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This study combines institutional and organizational learning perspectives to investigate the impact of institutional distance and institution-specific cross-border acquisition experience in emerging markets on cross-border acquisition performance.

The sample consists of 874 transactions involving targets across 37 emerging markets by 484 different acquirers from 45 developed and emerging markets. The authors decompose institutional distance and acquisition experience along their cultural, administrative, geographic and economic dimensions.

The authors find that cultural, administrative and geographic distance have a negative impact on acquisition performance. In contrast, economic distance does not appear detrimental to acquisition performance across markets. The study provides evidence that a company may apply learnings from previous transactions in similar cultural and economic emerging market environments to elevate the likelihood of a successful acquisition.

This study offers a more fine-grained perspective of the distance concept by decomposing the concepts of institutional distance and acquisition experience along different institutional dimensions. The research across 37 emerging markets sheds light on which of the similarities and differences between these markets are relevant concerning acquisition experience and performance.

This article examines the influence of market opportunity, risk, and distance on the choice of destination country for Mexican franchises.

The research hypotheses are developed under the theoretical approaches of institutional theory, agency theory, and transaction costs theory and were contrasted on the data obtained from 52 Mexican international franchisors operating in 37 countries as of 2016. This study uses linear regression with ordinary minimums using the STATA 13.1 software.

The results reveal that a larger market size, a greater level of economic freedom, and a smaller geographic distance are determining factors in the choice of destination country. No statistical significance was found in the variables GDP per capita, level of democracy and cultural distance.

This research contributes to the theoretical and practical field. On the theoretical side, this study integrates institutional theory, agency theory, and transaction cost theory to evaluate the factors of the destination country that influence the internationalization process of the franchise. Another contribution of this study is to apply theories and models of developed economies to the process of internationalization of franchises in an emerging economy. Additionally, this study is based on a model that considers the distance, opportunities and risks that are considered by Mexican franchisors in the selection of the international markets in which they maintain operations. This study contains important practical implications that can serve as relevant information for decision-making in the franchise sector and its internationalization. This data is valuable for new models of Mexican franchises that decide to start their internationalization process.

Land transactions are a key indicator of urban sustainable development and urban space expansion. Therefore, this paper aims to study the spatial correlation of different types of land transactions.

Based on the big data of land micro transactions in Yangtze River Delta urban agglomeration, this paper uses the generalized forecast error variance decomposition (GFEVD) method to measure the correlation level of urban land markets. Also, social network analysis (SNA) is used to describe spatial correlation network characteristics of an urban agglomeration land market. In the meantime, the factors that influence the spatial correlation of urban land markets are investigated through a quadratic assignment procedure (QAP).

The price growth rate of urban residential land was higher than that of industrial land and commercial land. The spatial relevance of urban residential land is the highest, while the spatial relevance of the urban commercial land market is the lowest. The urban industrial land market, commercial land market and residential land market all present a typical network structure. Population distance (POD) and Engel coefficient distance (EGD) are negatively correlated with the correlation degree of the urban residential land network; traffic distance (TRD) and economic distance (ECD) are negatively correlated with the correlation degree of the urban industrial land network and commercial land network.

This paper uses a systematically-integrated series of problem-solving models to better explain the development path of urban land markets and to realize the integration of the interdisciplinary methods of geography, statistics and big data analysis.

This study aimed to identify a specific taxonomy of entry modes for international construction contractors and to develop a decision-making mechanism based on case-based reasoning (CBR) to facilitate the selection of the most suitable entry modes.

According to the experience orientation of the construction industry, a CBR entry mode decision model was established, and based on successful historical cases, a two-step refinement process was carried out to identify similar situations. Then the validity of the model is proved by case analysis.

This study identified an entry mode taxonomy for international construction contractors (ICCs) and explored their decision-making mechanisms. First, a two-dimension model of entry mode for ICCs was constructed from ownership and value chain dimensions; seven common ICC entry modes were identified and ranked according to market commitment. Secondly, this study reveals the impact mechanism of the ICC entry mode from two aspects: the external environment and enterprise characteristics. Accordingly, an entry mode decision model is established.

Firstly, sorting out the categories of entry mode in the construction field, which provide an entry mode list for ICCs to select. Secondly, revealing the impact mechanism of ICC entry mode, which proposes a systematic decision-making system for the selection of ICC entry mode. Thirdly, constructing a CBR entry mode decision-making model from an empirical perspective, which offers tool support and reduces transaction costs in the decision-making process.

The study on entry modes for ICCs is still in the preliminary exploratory stage. The authors investigate the entry mode categories and decision-making mechanisms for ICCs based on Uppsala internationalization process theory. It widens the applied scope of Uppsala and promotes cross-disciplinary integration. In addition, the authors creatively propose a two-stage retrieval mechanism in the CBR model, which considers the order of decision variables. It refines the influence path of the decision variables on ICCs' entry mode.

The study aims to discover the spatial relationship between financial development, energy consumption and economic growth in 11 ASIA countries, using panel data from 1980 to 2016.

The study applies three popular spatial models, namely, (1) spatial error model (SEM), (2) spatial autoregressive model (SAR) and (3) spatial Durbin model (SDM), to explore the direct and spillover effect of financial development and energy consumption on economic growth. Furthermore, a novel test proposed by Juodis et al. (2020) is employed to check the Granger non-causality between each pair of variables.

The empirical outcomes found direct and spillover effects of financial development and energy consumption on economic growth in 11 ASIA countries. Accordingly, an expansion of the financial development in country i is beneficial for the growth of the host country and neighboring countries, and vice versa. However, an increase in energy consumption in country i leads to a decrease in the economic growth of neighboring countries. The test of Granger non-causality indicated a bidirectional causality between financial development and economic growth, and unidirectional causality running from economic growth to energy consumption.

Spillover effects of financial development and energy consumption on growth have largely been ignored in previous studies, especially in emerging countries. Thus, the study enriches the literature and provides some policy implications for ASIA countries.

Spillover effects of financial development and energy consumption on growth have largely been ignored in previous studies, especially in emerging countries. Thus, the study enriches the literature and provides some policy implications for ASIA countries.

Spillover effects of financial development and energy consumption on growth have largely been ignored in previous studies, especially in emerging countries. Thus, the study enriches the literature and provides some policy implications for ASIA countries.

This study aims to empirically examine the impact of digital finance on spatial urbanization and elucidate its underlying mechanisms.

Using panel data of Chinese prefecture-level cities from 2011 to 2021, and using a spatial dynamic panel model, the authors analyzed the effects of digital finance on spatial urbanization and the mechanism of its action.

The findings of the study reveal that digital finance, along with its sub-dimensions, namely coverage breadth, usage depth and digitization degree, all contribute to the enhancement of spatial urbanization. The information channel effect generated by the development of postal and telecommunication businesses, the goods delivery effect generated by the development of retail businesses and the wealth accumulation effect generated by the accumulation of household wealth are all important channels through which digital finance promotes spatial urbanization. Digital finance exerts a significant promotional effect on spatial urbanization in second-tier cities, third-tier cities and their subsequent tiers. This observation alludes to the regionally inclusive nature of spatial urbanization promotion facilitated by digital finance.

The present study endeavors to fill this void by employing empirical analysis to investigate the ramifications of digital finance on spatial urbanization, thereby shedding light on the pivotal role played by digital finance in expediting the progression of spatial urbanization. This study undertakes an examination of the spatial spillover effects, thus providing a comprehensive exposition of the influence of digital finance on spatial urbanization. This study introduces this crucial dimension, and the empirical findings elucidate that digital finance fosters the evolution of spatial urbanization by broadening the coverage of information channels, augmenting the efficiency of goods distribution and enhancing wealth accumulation efficacy.

Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations.

The authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches.

The results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect.

The findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity.

The paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.

This study aims to investigate the structural characteristics, spatial evolution paths and internal driving mechanisms of the knowledge transfer (KT) network in China’s patent-intensive industries (PIIs). The authors' goal is to provide valuable insights to inform policy-making that fosters the development of relevant industries. The authors also aim to offer a fresh perspective for future spatiotemporal studies on industrial KT and innovation networks.

In this study, the authors analyze the patent transfer (PT) data of listed companies in China’s information and communication technology (ICT) industry, spanning from 2010 to 2021. The authors use social network analysis and the quadratic assignment procedure (QAP) method to explore the problem of China’s PIIs KT from the perspectives of technical characteristics evolution, network and spatial evolution and internal driving mechanisms.

The results indicate that the knowledge fields involved in the PT of China’s ICT industry primarily focus on digital information transmission technology. From 2010 to 2021, the scale of the ICT industry’s KT network expanded rapidly. However, the polarization of industrial knowledge distribution is becoming more serious. QAP regression analysis shows that economic proximity and geographical proximity do not affect KT activities. The similarity of knowledge application capacity, innovation capacity and technology demand categories in various regions has a certain degree of impact on KT in the ICT industry.

The current research on PIIs mainly focuses on measuring economic contributions and innovation efficiency, but less on KT in PIIs. This study explores KT in PIIs from the perspectives of technological characteristics, network and spatial evolution. The authors propose a theoretical framework to understand the internal driving mechanisms of industrial KT networks.

This article aims at - exploring and prioritizing the barriers to adoption of digitization in supply chains (SCs), categorizing them into sustainability triple bottom line (STBL) based upon their direct impact and suggesting digital technologies to address each barrier.

A five-phase methodology is used which consists of an exploration of 44 barriers to the adoption of digitization in SCs, analysis of 44 barriers for mean, standard deviation and Cronbach alpha based on questionnaire-based feedback of 25 experts, extraction of 10 most significant barriers through 05 experts, followed by categorization of the barriers into STBL referring to their direct impact on STBL, prioritization of ten barriers using Fuzzy Technique for Order Performance by Similarity to Ideal Solution and recommendation of digital technologies to address each barrier.

While all the barriers considered in this study significantly impede the adoption of digitization in SCs, lack of top management commitment (B1) is found to be most crucial while lack of culture toward use of information and communication technology required for digitization (B3) has minimum impact. Large investment in digital infrastructure (B6), difficulty in integration of cyber physical systems (CPSs) on varied platforms (B8) and lack of experts having knowledge of digital technologies (B2) are equally important barriers requiring more attention while adopting digitization in SCs.

This study is mainly based on feedback from 25 seasoned experts; a wider cross section of experts will give more insight.

The outcomes are very significant for organizations looking to adopt digitization in their SCs. Simultaneous consideration to all the barriers becomes impractical hence prioritization of same will be useful for the SC managers to benchmark their preparedness and decide strategies for the adoption of digitization with due consideration toward the impact of barriers on STBL. The digital technologies recommended will further aid in planning the digital strategies to address each barrier.

A unique approach to explore, analyze, prioritize and categorize the barriers to adoption of digitization in SCs is used to provide a deeper understanding of factors deterring the same. It implies that a supportive top management along with systematic allocation of finances plays a crucial role. The importance of availability of digital experts for integrating CPSs on a single platform is also highlighted. The digital technologies recommended will further assist the organizations toward adoption of digitization in SCs with due consideration to STBL.

The authors investigate the effects of Chinese acquirer’s chief executive officer (CEO) risk preference on mergers and acquisitions (M&A) payment method and the moderating roles played by acquirer’s ownership, industry relatedness and whether the M&A is cross-border.

Using 4,624 worldwide M&A deals conducted by Chinese firms from 2009 to 2021, the authors conduct multiple linear regression and ordered probit regression. And comprehensive indexes constructed based on the observed features of acquirer’s CEOs are used to be the proxy for CEO risk preference.

The results show that the higher-level Chinese acquirer’s CEO risk preference is overall positively associated with using more stock in payment. Moreover, the above relationship is strengthened if the ownership of the acquirer is state-owned.

The authors highlight the importance of the non-economic factors and demonstrate a relationship between the Chinese acquirer’s CEO risk preference and the M&A payment method, providing support for and enriching the upper echelons theory (UET). Moreover, the unique risk priorities of Chinese acquirers’ CEOs are revealed.