Big data analytics and international market selection: An exploratory study

Abstract

<jats:p>A great deal of information is available on international trade flows and potentialmarkets. Yet many exporters do not know how to identify, with adequate precision, thosemarkets that hold the greatest potential. Even if they have access to relevant information, thesheer volume of information often makes the analytical process complex, time-consuming andcostly. An additional challenge is that many exporters lack an appropriate decision-makingmethodology, which would enable them to adopt a systematic approach to choosing foreignmarkets. In this regard, big-data analytics can play a valuable role. This paper reports on thefirst two phases of a study aimed at exploring the impact of big-data analytics on internationalmarket selection decisions. The specific big-data analytics system used in the study was theTRADE-DSM (Decision Support Model) which, by screening large quantities of marketinformation obtained from a range of sources identifies optimal product‒market combinationsfor a country, industry sector or company. Interviews conducted with TRADE-DSM users aswell as decision-makers found that big-data analytics (using the TRADE-DSM model) didimpact international market-decision. A case study reported on in this paper noted thatTRADE-DSM was a very important information source used for making the company’sinternational market selection decision. Other interviewees reported that TRADE-DSMidentified countries (that were eventually selected) that the decision-makers had not previouslyconsidered. The degree of acceptance of the TRADE-DSM results appeared to be influenced byTRADE-DSM user factors (for example their relationship with the decision-maker andknowledge of the organization), decision-maker factors (for example their experience andknowledge making international market selection decisions) and organizational factors (forexample senior managements’ commitment to big data and analytics). Drawing on the insightsgained in the study, we developed a multi-phase, big-data analytics model for internationalmarket selection.</jats:p>

Identifying export opportunities for China in the ‘Belt and Road Initiative’ group of countries: a decision support model approach

“…The DSM was originally designed to help export promotion agencies identify promising export opportunities and formulate suitable export promotion strategies (Cuyvers et al , 1995). The method has been applied for countries as diverse as Belgium (Cuyvers et al , 1995; Cuyvers et al , 2012a, Cuyvers and Viviers, 2012), Thailand (Cuyvers, 2004; Cuyvers et al , 2017), South Africa (Pearson et al , 2010), Greece (Kanellopoulos and Skintzi, 2016), the Czech Republic (Urban et al , 2014), Namibia (Teweldemedhin and Chiripanhura, 2015) and the USA (specifically Louisiana) (Oluwade, 2018), Furthermore, the TRADE-DSM has also been recognised as an important information source used by companies in their international market selection decisions as well as to develop a multi-phase, big data analytics model for international market selection (Calof and Viviers, 2020).…”

“…, Thailand(Cuyvers 2004;Cuyvers et al 2017), South Africa(Pearson et al 2010), Greece(Kanellopoulos and Skintzi 2016), the Czech Republic(Urban et al 2014), Namibia(Teweldemedhin and Chiripanhura 2015) and the USA (specifically Louisiana)(Oluwade 2018), Furthermore, the TRADE-DSM has also been recognised as an important information source used by companies in their international market selection decisions as well as to develop a multi-phase, big data analytics model for international market selection(Calof and Viviers 2020).As summarised in Figure1, the DSM methodology uses filters that sequentially eliminate less realistic/interesting product-country combinations with a view to categorising and prioritising REOs in different positions on a grid, for the country/firmcompany for which the analysis is applied.The first filter eliminates countries that pose too high a political and/or commercial risk to the exporting country and indicate inadequate size or economic growth. In this context the definition of Political political risk means to include any event in the importing country that assumes the nature of a force majeure incident (including wars, revolutions, natural disasters, unanticipated government actions) (ONDD 2014).…”

Impact of COVID 19 Pandemic and Big Data on China's International Trade: Challenges and Countermeasures

“…As the earnings of the people will be affected due to the strict lockdown norms, the governments will cut down the demands to meet the needs of the people who need support. This can lead to shrinkage of the demands, resulting in supply shocks ( 22 ). Most importantly, the spread of disease in a rapid manner discourages people from visiting supermarkets and other essential outlets, which can also lead to a shrinkage in demand.…”

International market selection: an application of hybrid multi-criteria decision-making technique in the textile sector

“…In this regard, selecting a new export market requires a sequential process that seeks to increase the probability of success of the company (Sakarya et al, 2007). The first phase of this process consists of obtaining and analyzing information on all feasible target markets, then studying the potential of these international buyers according to the needs of the companies (Cavusgil and Zou, 1994;Isa et al, 2014;Clark et al, 2018); and collecting a great volume of data (Calof and Viviers, 2020). Finally, the essential criteria of the target markets are compared with the strengths of the organization and an export plan is formulated with the markets having the highest final affinity (Lanzas and Moral, 2010;Pineda et al, 2012).…”