• Comprehensiveness versus pragmatism: Consensus at the Japanese-Dutch interface.

      Keizer, Arjan B.; Benders, J.G.J.M.; Noorderhaven, N.G. (2009-07-06)
      By comparing the views of managers working at the interface of two consensus-oriented societies, Japan and the Netherlands, we show important differences between the consensus decision-making processes as seen by Japanese and Dutch managers. These differences relate to how complete the agreement of opinion should be in order to speak of consensus, with the Japanese managers demanding a more complete consensus than the Dutch. The processes and conditions that Japanese and Dutch managers see as leading to consensus also differ. Japanese consensus is based on a more ordered, sequential process than Dutch consensus. Our respondents differed deeply regarding the role of the hierarchy in their own and the others consensus processes, with both Japanese and Dutch managers seeing their own consensus process as less hierarchical. Our findings show that the concept of consensus is interpreted quite differently by Japanese and Dutch managers. This is an important warning for companies operating at the interface of these two societies. More in general our research illustrates the usefulness for international management research of detailed comparative studies focusing not on stark contrasts but on more subtle differences between management practices.
    • Decision-making model for supply chain risk management in the petroleum industry

      Aroge, Olatunde O.; Rahmanian, Nejat; Munive-Hernandez, J. Eduardo; Abdi, Reza (2020)
      The purpose of this paper is to develop a decision-making model for supporting the management of risks in supply chain. This proposed model is applied to the case of the oil industry in Nigeria. A Partial Least Square Structural Equation Model (PLS-SEM) is developed to measure the significance of the influence of risk management strategy on mitigating disruption risks and their correlations with the performance of activities in the supply chain and relevance of key performance measures in the organisation. The model considered seven aspects: behavioural-based management strategy, buffer based oriented management strategy, exploration and production risks, environmental and regulatory compliance risks, geopolitical risks, supply chain performance, and organisational performance measures. A survey questionnaire was applied to collect data to populate the model, with 187 participants from the oil industry. Based on the PLS-SEM methodology, an optimised risk management decision-making method was developed and accomplished. The results show that behavioural-based mechanism predicts the capacity of the organisation to manage risks successfully in its supply chain. The approach proposed provides a new and practical methodology to manage disruption risks in supply chains. Further, the behavioural-based mechanism can help to formulate risk management strategies in the oil industry.
    • Is it too early to learn lessons from the developed world on the potential of big data technology: Harnessing and nurturing intuition in organisational decision makers

      Hussain, Zahid I.; Asad, M.; Chamas, H.B. (2017)
      As big data (BD) and data analytics gain significance in Europe, the industry expects that executives will eventually move towards evidence based decision making, and consequently would build sustainable competitive advantages for their organisations. Therefore, the lessons learned from experiences of European executives can be key for human development and also economic development. However, it also seems that in some cases decision makers in Europe seem to not use business intelligence systems at all. Since, executives are intelligent human beings with credible and proven expertise, it seems to raise a question mark on effectiveness of business intelligence systems, and the potential it has in human and economic development. Furthermore, repeated evaluation of literature pointed out that ultimately executives in Europe make decisions by intuition, and this leads to the question whether big data would ever replace intuition. In this paper, the mind-sets of executives about application and limitations of big data have been explored, by taking into account the cognitive factors in decision making. By using this, it is evaluated whether BD technologies can use to accelerate intuition development of the executives, and consequently lead to faster and sustainable economic development in the developing world.
    • A look at the potential of big data in nurturing intuition in organisational decision makers

      Hussain, Zahid I.; Asad, M. (2017)
      As big data (BD) and data analytics having gain significance the industry expects helping executives will eventually move towards evidence based decision making. The hope is to achieve more sustainable competitive advantage for their organisations. A key question is whether executives make decisions by intuition. This leads to another question whether big data would ever substitute human intuition. In this research, the ‘mind-set’ of executives about application and limitations of big data be investigated by taking into account their decision making behaviour. The aim is to look deeply into how BD technologies facilitate greater intuitiveness in executives, and consequently lead to faster and sustainable business growth.
    • What does Big Data has in-store for organisations: An Executive Management Perspective

      Hussain, Zahid I.; Asad, M.; Alketbi, R. (2017)
      With a cornucopia of literature on Big Data and Data Analytics it has become a recent buzzword. The literature is full of hymns of praise for big data, and its potential applications. However, some of the latest published material exposes the challenges involved in implementing Big Data (BD) approach, where the uncertainty surrounding its applications is rendering it ineffective. The paper looks at the mind-sets and perspective of executives and their plans for using Big Data for decision making. Our data collection involved interviewing senior executives from a number of world class organisations in order to determine their understanding of big data, its limitations and applications. By using the information gathered by this is used to analyse how well executives understand big data and how well organisations are ready to use it effectively for decision making. The aim is to provide a realistic outlook on the usefulness of this technology and help organisations to make suitable and realistic decisions on its investment. Professionals and academics are becoming increasingly interested in the field of big data (BD) and data analytics. Companies invest heavily into acquiring data, and analysing it. More recently the focus has switched towards data available through the internet which appears to have brought about new data collection opportunities. As the smartphone market developed further, data sources extended to include those from mobile and sensor networks. Consequently, organisations started using the data and analysing it. Thus, the field of business intelligence emerged, which deals with gathering data, and analysing it to gain insights and use them to make decisions (Chen, et al., 2012). BD is seem to have a huge immense potential to provide powerful information businesses. Accenture claims (2015) that organisations are extremely satisfied with their BD projects concerned with enhancing their customer reach. Davenport (2006) has presented applications in which companies are using the power of data analytics to consistently predict behaviours and develop applications that enable them to unearth important yet difficult to see customer preferences, and evolve rapidly to generate revenues.