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The availability of spatial databases and widespread use of geographic information systems has stimulated increasing interest in the analysis and modelling of spatial data. Spatial data analysis focuses on detecting patterns, and on exploring and modelling relationships between them in order to understand the processes responsible for their emergence. In this way, the role of space is emphasised , and our understanding of the working and representation of space, spatial patterns, and processes is enhanced. In applied research, the recognition of the spatial dimension often yields different and more meaningful results and helps to avoid erroneous conclusions. This book aims to provide an introduction into spatial data analysis to graduates interested in applied statistical research. The text has been structured from a data-driven rather than a theory-based perspective, and focuses on those models, methods and techniques which are both accessible and of practical use for graduate students. Exploratory techniques as well as more formal model-based approaches are presented, and both area data and origin-destination flow data are considered.

The human immunodeficiency virus (HIV) infection rate for men who have sex with men (MSM) has rapidly increased in recent years in China and the migrant population accounts for a large proportion of this increase. The migration of MSM not only poses difficulties for government departments charged with treating the disease, but also increases the spread of HIV in geographical space, so it is important to understand the geographical distribution and migrant patterns of MSM. We searched the largest dating website in China to obtain open information from all users in the Chinese mainland from January 2006 to August 2017. For the analysis, the datasets were merged according to units of time and administrative regions. In total, 1,356,609 records were obtained for this study. The main users of the website were single males aged 18–35 years old. Most of the users were located in the large and mid-sized cities of East China. The distribution of MSM was strongly associated with the distribution of the development of service industry in geographical space. The main flow of MSM are mainly located inside the province as internal flow. For those MSM who prefer to migrate to other provinces, the Beijing-Tianjin-Hebei area, the Yangtze River Delta, the Pearl River Delta, and Sichuan and Chongqing area were their primary destinations. The interprovincial migration behavior of MSM was closely related to an increased average income. MSM prefer to migrate to cities with developed economies and open cultures. It is important to strengthen the management of migrant MSM and increase their basic understanding of HIV.

Abstract Background Severe acute respiratory syndrome (SARS) originated in China in 2002, and it spread to 26 provinces in mainland China and 32 countries across five continents in a matter of months. This outbreak resulted in 774 deaths. However, the spatial features and potential determinants of SARS input-output flows remain unclear. Methods We used an adjusted spatial interaction model to examine the spatial effects and potential factors associated with SARS input-output flows. Results The presence of origin-based spatial dependence positively affected SARS input-output flows from the neighbours of the origin regions. Two components of the input-output flows, migrant and hospitalization flows, exhibited distinctive features. The origin-based and destination-based spatial dependence positively affected migrant flows (i.e., due to those seeking jobs) from the neighbours of origin and destination locations. Similarly, the destination-based spatial dependence also positively affected hospitalization flows (i.e., due to those seeking treatment) from the neighbours of destination regions. However, the origin-to-destination based spatial dependence negatively affected hospitalisation flows from the neighbours of origin-to-destination regions. The direct effects accounted for 78 % of the SARS input-output flows, which was 3.56-fold greater than the indirect effects. Differences in regional income drove the SARS input-output flows. Therefore, urban income had a positive effect, whereas rural income had a negative effect. Total interregional flows increased by 3.54 % with a 1 % increase in urban income, and intraregional flows increased by 8.35 %. In contrast, the total interregional flows decreased by 3.38 % with a 1 % increase in rural income, and intraregional flows declined by 2.29 %. Railway capacity, per person gross domestic product (PGDP), urban rate and the law of distance decay also affected the input-output flows. Conclusions Our results confirm that the SARS input-output flows presented significant geographic spatial heterogeneity and spatial effects. Income differences were the major cause of the flows between pairs of regions. Railway capacity, PGDP, and urban rate also played important roles. These findings provide valuable information for the Chinese government to control the future spread of nationwide epidemics.

Vulnerability of human beings exposed to a catastrophic disaster is affected by multiple factors that include hazard intensity, environment, and individual characteristics. The traditional approach to vulnerability assessment, based on the aggregate‐area method and unsupervised learning, cannot incorporate spatial information; thus, vulnerability can be only roughly assessed. In this article, we propose Bayesian network (BN) and spatial analysis techniques to mine spatial data sets to evaluate the vulnerability of human beings. In our approach, spatial analysis is leveraged to preprocess the data; for example, kernel density analysis (KDA) and accumulative road cost surface modeling (ARCSM) are employed to quantify the influence of geofeatures on vulnerability and relate such influence to spatial distance. The knowledge‐ and data‐based BN provides a consistent platform to integrate a variety of factors, including those extracted by KDA and ARCSM to model vulnerability uncertainty. We also consider the model's uncertainty and use the Bayesian model average and Occam's Window to average the multiple models obtained by our approach to robust prediction of the risk and vulnerability. We compare our approach with other probabilistic models in the case study of seismic risk and conclude that our approach is a good means to mining spatial data sets for evaluating vulnerability.

PurposeThe desired outcome in the new product development (NPD) effort is the timely commercialization of a profitable product. Whether marketing can benefit from the NPD case study is a critical but underresearched issue. The purpose of this study is to investigate the usage and quality of NPD case studies in business and industrial marketing.Design/methodology/approachTo investigate the prevalence and research quality of case studies on NPD in business and industrial marketing, 317 case studies published in mainstream journals over the past decade (2010–2020) are reviewed.FindingsThis study finds that the distribution of quantity and quality of case studies fluctuates across journals. The scores on the evaluation template for the different case study stages vary widely across journals. This indicates that different journals have different criteria and priorities for NPD case studies. By focusing on different issues, enterprises can quickly find appropriate journals and case results according to their own needs.Originality/valueThis paper can help spark a debate about the implementation and quality of NPD case studies, including future studies and practical applications. To the best of the authors' knowledge, no similar study has been found in existing studies.

Purpose
Implementing servitization requires collaborative efforts from multiple actors in the business network or ecosystem. A multi-actor perspective is considered valuable for understanding the process of servitization. This study aims to review the contemporary research on organizing servitization by multi-actor collaborations.


Design/methodology/approach
The approach of systematic literature review was used. In total, 90 English-language journal articles published from 2004 to 2021 were selected based on a series of rigorous steps. Furthermore, descriptive and thematic analyses were conducted to answer the predefined review questions.


Findings
The servitization research from the multi-actor collaboration perspective is an infant field yet growing increasingly. An integrative framework was proposed to reveal the extant related studies. In this framework, three typical servitization lenses emphasizing multi-actor collaborations were uncovered. Moreover, six categories of influence factors and possible positive and negative outcomes for this process were identified. Existing knowledge gaps and underlying research directions were also discussed to lay the foundations for future research.


Research limitations/implications
This research has been limited by the usage of single database, rigorous selection criteria by the Academic Journal Guide (AJG 2018) list and exclusion of non-English papers.


Originality/value
To the best of the authors' knowledge, this study is one of the earliest systematic literature reviews to explore the servitization issues by adopting a multi-actor perspective. The findings can consolidate the knowledge base of servitization and provide implications for the multiple fields of industrial marketing, operational management, information management and service marketing.

The ongoing coronavirus disease (COVID-19) pandemic has had a far-reaching impact on urban living, prompting emergency preparedness and response from public health governance at multiple levels. The Chinese government has adopted a series of policy measures to control infectious disease, for which cities are the key spatial units. This research traces and reports analyses of those policy measures and their evolution in four Chinese cities: Zhengzhou, Hangzhou, Shanghai and Chengdu. The theoretical framework stems from conceptualisations of urban governance and its role in public health emergencies, wherein crisis management and emergency response are highlighted. In all four cities, the trend curves of cumulative diagnosed cases, critical policies launched in key time nodes and local governance approaches in the first wave were identified and compared. The findings suggest that capable local leadership is indispensable for controlling the coronavirus epidemic, yet local governments' approaches are varied, contributing to dissimilar local epidemic control policy pathways and positive outcomes in the fight against COVID-19. The effectiveness of disease control is determined by how local governments' measures have adapted to geospatial and socioeconomic heterogeneity. The coordinated actions from central to local governments also reveal an efficient, top-down command transmission and execution system for coping with the pandemic. This article argues that effective control of pandemics requires both a holistic package of governance strategies and locally adaptive governance measures/processes, and concludes with proposals for both a more effective response at the local level and identification of barriers to achieving these responses within diverse subnational institutional contexts.