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The purpose of this paper is to study the optimization of the geographical location of a network of points of sale, so that each retailer can have access to a potential geographic market. In addition, the authors study the importance of the distance variable in the commercial viability of a point of sale and a network of points of sale, analysing if the best location for each point (local optimum) is always the best location for the whole (global optimum).

Location-allocation models are applied using p-median algorithms and spatial competition maximization to analyse the actual journeys of 64,740 car buyers in 1240 postal codes using a geographic information system (GIS) and geomarketing techniques.

The models show that the pursuit of individual objectives by each concessionaire over the collective provides poorer results for the whole network of points of sale when compared to coordinated competition. The solutions provided by the models considering geographic and marketing criteria permit a reduction in the length of journeys made by the buyers. GIS allows the optimal control of market demand coverage through the collaborative strategies of the supplying retailers, in this case, car dealerships.

The paper contributes to the joint research of geography and marketing from a theoretical and practical point of view. The main contribution is the use of information on actual buyer journeys for the optimal location of a network of points of sale. This research also contributes to the analysis of the correlation between the optimum local and optimum global locations of a commercial network and is a pioneering work in the application of these models to the automotive sector in the territorial area of the study.

China is the world’s largest user market for digital technologies and experiencing unprecedented rates of rural-urban migration set to create the world’s first “urban billion”. This is an important context for studying nuanced adoption behaviours that define a digital divide. Large-scale studies are required to determine what behaviours exist in such populations, but can offer limited ability to draw inferences about why. The purpose of this paper is to report a large-scale study inside China that probes a nuanced “digital divide” behaviour: consumer demographics indicating ability to pay by electronic means but behaviour suggesting lack of willingness to do so, and extends current demographics to help explain this.

The authors report trans-national access to commercial “Big Data” inside China capturing the demographics and consumption of millions of consumers across a wide range of physical and digital market channels. Focusing on one urban location we combine traditional demographics with a new measure that reflecting migration: “Distance from Home”, and use data-mining techniques to develop a model that predicts use behaviour.

Use behaviour is predictable. Most use is explained by value of the transaction. “Distance from Home” is more predictive of technology use than traditional demographics.

Results suggest traditional demographics are insufficient to explain “why” use/non-use occurs and hence an insufficient basis to formulate and target government policy.

The authors understand this to be the first large-scale trans-national study of use/non-use of digital channels within China, and the first study of the impact of distance on ICT adoption.

The purpose of this study is to examine whether and how analysts’ foreign ancestral origins would have an effect on analysts’ earning forecasts in particular and ultimately on firms’ information environment in general.

By inferring analysts’ ancestral countries based on their surnames, this study empirically examines whether analysts’ ancestral countries affect their earnings forecast errors.

Using novel data on analysts’ foreign ancestral origins from more than 110 countries, this study finds that relative to analysts with common American surnames, analysts with common foreign surnames tend to have higher earnings forecast errors. The positive relation between analyst foreign surnames and earnings forecast errors is more likely to be observed for African-American analysts and analysts whose ancestry countries are geographically apart from the USA. In contrast, this study finds that when analysts’ foreign countries of ancestry are aligned with that of the CEOs, analysts exhibit lower earnings forecast errors relative to analysts with common American surnames. More importantly, the results show that firms followed by more analysts with foreign surnames tend to exhibit higher earnings forecast errors.

Taken together, findings of this study are consistent with the conjecture that geographical, social and ethnical proximity between managers and analysts affect firms’ information environment. Therefore, this study contributes to the determinants of analysts’ earnings forecast errors and adds to the literature on firms’ information environment.

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.

Climate risk greatly increases the risk exposure of global investments. Both the climate risks of home countries and host countries may affect international investment behaviors. The purpose of this paper is to explore the impact of climate risk and climate risk distance on foreign direct investment (FDI) inflows and outflows. Targeted proposals are provided to promote international economic and trade cooperation and the authors provide suggestions for the FDI strategies of multinational enterprises.

The authors define “climate risk distance” as the difference in climate risks between two countries. This paper uses both a theoretical model and a generalized least squares test to investigate the impact of climate risk distance on FDI from the perspectives of FDI inflows and outflows. In addition, the authors subdivide the samples according to the sign of climate risk distance and rank the FDI share from home country to host country into four groups according to the host country’s climate risk index. Finally, the authors undertake empirical tests with outward foreign direct investment (OFDI) data to support the empirical results.

Investors from countries with low climate risks have the upper hand due to their competitive advantages, like their skills, trademarks and patent rights, which they can transfer abroad to offset the disadvantage of being non-native. This is generally defined as ownership advantage. The impact of climate risk distance on FDI depends on the sign of climate risk distance. Specifically, host countries with higher climate risks compared with the climate risk levels of home countries may experience insignificant reductions in FDI inflows. For investors from home countries with higher climate risks, they are less likely to invest in host countries with lower climate risks. The results for samples from emerging market economies are shown to be more significant.

This study advances the O (ownership advantage) part of the ownership, location and internationalization (OLI) paradigm by incorporating the climate risk distance between the home country and the host country into the influencing factors of FDI. Both the O part and the L (location advantage, the advantage that host countries offers to make internationalization worthwhile to undertake FDI) part of the OLI paradigm concerning climate risks are validated with FDI and OFDI data.

By observing facts of the “reversal of agglomeration” of Chinese enterprises during the period of rapid Internet development and using a new economic geography model combined with the data of the real estate sector, this paper deduces the influence of the “reshaping mechanisms” of the Internet on China's economic geography based on the “gravitation mechanism” of the Internet that affects the enterprises and the “amplification mechanism” of the Internet that amplifies the dispersion force of house prices.

In the empirical aspect, the dynamic spatial panel data model is used to test the micromechanisms of the impact of the Internet on enterprises' choice of location and the instrumental variable method is used to verify the macro effects of the Internet in reshaping economic geography.

It is found that in the era of the network economy, the Internet has become a source of regional competitive advantage and is extremely attractive to enterprises. The rapidly rising house price has greatly increased the congestion cost and has become the force behind the dispersion of enterprises. China's infrastructure miracle has closed the access gap which gives full play to network externalities and promotes the movement of enterprises from areas with high house prices to areas with low house prices.

The Internet is amplifying the dispersion force of congestion costs manifested as house prices and is reshaping China's economic geography. This paper further proposes policy suggestions such as taking the Internet economy as the new momentum of China's economic development and implementing the strategy of regional coordinated development.

The purpose of this paper is to investigate the most recurrent variables characterizing the collaborative relationships of industrial symbiosis (IS) (hereinafter also referred to as “anatomic” variables) established in the attempt to adopt circular economy (CE) by collecting evidence from a rich empirical set of implementation cases in Italy.

The current literature on IS was reviewed, and a content analysis was performed to identify and define the “anatomic” variables affecting its adoption in the circular economy. We followed a multiple-case study methodology investigating 50 cases of IS in Italy and performed a content analysis of the “anatomic” variables characterizing each case.

This research proposes the “anatomic” variables (i.e. industrial sectors involved, public actors involvement, governmental support, facilitator involvement and geographical proximity) explaining the cases of IS in the circular economy. Each “anatomic” variable is discussed at length based on the empirical evidence collected, with a particular reference to the impact on the different development strategies (i.e. “bottom-up” and “top-down”) in the cases observed.

Current literature on IS focuses on a sub-set of variables characterizing collaboration in IS. This research builds on extant literature to define a new framework of five purposeful “anatomic” variables defining IS in the circular economy. Moreover, we also collect and discuss a broad variety of empirical evidence in what is a still under-investigated context (i.e. Italy).

This study aims to understand the role of drivers, underlying challenges and, consequently, the implications of the reverse knowledge transfer (RKT) process for the multinational enterprises (MNE)s.

A dyadic qualitative research design was used with a cross-country design covering perspectives from both the headquarters and subsidiaries from the USA, Denmark, Pakistan, India and Bangladesh. In-depth interviews were conducted with managers in multiple sectors such as information technology, telecommunications, project management and engineering.

The study reveals the constraints and drivers of the RKT process, and furthermore elaborates on the implications for MNEs. RKT can lead to the development of new processes, subsidiary independence and intra-organizational knowledge transfer. Besides, it can entail challenges such as position insecurity for subsidiaries and a blurring of the MNE market vision. The findings demonstrate several implications for the MNEs.

The study highlights the direct implications of RKT for the multinational enterprises. The findings serve as a practical guide for global managers seeking to improve their competitive edge.

The study presents a framework of the RKT process from emerging market subsidiaries to parent companies, that demonstrates the role of drivers, underlying challenges and implications of the RKT process for the MNEs.

Analyzing the main determinants that lead a traveler to make a cultural trip is an important issue to understand where the cultural tourism market is going, and where the decision-makers should intervene. This study helps develop a profile of cultural tourism participants, and underscore the changes in this market niche. This information is crucial for the successful marketing and development of cultural tourism in the future.

The authors estimate a binary probabilistic (logit) model to determine the probability of a tourist to travel for cultural reasons, as a function of the traveler's socio-economic characteristic (e.g. age, gender, income or level of studies), of the trip-related characteristics (e.g. distance traveled to destination or mode of transport) and of the characteristics of the province of destination (e.g. weather conditions or existence of cultural sites at destination).

This study’s estimates reveal that middle-aged individuals, with a higher level of studies and with a medium level of income show a higher propensity to travel for cultural reasons. The latter finding evidences that cultural tourism has evolved from a niche market reserved for an elite clientele to a much wider range of people. Additionally, cultural travelers tend to travel statistically much longer distances. They are less prone to visit crowded destinations, prefer visiting destinations with important cultural sites, and are less sensitive to weather conditions. Finally, the authors discover a complementary effect of culture tourism and other activities carried out during the trip such as visiting cities or theme parks; and a substitution effect with “beach-and-sun” tourism.

The information given in this study can be crucial for the successful marketing and development of cultural tourism in the future. A better understanding of the main determinants of being a cultural traveler implies a better and a more efficient implementation of managerial and political measures to attract a kind of tourism characterized by a high spending capacity.

Discovering the main determinants of being a cultural traveler is a topic scarcely treated in the literature. This study has the main originality to include characteristics of the destination (pull factors) to explain the individual's decision to take a cultural trip. Moreover, the authors work at a provincial (NUTS-3) level of analysis, which makes this study original in the field of cultural tourism.

Supporting distant teams is a frequent phenomenon. Through the lens of the social identity theory, this research aims to examine differences between local and distant fans regarding drivers of team identification.

A multigroup structural equation model was employed. The data were collected through an online survey with 1,285 sports fans.

Team distinctiveness constitutes an important aspect fueling identification for all fans, whereas congruence between own and team personality is important for local and displaced fans only. Team prestige does not impact identification for either group.

To build up a base of highly identified supporters, clubs should emphasize those aspects of team brands that fans consider distinctive. When targeting local fans, clubs should also focus on communicating the brand's unique personality aspects.

This is the first study that assesses the potential differences behind fans' social identification with local and distant teams.