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The purpose of this study is to examine the effects of executives’ overseas education and work experience on enterprise digital as executives’ overseas background is critical to the development of enterprises. It also explored the mediating role of enterprise digital transformation on the relationship between executives’ overseas background and enterprise growth.

Chinese A-share companies listed on the Shanghai and Shenzhen Stock Exchanges for the period 2018–2020 were analyzed using regression analysis and bootstrapping to verify hypothesized relationships.

Executives’ overseas study and work experience both enhanced enterprise digital transformation significantly, thus improving enterprise growth. The level of employee education moderated the mediating role proposed in the theoretical model. Moreover, the promoting effect of executives’ overseas background on enterprise digital transformation was more significant for non-state-owned enterprises and those in eastern China.

The findings provide reference for the formulation and optimization of companies’ human resource structure and have implications on the improvement of enterprise digital transformation and enterprise growth.

This study explored the factors influencing enterprise digital transformation at the microlevel of corporate human capital, thereby providing microlevel empirical evidence for research on the factors influencing enterprise digital transformation. Its findings shed light on the mechanism and context under which executives with overseas backgrounds may enhance enterprise digital transformation and growth.

This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR).

This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice.

The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%.

To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector.

Bicycle sharing offers a novel way to create smart and sustainable mobility solutions for the future. The purpose of this study is to draw on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) framework for identifying the factors necessary to predict bike-sharing intention among users in India.

Data were collected through a questionnaire distributed across four major cities in India, and 515 responses were analyzed. A sequential approach was employed to analyze the data using Partial Least Square–Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA).

The findings from PLS analysis revealed that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation and price value are the salient variables that affect users' intentions to participate in bike sharing. In addition, based on fsQCA, six configurations of causal conditions are presented as intermediate solutions that produce the same results. Although antecedent conditions, such as habit and social influence, had an insignificant effect on individuals' BSI, they create conditions sufficient to encourage users' participation in bike sharing in combination with other variables.

A few limitations of this research and the implications of the findings in terms of theory and policy implications are also discussed.

The reported study is one of the earliest to explain bike-sharing adoption in India using the UTAUT 2 model.