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The purpose of this paper is to explore the data connection, spatial distribution characteristics and trends in genealogical information. First, it implements a spatial-temporal visualization of the Hakka genealogical information system that makes these individual family pedigree charts appear as one seamless genealogy to family and researchers seeking connections and family history all over the world. Second, this study applies migration analysis by applying big data technologies to Hakka genealogies to investigate the migration patterns of the Hakka ethnic group in Taiwan between 1954 and 2014. This innovative library service enhances the Hakka genealogical migration analysis using big data.

The platform is designed for the exchange of genealogical data to be used in big data analysis. This study integrates big data and geographic information systems (GIS) to map the population distribution themes. The general procedure included collecting genealogical big data, geographic encoding, gathering the map information, GIS layer integration and migration map production.

The analytical results demonstrate that big data technology is highly appropriate for family migration history analysis, given the increasing volume, velocity and variety of genealogical data. The spatial-temporal visualization of the genealogical research platform can follow family history and migration paths, and dynamically generate roadmaps to simplify the cartographic steps.

Technology that combines big data and GIS is suitable for performing migration analysis based on genealogy. A web-based application for spatial-temporal genealogical information also demonstrates the contribution of innovative library services.

Big data play a dominant role in library services, and in turn, provide an active library service. These findings indicate that big data technology can provide a suitable tool for improving library services.

Online genealogy and family trees are linked with large-volume, growing data sets that are complex and have multiple, autonomous sources. The migration analysis using big data has the potential to help genealogy researchers to construct minority ethnic history.

Conventional rule‐based systems are insufficient for description of complex dynamic systems requiring nontrivial decision procedures. Fuzzy cognitive maps seem to be convenient to overcome these limitations. However, they lack ability of self‐learning and therefore some adaptation approaches are needed. The purpose of this paper is both to show the use of fuzzy cognitive maps for such systems and to present migration algorithms as convenient adaptation means.

Some problems of a complex dynamic system description by knowledge‐based means are discussed. Fuzzy cognitive maps are presented as a possible way to solve these problems followed by description of migration algorithms as their adaptation means. Their use is clarified on an example of the so‐called parking problem based on path planning using a graph search algorithm and a traffic simulation system.

After series of simulations the reality of the proposed system and selected methods with their modifications was proved. It has shown the robustness of the presented solution under circumstances of uncertainty, too.

The paper points to stability investigation of the proposed approach introducing uncertainties into the traffic simulation system to take into account, e.g. unexpected events. Further, a possibility of developing a linguistic information retrieval system is mentioned.

The proposed approach can find various implementations not only in planning tasks but also in robotic navigation and multi‐agent applications in general. In addition, it suggests possibilities of knowledge‐based systems, directly using human‐like approaches, to areas of decision making under uncertainties and contradictories.

An new modification of migration algorithms for adaptation of parameters for fuzzy cognitive maps is introduced and compared to other known self‐learning methods. Further, the concept of a traffic simulation system for path planning is presented.

The purpose of this paper is to map the “migration pathways” (King and Skeldon, 2010) followed by interviews with a group of Vietnamese international labour migrants.

Through 50 in-depth interviews, the authors identify the reasons that explain the pathways observed.

The authors found that more than half of the interviewees did what King and Skeldon describe as a U-turn, whereby the migrants go abroad for work directly from their home town and return to settle there. The remainder did a J-turn, meaning the migrants returned and settled elsewhere. The majority of those doing a J-turn moved to another town/city within the province of their home town. Few return migrants settled outside their home province. The main explanations for the U-turn choice include existing investment in immobile assets in their home town, strong family ties, parental care obligations, lack of skill acquisition from international labour migration, age and for married migrants having children. Poor conditions in their home town, the absence of local job opportunities and better schooling for children were important considerations that made the J-turn more desirable. Having family ties in a new location, and affording the investment needed to settle in a new town, were important explanations to make the J-turn possible.

This paper highlights the need for economic development in rural Vietnam, including the creation of decentralised and sustainable livelihoods, so that return migrants have opportunities to reintegrate within their home communities.

Most discussions of knowledge, knowledge management and knowledge transfer, especially of human resource management (HRM) knowledge and its transfer, have failed to consider them in a cross‐cultural context. After a discussion of this issue, the paper analyses the migration or transfer of what is often claimed to be best practice in HRM from Western countries to developing, culturally different countries. It does this with specific reference to the case of HRM in Mauritius, especially in the Mauritian Civil Service, and uses this case not only to identify some of the limits to cross‐cultural knowledge management, but also to develop a more appropriate model of “knowledge migration” of HRM knowledge across cultures based on viable systems theory, including a future research agenda.

Disruptive innovation is particularly important during recovery periods, as companies need to win back customers with radically new value propositions. The purpose of this paper is to pull back all of the clutter and to present three critical lessons that companies must consider in their pursuit of disruptive innovation.

The lessons were extracted from systematic observations of successful and unsuccessful industry disruptors.

Three key lessons were uncovered: the ability to anticipate and act on market discontinuities and unmet customer needs, with a particular focus on the business model; The ability link incremental and breakthrough innovation efforts by focusing on a single, shared aspiration; and the recognition that disruptive innovation can inform strategy, just as strategy can (and should) inform disruptive innovation

These three lessons could help companies envision and commercialize disruptive innovation that dramatically reshape the competitive landscape of their industries.

This paper is targeted at companies seeking to offer dramatically new values to their customers and fundamentally alter the competitive balance of their industries. Envisioning and commercializing disruptive innovations is a means to this end. By applying the lessons learned from successful and not so successful innovators, companies have a better chance at winning.

This study aims to gauge the effect of rural–urban migration and its challenges on the urban development of Bengaluru. This study examines the driving forces behind urbanization and its impact on social, economic and environment areas. The research helps to establish the sustainable city planning, after evaluation of specific challenges of zones, and this mitigation will optimize government investment and reduce cost.

Bengaluru is used as a study area to examine the interaction of migration and urban development. The study covers the period between 2011 and 2019. Panel data analysis is applied to measure the effect of urban development indicators on urban migration. The authors applied the integrated urban metabolism analysis tool to quantify the urban development indicators and identified the most critical areas for migrants. Later, authors proposed mitigation measures based on alternate scenario approach.

The authors found that there is a mixed effect of urban migration on urban development across various zones in Bengaluru. Besides, the authors suggest how planned collaboration should play a significant role in urban planning and optimize city planning judiciously. Effective mitigation measures should be developed based on zone-specific core issues, and practical trainings, research, public awareness campaigns and skill up-gradation of migrants would enhance the socio-economic and environmental conditions.

The study will support the ongoing and upcoming initiatives launched by the Government of India i.e. Awas Yojna, Atmanirbhar Bharat and Swach Bharat.

The structured city planning suggested in the study will help to save wastage of resources and cost and time of developers and policymakers. This will also help to upgrade the status of migrants and enhance the ambience of city around social, economic and environment fronts.

The first of its kind of innovative model mapped in the study area establishes a link between strategic city planning under rural–urban migration and urban development.

Germany has become one of the major destination countries for labour migration within the European Union. The German government introduced temporary restrictions on labour migration after the eastern enlargement rounds of 2004 and 2007. These barriers had little impact on the overall volume of labour mobility. Rather they were accompanied by new “atypical” forms of mobility through the posting of workers, self-employment and seasonal workers, which according to EU rules are covered only by a minimum of host country regulations. The combination of temporary restrictions on regular migration and the opportunities through atypical mobility created strong incentives for companies to engage in ‘regime shopping’ strategies. This contributed to a considerable growth in outsourcing, subcontracting and flexible use of external labour added to pre-existing dynamics of low-wage competition, segmentation and fragmentation in the German labour market. Using data on the different forms of intra-EU migration to Germany, the article analyses the different paths that labour migration has frequently used since the fall of the Iron Curtain. First, it maps the changes in magnitude, character and direction of intra-EU labour mobility to Germany and the relative weight of the different channels through which such movements occurred from 2000 to 2015. Second, the article discusses the various responses by the government by the extension of collective agreements and the statutory minimum wage.

This paper aims to bring together research on housing market area, submarket and household migration into a systems approach that helps us gain a better understanding of the structure and dynamics of a housing market and identify housing problems for a large metropolitan area.

The paper uses a geographic information system (GIS)-based method with simple quantitative techniques, including spatial analysis, location analysis, house price clustering and cross-tabulation. The analysis is based on migration data from the 2011 Census, house price data from the Land Registry in 2011 for Greater Manchester at the ward level and the output areas level.

The results show that different submarkets and housing market areas had different patterns of spatial migration and connections with other areas. Through a systematic analysis of migration and house price in combination, it also found a close connection between destination submarkets and the ages of migrants and identified specific problematic patterns for a large metropolitan area.

The interactions between the owner-occupied sector and the social and private rented sectors are arguably an important omission from the analysis. Also, it is acknowledged that clustering ward units based on price differentials is subject to distortions in terms of specification, size and shape. Moreover, the use of the large samples may result in very small p-values, leading to the problem of the rejection of the predefined hypothesis.

A systematic analysis of migration and house price in combination may be used to gain a better understanding of the housing market dynamics and identify housing problems systematically for a large metropolitan. It may help to identify low-demand areas, high-demand areas and assist planners with decisions in allocating suitable land for new housing constructions.

The GIS-based method introduced in the paper could be considered as an effective approach to provide a better basis for determining policy interventions and public investment designed to allocate land resources effectively and improve transport systems to change existing problematic migration patterns.

This paper fills a gap in the international literature in relation to adopting a systems approach that analyses migration and house price data sets in combination to systematically explore migration patterns and linkages and identify housing problems for a large metropolitan area. This systems approach can be applied in any metropolitan area where migration and house price data are available.