Virtual Geodemographics: Repositioning Area Classification for Online and Offline Spaces

Computer mediated communication and the Internet has fundamentally changed how consumers and producers connect and interact across both real space, and has also opened up new opportunities in virtual spaces. This paper describes how technologies capable of locating and sorting networked communities of geographically disparate individuals within virtual communities present a sea change in the conception, representation and analysis of socioeconomic distributions through geodemographic analysis. We argue that through virtual communities, social networks between individuals may subsume the role of neighbourhood areas as the most appropriate units of analysis, and as such, geodemographics needs to be repositioned in order to accommodate social similarities in virtual, as well as geographical, space. We end the paper by proposing a new model for geodemographics which spans both real and virtual geographies

Taka Company Strategic Change & Implementation Measures on Bata Company

Mergers and acquisitions (M&A) have been an important element of corporate strategy to building and growing businesses. M&A offer firms an opportunity to leverage existing capabilities and increase market share. The study of M&A varies as the performance of targeted companies continues to draw attention given the high collapse rate of most M&A. This study looks at the measures undertaken by management in managing expectations and charting a way forward for the acquired company and sustaining the growth and development. It is critical that an organization employ a well-defined integration and implementation strategy for any acquired businesses. The study of Taka’s company strategic integration and implementation of Bata’s company was researched utilizing documentation review, interviews and surveys. The performance of Taka’s acquisition of Bata Company was analyzed by studying its financial performance but most importantly the effectiveness of harnessing the human factor. M&A do not only involve acquiring capital asset but also the most commonly overlooked human factor. For any M&A, strategy to succeed management’s ability to harness the synergies of both companies is vital. For the synergies to be exploited management has to integrate and implement policies that assimilate the cultures of both companies, which rest with the personnel. A sound strategy alone that overlooks the human factor is not enough, as employee resistance and rebellion will subvert any prospects of success. This study looks at the adjustments of the employees of the acquired Bata Company. It looks at how the strategic changes implemented affect them in discharging their duties. Critical to succeeding an M&A strategy is effective communication. When done effectively, it cast aside any aspersions of mistrust and doubt in management. The better communicated the employees are the less time they spent speculating on future direction of the company

Corporate retail outlets are blessings in disguise for unorganized retail outlets: an empirical analysis in the Indian context

The objective of the present study is to answer the question whether the corporate organized retail outlets (ORO) have exerted any harmful effects on the small unorganized retail outlets (URO) in India. Answer to this question will facilitate us to gauge the impact of corporate FDI in retail on the survival of the small unorganized retail outlets, which is currently debated rigorously in India. Based on the primary survey data collected from the National Capital Region and Chennai between November 2008 and March 2010, the analysis in this study shows that the emergence of ORO did displace some URO, but increased employment in urban areas. The displaced URO, which opened businesses away from ORO have increased their profits. This indeed is a blessing in disguise for the small unorganized retail outlets. Thus, the total effects produced net social benefit in terms of income and employment generation in the concerned region.Kaliappa Kalirajan Crawford School of Public Policy The Australian National University, Canberra and Kanhaiya Singh National Council of Applied Economic Research New Delhi Authors: Kaliappa Kalirajan, Crawford School of Public Policy, The Australian National University, Canberra and Kanhaiya Singh, National Council of Applied Economic Research, New Delhi&nbsp

Business opportunities analysis using GIS: the retail distribution sector

[EN] The retail distribution sector is facing a difficult time as the current landscape is characterized by ever-increasing competition. In these conditions, the search for an appropriate location strategy has the potential to become a differentiating and competitive factor. Although, in theory, an increasing level of importance is placed on geography because of its key role in understanding the success of a business, this is not the case in practice. For this reason, the process outlined in this paper has been specifically developed to detect new business locations. The methodology consists of a range of analyzes with Geographical Information Systems (GISs) from a marketing point of view. This new approach is called geomarketing. First, geodemand and geocompetition are located on two separate digital maps using spatial and non-spatial databases. Second, a third map is obtained by matching this information with the demand not dealt with properly by the current commercial offer. Third, the Kernel density allows users to visualize results, thus facilitating decision-making by managers, regardless of their professional background. The advantage of this methodology is the capacity of GIS to handle large amounts of information, both spatial and non-spatial. A practical application is performed in Murcia (Spain) with 100 supermarkets and data at a city block level, which is the highest possible level of detail. This detection process can be used in any commercial distribution company, so it can be generalized and considered a global solution for retailers.Roig Tierno, H.; Baviera-Puig, A.; Buitrago Vera, JM. (2013). Business opportunities analysis using GIS: the retail distribution sector. Global Business Perspectives. 1(3):226-238. doi:10.1007/s40196-013-0015-6S22623813Alarcón, S. (2011). The trade credit in the Spanish agrofood industry. Mediterranean Journal of Economics, Agriculture and Environment (New Medit), 10(2), 51–57.Alcaide, J. 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Using Hybrid Agent-Based Systems to Model Spatially-Influenced Retail Markets

One emerging area of agent-based modelling is retail markets; however, there are problems with modelling such systems. The vast size of such markets makes individual-level modelling, for example of customers, difficult and this is particularly true where the markets are spatially complex. There is an emerging recognition that the power of agent-based systems is enhanced when integrated with other AI-based and conventional approaches. The resulting hybrid models are powerful tools that combine the flexibility of the agent-based methodology with the strengths of more traditional modelling. Such combinations allow us to consider agent-based modelling of such large-scale and complex retail markets. In particular, this paper examines the application of a hybrid agent-based model to a retail petrol market. An agent model was constructed and experiments were conducted to determine whether the trends and patterns of the retail petrol market could be replicated. Consumer behaviour was incorporated by the inclusion of a spatial interaction (SI) model and a network component. The model is shown to reproduce the spatial patterns seen in the real market, as well as well known behaviours of the market such as the "rocket and feathers" effect. In addition the model was successful at predicting the long term profitability of individual retailers. The results show that agent-based modelling has the ability to improve on existing approaches to modelling retail markets.Agents, Spatial Interaction Model, Retail Markets, Networks

Towards Real-Time Geodemographics: Clustering Algorithm Performance for Large Multidimensional Spatial Databases

and demographic characteristics of people living within small geographic areas. They have hitherto been regarded as products, which are the final “best” outcome that can be achieved using available data and algorithms. However, reduction in computational cost, increased network bandwidths and increasingly accessible spatial data infrastructures have together created the potential for the creation of classifications in near real time within distributed online environments. Yet paramount to the creation of truly real time geodemographic classifications is the ability for software to process and efficiency cluster large multidimensional spatial databases within a timescale that is consistent with online user interaction. To this end,this article evaluates the computational efficiency of a number of clustering algorithms with a view to creating geodemographic classifications “on the fly” at a range of different geographic scales.tgis_1197 283..29

Towards Real-Time Geodemographics: Clustering Algorithm Performance for Large Multidimensional Spatial Databases

and demographic characteristics of people living within small geographic areas. They have hitherto been regarded as products, which are the final “best” outcome that can be achieved using available data and algorithms. However, reduction in computational cost, increased network bandwidths and increasingly accessible spatial data infrastructures have together created the potential for the creation of classifications in near real time within distributed online environments. Yet paramount to the creation of truly real time geodemographic classifications is the ability for software to process and efficiency cluster large multidimensional spatial databases within a timescale that is consistent with online user interaction. To this end,this article evaluates the computational efficiency of a number of clustering algorithms with a view to creating geodemographic classifications “on the fly” at a range of different geographic scales.tgis_1197 283..29