Manufacturing operations location decision: what are the main criteria?

Spalanzani, Anne; Ageron, Blandine; Zouaghi, I.

doi:10.1080/16258312.2016.1240227

Cited by 7 publications

(8 citation statements)

References 19 publications

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“…It should be emphasised that the concept of attractiveness in the scientific literature has been analysed on/at different levels: on the level of company, branch of economy, city, region and country. The attractiveness of a location in regard to business development is usually analysed in two different aspects: from the perspective of the company, when the optimal solution, related to the selection process of the location eligible for the development of an activity, is assessed (Dub e, Brunelle & Legros, 2016;Frenkel, 2012;Giner, Santa-Mar ıa, & Fuster 2017;Goerzen, Asmussen, & Nielsen, 2013;Kimelberg & Nicoll, 2012;Kronenberg, 2013;Mota & Brandao, 2013;Ramadani, Zendeli, Gerguri-Rashiti, & Dana, 2018;Spalanzani et al, 2016), and globally, when analysing the attractiveness of specific locations for businesses by simply highlighting the factors that are attractive (Ambroziak, 2014;Arauzo-Carod et al, 2009;Bruneckien_ e et al, 2016;Crozet et al, 2004;Ezmale, 2016;Godlewska-Majkowska, 2013;Litavniece, 2014;Saez & Perianez, 2015;Strzelczyk, 2015). Academic works which analyse the cases of company decisions to act in a certain location stress the importance of market orientation, consumer behaviour and influencing factors (Schmidt, Touray, & Hansen, 2017).…”

Section: The Level Of Investigation Of the Research Problemmentioning

confidence: 99%

“…In the scientific literature, the concept of attractiveness is evaluated using different methods. Some scientists (Godlewska-Majkowska, 2013;Kosinova, Tolstel & Chekalkina, 2014;Nikolova & Plotnikova, 2013;Yatsenko, 2016) evaluate the attractiveness on the basis of separate statistical macroeconomic indicators and their dynamics, the others (Dub e et al, 2016;Frenkel, 2012;Giner et al, 2017;Kimelberg & Nicoll, 2012;Kronenberg, 2013;Mota & Brandao, 2013;Spalanzani et al, 2016) identify it according to the financial indicators of companies. The third group (De Noni et al, 2014;Glebova et al, 2015) analyse good examples.…”

Section: The Level Of Investigation Of the Research Problemmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of location’s attractiveness for business growth in smart development

Snieška

Zykienė

Burksaitiene

2019

Economic Research-Ekonomska Istraživanja

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The issue of a location's attractiveness for business development in literature lacks approach, when attractiveness is assessed not as a set of factors which determine individual attractiveness, but as a locality's ability to attract, maintain, and create business and investments. The contribution of the research to the discipline is a multi-criterion model of factors determining the location's attractiveness for business development in the context of smart growth, as a methodological tool to evaluate and analyse the scientific problem in a question which is proposed by us. The attractiveness of a location for business development in the model is combined with the concept of smart development. A new and reliable instrument for decision-makers and managers is presented. An example of panel data analysis of 36 indicators and 3600 observations from 10 cross-sections of annual data for determining the role of quantitative indicators in attractiveness index is provided and timing lags influence is assessed. The method proposed is suitable for the attractiveness analysis of any location if the necessary data is available.

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Section: The Level Of Investigation Of the Research Problemmentioning

confidence: 99%

Section: The Level Of Investigation Of the Research Problemmentioning

confidence: 99%

Evaluation of location’s attractiveness for business growth in smart development

Snieška

Zykienė

Burksaitiene

2019

Economic Research-Ekonomska Istraživanja

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“…However, it is often difficult to judge how far government incentives were the decisive factor for the location choice (Bartik, 2020), in particular because of the variety of direct and indirect ways in which government policies influence the decision. For example, Spalanzani, Ageron and Zouaghi (2016) found that the role of government was most influential in the development of the local territory's ‘business climate’, which includes global competitiveness and dynamism of the territory, as well as local labour. The importance of the role of local government in developing an entrepreneurial climate for clusters of innovation and enhancing the quality and availability of local labour has also been identified in other studies (Dziemianowicz, Lukomska, & Ambroziak, 2019; Ferras‐Hernandez & Nyland, 2019).…”

Section: Resultsmentioning

confidence: 99%

The influence of government upon multinational company manufacturing location decisions

Ekhart

Breese

2022

European Management Review

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With the rapid changes taking place in international manufacturing, there is a need for new theories linking the drivers for manufacturing location decisions to the influence of government. A Delphi study in 2017 of senior industrialists in Europe from capital intensive, complex technology manufacturing sectors provided evidence on the importance of government-specific factors for final location decisions. This was because of the influence of government policies as an exogenous factor on the drivers for international manufacturing, including cost effective, flexible supply chains and the use of the new technologies of Industry 4.0, in an uncertain global political climate. The findings are used to develop a new theoretical framework comprising the decision onion and the government policy matrix for multinational company manufacturing location decisions. This systematic approach to the influence of government will assist in the development of policy in the post-Covid 19 era of transformational change in industrial location strategies.

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“…It is true that the potential customers of a city is the top sub-criterion. Another interesting point is that skilled labour is considered less important than the impact of a city's government and policies, and this a novelty if it is compared with other studies [19,20], where this was a very important variable for location decisions. Moreover, the authors have also incorporated all factors related to the triple bottom line assumption of sustainability and these are gaining importance in the final rank compared with other recent decision support frameworks [21,114,122] as well.…”

Section: Discussionmentioning

confidence: 95%

Understanding Location Decisions of Energy Multinational Enterprises within the European Smart Cities’ Context: An Integrated AHP and Extended Fuzzy Linguistic TOPSIS Method

et al. 2020

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Becoming a smart city is one of the top priorities in the urban agenda of many European cities. Among the various strategies in the transition path, local governments seek to bring innovation to their cities by encouraging multinational enterprises to deploy their green energy services and products in their municipalities. Knowing how to attract these enterprises implies that political leaders understand the multi-criteria decision problem that the energy sector enterprises face when deciding whether to expand to one city or another. To this end, the purpose of this study is to design a new manageable and controllable framework oriented to European cities’ public managers, based on the assessment of criteria and sub-criteria governing the strategic location decision made by these enterprises. A decision support framework is developed based on the AHP technique combined with an extended version of the hesitant fuzzy linguistic TOPSIS method. The main results indicate the higher relative importance of government policies, such as degree of transparency or bureaucracy level, as compared to market conditions or economic aspects of the city’s host country. These results can be great assets to current European leaders, they show the feasibility of the method and open up the possibility to replicate the proposed framework to other sectors or geographical areas.

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Manufacturing operations location decision: what are the main criteria?

Cited by 7 publications

References 19 publications

Evaluation of location’s attractiveness for business growth in smart development

Evaluation of location’s attractiveness for business growth in smart development

The influence of government upon multinational company manufacturing location decisions

Understanding Location Decisions of Energy Multinational Enterprises within the European Smart Cities’ Context: An Integrated AHP and Extended Fuzzy Linguistic TOPSIS Method

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