this study explored indirect effects of EIN and OSR on performance through ACAP among small- and medium-sized enterprises (SMEs) in Oman by considering the moderating role of big data analytics (BDA) outsourcing.

This study utilized quantitative method through survey questionnaire. The hypotheses were tested with a sample size of 202 surveys completed by SME owners. Partial least squares-structural equation modeling (PLS-SEM) was administered to analyze data via the SmartPLS 4.0 software.

The analysis revealed that EIN and OSR had an indirect effect on performance through ACAP, while propensity to outsource BDA was found to have a positive moderating role between EIN and performance. Interestingly, propensity to outsource BDA was found to have a negative moderating influence on the relationship between ACAP and performance.

This research is beneficial for entrepreneurs who wish to learn about the specific intangible resources significant for venture growth, to devise effective strategies to expand their EIN and OSR and to consider the significance of the correlations established in this study through ACAP. The result also assists managers in a way that the propensity to outsource BDA strengthens the positive effect of EIN on performance and weakens the positive effect of ACAP on performance.

This research appears to be among the first empirical studies that attempt to provide insights into the importance of ACAP as the key mechanisms to transform the advantages of EIN and OSR to enhance performance by considering the moderating role of propensity to outsource BDA.

The purpose of the research is to analyze the factors that determine the intention of small- and medium-sized enterprises (SMEs) to adopt the Metaverse. For this purpose, the analysis of the effort expectancy and performance expectancy of the constructs in relation to business satisfaction is proposed.

The analysis was performed on a sample of 182 Spanish SMEs in the technology sector, using a PLS-SEM approach for development. For the confirmation of the model and its results, an analysis with PLSpredict was performed, obtaining a high predictive capacity of the model.

After the analysis of the model proposed in this research, it is recorded that the valuation of the effort to be made and the possible performance expected by the companies does not directly determine the intention to use immersive technology in their strategic behavior. Instead, the results obtained indicate that business satisfaction will involve obtaining information, reducing uncertainty and analyzing the competition necessary for approaching this new virtual environment.

The study represents one of the first approaches to the intention of business behavior in the development of performance strategies within Metaverse systems. So far, the literature has approached immersive systems from perspectives close to consumer behavior, but the study of strategic business behavior has been left aside due to the high degree of experimentalism of this field of study and its scientific approach. The present study aims to contribute to the knowledge of the factors involved in the intention to use the Metaverse by SMEs interested in this field.

This study's goal is to look at how visitors' experiences affect the indirect links between the destination's extrinsic motivations (DEMs) and tourists' intrinsic motives (TIMs), on the one hand, and the perceived destination image (PDI), on the other.

Using structural equation modeling, 613 tourists from different nationalities were used to test the five hypotheses.

The research results revealed that second-order destinations' extrinsic motivations directly impact TIM and PDI. It also showed that tourists' experiences as moderators reduce the direct effect of DEM on PDI for first-time visitors compared to repeat visitors. Moreover, it increases the direct effect of TIM on PDI for repeated visitors.

Destination managers can fix the problems that hurt their reputations and images by hiring police officers in tourist areas and cleaning tourist places. In the same way, destination managers and travel agencies should use AI tools to create social media marketing campaigns focusing on natural and historical monuments. Also, the marketing plans should stress the value for money (for example, lodging, food and attractions’ cost). Finally, destination marketers can make programs for repeat visitors, focusing on DEM and TIM.

This article tries to fill a gap in the research on PDI formation in emerging markets as a modern technique in destination marketing by using the push-intrinsic and pull-extrinsic theories. It also looks at how the tourists' experiences moderate the direct link between DEM, TIM and PDI. Lastly, this study examines how TIM affects a destination's image in emerging markets.

The purpose of this paper is to introduce an improved system identification method for small unmanned helicopters combining adaptive ant colony optimization algorithm and Levy’s method and to solve the problem of low model prediction accuracy caused by low-frequency domain curve fitting in the small unmanned helicopter frequency domain parameter identification method.

This method uses the Levy method to obtain the initial parameters of the fitting model, uses the global optimization characteristics of the adaptive ant colony algorithm and the advantages of avoiding the “premature” phenomenon to optimize the initial parameters and finally obtains a small unmanned helicopter through computational optimization Kinetic models under lateral channel and longitudinal channel.

The algorithm is verified by flight test data. The verification results show that the established dynamic model has high identification accuracy and can accurately reflect the dynamic characteristics of small unmanned helicopter flight.

This paper presents a novel and improved frequency domain identification method for small unmanned helicopters. Compared with the conventional method, this method improves the identification accuracy and reduces the identification error.

The study examines tourists' psychological and social risk and shared beliefs – devotion, concerns and entertainment – at a religious and cultural heritage destination. It also examines how shared beliefs impact tourists’ nostalgia. Further, it examines whether nostalgia affects choice deferral and revisit intentions. Finally, it investigates how moderation of place attachment strengthens the link between shared beliefs – devotion, concerns, entertainment and nostalgia.

The data were collected from 439 inbound tourists, with 272 completing online questionnaires and 167 participating in face-to-face survey. Data analysis was performed using Amos 24.0 and SPSS 25.0, employing structural equation modeling (SEM) and the PROCESS macro.

The findings suggest that perceived psychological and social risk negatively impacts tourists' shared beliefs – devotion, concerns and entertainment – which positively impacts nostalgia. Positive nostalgic association boosts revisit intention and hampers choice deferral. The data also show how strong place attachment strengthens the relationship between shared beliefs – devotion, concerns and entertainment – and tourists’ perceived nostalgia.

This work contributes to information behavior using S-O-R theory. It analyzes the psychological and social risks of destination visits and how nostalgia affects shared beliefs and revisit intentions. Management and policymakers at destination enterprises can use the findings to design measures to enhance revisit intentions despite risk considerations.

Pakistan's destination tourism is underutilized amid its religious and cultural heritage significance. The literature has ignored how perceived psychological and social risk affects travelers' shared beliefs and nostalgic feelings. Thus, this study suggests and validates these linkages utilizing stimulus-organism-response (S-O-R) theory in Pakistan's unique environment with inbound tourists.

This study aims to examine the association between parental financial socialization and life satisfaction and the mediating roles of desirable financial behavior in the association between parental financial socialization and life satisfaction of college students in India. Furthermore, this research also explores the moderating effects of parents’ socioeconomic characteristics (education, income and professions) in the association between parental financial socialization and desirable financial behavior.

A sample of 1,161 college students was collected in India. Parental financial socialization is measured by direct parental teaching in this study. The first stage moderated mediation model is performed to examine the direct and indirect effects through financial behavior of parental financial on life satisfaction as well as the moderating role of parents’ socioeconomic characteristics.

The mediation analysis shows that parental direct teaching is positively associated with young adults’ financial behavior, which in turn contributes to their life satisfaction. Furthermore, this study also finds negative moderation effects of parental education on the association between parental direct teaching and children's financial behavior.

This study extends the knowledge of family financial socialization in the context of India. Moreover, it examines the mediation roles of desirable financial behavior in the association between parental direct teaching and children’s life satisfaction. Furthermore, this paper explores the potential influence of parents’ education, income and professions on children’s financial behavior and life satisfaction.

The main purpose of this study is to explore the effect of three dimensions of “home feeling” – home-as-practical, home-as-social and home-as-attachment – on the online rating of homestays and additionally considers the accommodation’s attribute performance and level of sharing.

To achieve the research aims, more than 9,738,335 items of user-generated content concerning 743,953 Airbnb listings covering 35 cities were collected as the study data. These data are analyzed through hierarchical regression.

The results show that all three dimensions of home feeling positively affect the online rating; all three dimensions negatively moderate the relationship between attribute performance and online rating; the size of the moderating effect of each dimension on the relationship between attribute performance and online rating gradually increases in the order home-as-practical, home-as-social and home-as-attachment; and as the level of sharing increases, the moderating effect of home feeling on the relationship between attribute performance and online rating diminishes.

This study contributes to the literatures on the role of home feeling in homestays, the online rating of homestays and the motivations of guests who choose different room types. The findings of this study can help hosts better understand the formation of online rating of homestays, make targeted improvements in rooms and services and create a home feeling for specific degrees of sharing. This in turn will help them to improve the online rating of their homestays, establish an excellent online reputation and, ultimately, increase sales.

This study advances knowledge by confirming three dimensions of home feeling not only have direct positive impacts on online rating but also mitigate the impact of attribute performance on online rating. This effect differs significantly in magnitude with the degree of sharing.

This paper aims to propose a robust method for non-rigid point set registration, using the Gaussian mixture model and accommodating non-rigid transformations. The posterior probabilities of the mixture model are determined through the proposed integrated feature divergence.

The method involves an alternating two-step framework, comprising correspondence estimation and subsequent transformation updating. For correspondence estimation, integrated feature divergences including both global and local features, are coupled with deterministic annealing to address the non-convexity problem of registration. For transformation updating, the expectation-maximization iteration scheme is introduced to iteratively refine correspondence and transformation estimation until convergence.

The experiments confirm that the proposed registration approach exhibits remarkable robustness on deformation, noise, outliers and occlusion for both 2D and 3D point clouds. Furthermore, the proposed method outperforms existing analogous algorithms in terms of time complexity. Application of stabilizing and securing intermodal containers loaded on ships is performed. The results demonstrate that the proposed registration framework exhibits excellent adaptability for real-scan point clouds, and achieves comparatively superior alignments in a shorter time.

The integrated feature divergence, involving both global and local information of points, is proven to be an effective indicator for measuring the reliability of point correspondences. This inclusion prevents premature convergence, resulting in more robust registration results for our proposed method. Simultaneously, the total operating time is reduced due to a lower number of iterations.