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To enrich the research on the economic consequences of enterprise digital development from the perspective of capacity utilization.

Using a sample of listed firms from 2010 to 2020, this paper exploits text analysis of annual reports to construct a proxy for enterprise digital development.

Results show that enterprise digital development not only improves their own capacity utilization but also generates a positive spillover effect on the capacity utilization of peer firms and firms in the supply chain. Next, based on the incomplete information about market demand and potential competitors when making capacity-building decisions, the mechanism tests show that improving the accuracy of market forecasts and reducing investment surges are potential channels behind the baseline results. Cross-sectional tests show the baseline result is more pronounced when industries are highly homogeneous and when firms have access to less information.

This paper contributes to the research related to the economic consequences of digital development. With the development of the digital economy, the real effects of enterprise digital development have also triggered extensive interest and exploration. Existing studies mainly examine the impact on physical operations, such as specialization division of labor, innovation activities, business performance or total factor productivity (Huang, Yu, & Zhang, 2019; Yuan, Xiao, Geng, & Sheng, 2021; Wang, Kuang, & Shao, 2017; Li, Liu, & Shao, 2021; Zhao, Wang, & Li, 2021). These studies measure the economic benefits from the perspective of the supply (output) side but neglect the importance of the supply system to adapt to the actual market demand. In contrast, this paper focuses on capacity utilization, aimed at estimating the net economic effect of digital development by considering the supply-demand fit scenario. Thus, our findings enrich the relevant studies on the potential consequences of digital development.

The objective of this study is to investigate consumer motivations and purchase behaviors with respect to cookies with customized packaging and consumer interest in different types of customization in the Italian food industry.

The study was conducted by performing a quantitative analysis of 642 surveys collected via Google Forms. A repeated-measures ANOVA, univariate ANOVA, chi-squared test, correlation analysis and linear regression analysis were conducted using SPSS.

Customers buy cookies with customized packaging as personal gifts to someone they care about. The ability to insert their initials or a personalized phrase appears to increase customers’ positive attitudes toward buying cookies with customized packaging. Those interested in this type of customization are willing to pay more, regardless of the type of customization.

In the survey, only some types of customization not previously extracted from a focus group are explored, and the analysis covers only the food industry and does not take a cross-sectional approach. In addition, we specifically refer to the Italian market, which means that results cannot be generalized.

From a managerial perspective, our results highlight that food industry companies should take advantage of the opportunity to segment the demand for customized packaging with respect to consumers’ attitudes and their motivation toward food products.

From a theoretical perspective, this study analyzes consumer attitudes and behaviors toward purchasing cookies with customized packaging. From a managerial perspective, the results of the study highlight interesting courses of action for companies in the food industry that would like to use the tool of customization by intervening in terms of the packaging rather than the product itself.

This study aims to use geographical information on social media for public opinion risk identification during a crisis.

This study constructs a double-layer network that associates the online public opinion with geographical information. In the double-layer network, Gaussian process regression is used to train the prediction model for geographical locations. Second, cross-space information flow is described using local government data availability and regional internet development indicators. Finally, the structural characteristics and information flow of the double-layer network are explored to capture public opinion risks in a fine-grained manner. This study used the early stages of the COVID-19 outbreak for validation analyses, and it collected more than 90,000 pieces of public opinion data from microblogs.

In the early stages of the COVID-19 outbreak, the double-layer network exhibited a radiating state, and the information dissemination was more dependent on the nodes with higher in-degree. Moreover, the double-layer network structure showed geographical differences. The risk contagion was more significant in areas where information flow was prominent, but the influence of nodes was reduced.

Public opinion risk identification that incorporates geographical scenarios contributes to enhanced situational awareness. This study not only effectively extends geographical information on social media, but also provides valuable insights for accurately responding to public opinion.

This study aims to examine if and how an activity-based work environment affects employee workspace satisfaction – an attitude linked to important employee outcomes. By comparing perceptions before and after implementation, the research draws attention to factors that may help explain the impact of an activity-based work environment. Specifically, prior attitudes toward activity-based work environments and gender are tested.

The present study uses a longitudinal design to explore how implementing an activity-based work environment impacts employees’ workspace satisfaction (e.g. privacy, air quality, lighting, temperature, etc.). A sample of 100 employees in a government organization implementing an activity-based working environment was investigated using a longitudinal design, with employees being surveyed thrice – once before and twice after implementation.

The results indicate that when workspace satisfaction is impacted by implementing an activity-based work environment, this effect seems primarily based on employees’ prior attitude toward such work environments. In addition, employee gender emerges as a potentially important factor in workspace satisfaction, though not exclusive to the activity-based work environment.

Using a longitudinal approach – which allows for observing potential changes over time – and robust statistical methods, this study supports the importance of employees’ initial attitude toward an activity-based work environment concerning workspace satisfaction. This finding has practical implications for organizations and advances the understanding of why an activity-based work environment may positively affect workspace satisfaction for some employees while negatively affecting others.

In this study, a different approach is introduced to generate the kinetic sub-model for the modeling of solid-state pyrolysis reactions based on the thermogravimetric (TG) experimental data over a specified range of heating rates. Gene Expression Programming (GEP) is used to produce a correlation for the single-step global reaction rate as a function of determining kinetic variables, namely conversion, temperature, and heating rate.

For a case study on the coal pyrolysis, a coefficient of determination (R²) of 0.99 was obtained using the generated model according to the experimental benchmark data. Comparison of the model results with the experimental data proves the applicability, reliability, and convenience of GEP as a powerful tool for modeling purposes in the solid-state pyrolysis reactions.

The resulting kinetic sub-model takes advantage of particular characteristics, to be highly efficient, simple, accurate, and computationally attractive, which facilitates the CFD simulation of real pyrolizers under isothermal and non-isothermal conditions.

It should be emphasized that the above-mentioned manuscript is not under evaluation in any journals and submitted exclusively for consideration for possible publication in this journal. The generated kinetic model is in the final form of an algebraic correlation which, in comparison to the conventional kinetic models, suggests several advantages: to be relatively simpler, more accurate, and numerically efficient. These characteristics make the proposed model computationally attractive when used as a sub-model in CFD applications to simulate real pyrolizers under complex heating conditions.

This study aims to examine the impact of digital transformation on firms’ value and explore the mediating impact of ESG performance and moderating impact of information interaction.

Data was collected from companies listed on the Shanghai and Shenzhen stock exchange between 2012 and 2020 with 21,488 observational samples, featuring a selection of 3,348 companies. Panel data regression techniques were used to test the mediating role of ESG performance and the moderating role of information interaction.

The study found that digital transformation can improve firms’ ESG performance, which in turn positively affects their value. The firms that engage in more interaction with outsiders benefit more from digital transformation and have a higher value.

This study provides new theoretical insight into improving firms’ value through digital transformation and ESG performance. It is the first to discuss and study the moderating role of information interaction in the relationship between digital transformation and firms’ value.

This study aims to explore how transformational leadership influences employees' creativity by considering the role of the environment and psychology. The study aims to provide insights into the impact of transformational leadership on team innovation climate, team reflexivity, psychological capital and employee creativity while also examining the moderating effect of environmental dynamism on these relationships.

This study employed a multi-source, multi-wave approach, utilizing data from 618 participants in 118 teams. It constructed a multilevel structural equation model and estimated the confidence intervals of the mediated and moderated effects using the Markov chain Monte Carlo method.

The results of the multilevel analyses indicated that transformational leadership positively influenced the team innovation climate, team reflexivity, psychological capital and employee creativity. Moreover, the study found that environmental dynamism positively moderates the relationships among transformational leadership, team reflexivity, psychological capital and employee creativity.

Drawing on social cognitive theory and the motivated information processing in groups model, this study offers new insights into the interplay between transformational leadership and creativity. It examines the moderating role of cross-level process linkages and environmental dynamism, thereby validating and extending relevant theories.