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Finance-Led Growth and Growth-Led Finance: Evidence from Nigeria Economic and Financial Sector Development

Pages: 191-198
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Finance-Led Growth and Growth-Led Finance: Evidence from Nigeria Economic and Financial Sector Development

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DOI: 10.18488/journal.73.2019.74.191.198

Udo, Emmanuel Samuel , Akpan Ededem Jack , Abner, Ishaku Prince , Idogen, Kingsley , Ndubuaku, Victor

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Adeyeye, P.O., O. Fapetu and O.A. Aluko, 2015. Does the supply-leading hypothesis hold in a developing economy? A Nigerian Focus 3rd Economics & Finance Conference, Rome, Italy, April 14-17, 2015 and 4th Economics & Finance Conference, London, UK, August 25-28, 2015.

Al-Awad, M. and N. Harb, 2005. Financial development and economic growth in the Middle East. Applied Financial Economics, 15(15): 1041-1051.Available at: https://doi.org/10.1080/09603100500120639.

Beck, T. and R. Levine, 2004. Stock markets, banks, and growth: Panel evidence. Journal of Banking and, Finance, 28(3): 423-442.Available at: https://doi.org/10.1016/s0378-4266(02)00408-9.

Chuah, H. and V. Thai, 2004. Financial development and economic growth: Evidence from causality tests for the GCC countries. IMF Working Paper, No.04/XX.

Ehigiamusoe, K.U., H.H. Lean and R.A. Badeeb, 2017. Finance-growth Nexus in Cote D'Ivoire and Nigeria: Does the proxy of financial development matter?. Pertanika Journal of Social Sciences & Humanities, 25(1): 401-415.

Fosu, S.B., 2013. Financial development and economic growth in Africa: A dynamic causal relationship (Master of Arts in Economics Dissertation). New Hampshire: University of New Hampshire.

Grassa, R. and K. Gazdar, 2014. Financial development and economic growth in GCC countries: A comparative study between Islamic and conventional finance. International Journal of Social Economics, 41(6): 493-514.Available at: https://doi.org/10.1108/ijse-12-2012-0232.

Herwartz, H. and Y.M. Walle, 2014. Determinants of the link between financial and economic development: Evidence from a functional-coefficient model. Economic Modelling, 37: 417-427.

Kar, M., Ş. Nazlıoğlu and H. Ağır, 2011. Financial development and economic growth nexus in the MENA countries: Bootstrap panel granger causality analysis. Economic Modelling, 28(1-2): 685-693.Available at: https://doi.org/10.1016/j.econmod.2010.05.015.

Kennedy, K. and F. Nourzad, 2016. Exchange rate volatility and its effect on stock market volatility. International Journal of Human Capital in Urban Management, 1(1): 37-46.Available at: 10.7508/ijhcum.2016.01.005.

King, R.G. and R. Levine, 1993. Finance and growth: Schumpeter might be right. The Quarterly Journal of Economics, 108(3): 717-737.Available at: https://doi.org/10.2307/2118406.

Kolapo, F. and A. Adaramola, 2012. The impact of the Nigerian capital market on economic growth (1990-2010). International Journal of Developing Societies, 1(1): 11-19.

Madichie, C., A. Maduka, C. Oguanobi, and C. Ekesiobi, 2014. Financial development and economic growth in Nigeria: A reconsideration of empirical evidence. Journal of Economics and Sustainable Development, 5(28): 199-208.

Menyah, K., S. Nazlioglu and Y. Wolde-Rufael, 2014. Financial development, trade openness and economic growth in African countries: New insights from a panel causality approach. Economic Modelling, 37: 386-394.Available at: https://doi.org/10.1016/j.econmod.2013.11.044.

Mhadhbi, K., 2014. New proxy of financial development and economic growth in medium-income countries: A bootstrap panel granger causality analysis. American Journal of Applied Mathematics and Statistics, 2(4): 185-192.Available at: https://doi.org/10.12691/ajams-2-4-2.

Ndubuisi, P., 2017. An examination of the relationship between financial development and economic growth in Nigeria: Application of multivariate var framework. International Association of African Researchers and Reviewers, 2006-2017. Available from www.afrrevjo.net.

Nkoro, E. and A.K. Uko, 2013. Financial sector development-economic growth Nexus: Empirical evidence from Nigeria. American International Journal of Contemporary Research, 3(2): 87-94.

Onayemi, S., 2013. Output growth, economic openness and financial deepening in Nigeria: A structural differential and causality analyses. European Journal of Humanities and Social Sciences, 26(1): 1381-1395.

Pagano, M., 1993. Financial markets and growth: An overview. European Economic Review, 37(2-3): 613-622.

Patrick, H.T., 1966. Financial development and economic growth in underdeveloped countries. Economic Development and Cultural Change, 14(2): 174-189.Available at: https://doi.org/10.1086/450153.

Pesaran, M.H. and Y. Shin, 1999. An autoregressive distributed lag modeling approach to cointegration analysis. In Econometrics and Economic Theory in the 20th Century: The Ragnar Frish Centennial Symposium. Cambridge: Cambridge University Press. pp: 1-33.

Pesaran, M.H., Y. Shin and R.J. Smith, 2001. Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3): 289-326.Available at: https://doi.org/10.1002/jae.616.

Pradhan, R.P., M.B. Arvin, S. Bahmani, J.H. Hall and N.R. Norman, 2017. Finance and growth: Evidence from the ARF countries. The Quarterly Review of Economics and Finance, 66: 136-148.Available at: https://doi.org/10.1016/j.qref.2017.01.011.

Robinson, J.C., 1952. The generalisation of the general theory in the rate of interest and other essays. London: Macmillan Press.

Singh, A., 1999. Should Africa promote stock market capitalism?. Journal of International Development: The Journal of the Development Studies Association, 11(3): 343-365.Available at: https://doi.org/10.1002/(sici)1099-1328(199905/06)11:3<343::aid-jid593>3.0.co;2-q.

Sunde, T., 2013. Financial development and economic growth: Empirical evidence from Namibia (1990Q1-2011Q4). Journal of Emerging Issues in Economics, Finance, and Banking, 1(1): 52-65.

Torruam, J.T., M.A. Chiawa, and C.C. Abur, 2013. Financial deepening and economic growth in Nigeria: An application of co-integration and causality analysis. 3rd International Conference on Intelligent Computational Systems, April 29-30, Singapore.

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Udo, Emmanuel Samuel , Akpan Ededem Jack , Abner, Ishaku Prince , Idogen, Kingsley , Ndubuaku, Victor (2019). Finance-Led Growth and Growth-Led Finance: Evidence from Nigeria Economic and Financial Sector Development. Humanities and Social Sciences Letters, 7(4): 191-198. DOI: 10.18488/journal.73.2019.74.191.198
This study investigates the cause-effect relationship between financial sector development and economic growth; in Nigeria through supply-led growth and demand-led growth models. Annualized time-series data extracted from the Central Bank of Nigeria Bulletin from 1999 to 2017 were used in the investigation. The supply-led growth model assumes that financial sector development granger causes economic growth. The demand-led growth model assumes that economic growth Granger causes financial sector growth. Estimating the cause-effect relationship the Autoregressive Distributed Lag (ARDL), and Pairwise Granger Causality was adopted. Findings revealed that the causal relationship is influenced by the stages and level of economic and financial sector growth through the appropriate policy mixes, of the regulators and monetary authorities. The Error Correction Model (ECM) adjusts for disequilibrium caused by the financial and economic factors of lack of economic value, chain effect of export goods, saving-investment gap, and decrease in capital productivity, back to equilibrium at 37% annually. Both the supply-led growth and demand-led growth models hold in Nigeria. The findings differ from previous studies in Nigeria and report that the causality between finance and economic growth is based on stages and the level of economic and financial sector growth and development. The study also supports the argument of Patrick (1966).
Contribution/ Originality
This study contributes to the extant literature by investigating the cause-effect relationship between the financial sector development and economic growth, through the supply-led growth and demand-led growth models in Nigeria from 1999 to 2017.

The Mediating Role of E-Satisfaction on the Effect of E-Service Quality Dimensions on E-Loyalty: A Lesson from Bukalapak.Com Indonesia

Pages: 199-208
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The Mediating Role of E-Satisfaction on the Effect of E-Service Quality Dimensions on E-Loyalty: A Lesson from Bukalapak.Com Indonesia

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DOI: 10.18488/journal.73.2019.74.199.208

Hermansyah Andi Wibowo

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Al-dweeri, R.M., Z.M. Obeidat, M.A. Al-dwiry, M.T. Alshurideh and A.M. Alhorani, 2017. The impact of e-service quality and e-loyalty on online shopping: Moderating effect of e-satisfaction and e-trust. International Journal of Marketing Studies, 9(2): 92-103.Available at: https://doi.org/10.5539/ijms.v9n2p92.

Alam, S.S. and N.M. Yasin, 2010. An investigation into the antecedents of customer satisfaction of online shopping. Journal of Marketing Development and Competitiveness, 5(1): 71-78.

Anderson, R.E. and S.S. Srinivasan, 2003. E-satisfaction and e-loyalty: A contingency framework. Psychology & Marketing, 20(2): 123-138.Available at: https://doi.org/10.1002/mar.10063.

APJII, 2017. Penetration & behavior of Indonesian internet users - Survey 2017. Indonesian Internet Service Providers Association. Available from https://web.kominfo.go.id/sites/default/files/Laporan Survei APJII_2017_v1.3.pdf.

Aryani, D. and F. Rosinta, 2010. Effect of service quality on customer satisfaction in forming customer loyalty. Journal of Administrative and Organizational Sciences, 17(2): 114-126.

Bukhari, S., A. Ghoneim and C. Dennis, 2012. Understanding the factors that attract travellers to buy airline tickets online in Saudi Arabia. European, Mediterranean & Middle Eastern Conference on Information Systems 2012, (June 2017). Munich Germany.

Bukhari, S.M.F., A. Ghoneim, C. Dennis and B. Jamjoom, 2013. The antecedents of travellers'e-satisfaction and intention to buy airline tickets online: A conceptual model. Journal of Enterprise Information Management, 26(6): 624-641.

Chiou, J.-S., L.-Y. Wu and Y.-P. Sung, 2009. Buyer satisfaction and loyalty intention in online auctions: Online auction web site versus online auction seller. Journal of Service Management, 20(5): 521-543.Available at: https://doi.org/10.1108/09564230910995125.

Eid, M.I., 2011. Determinants of e-commerce customer satisfaction, trust, and loyalty in Saudi Arabia. Journal of Electronic Commerce Research, 12(1): 78-93.

Francis, T. and F. Hoefel, 2018. Generation Z characteristics and its implications for companies | McKinsey. McKinsey and Company. Available from https://www.mckinsey.com/industries/consumer-packaged-goods/our-insights/true-gen-generation-z-and-its-implications-for-companies.

Gee, R., G. Coates and M. Nicholson, 2008. Understanding and profitably managing customer loyalty. Marketing Intelligence & Planning, 26(4): 359-374.Available at: https://doi.org/10.1108/02634500810879278.

Guo, X., K.C. Ling and M. Liu, 2017. Evaluating factors influencing consumer satisfaction towards online shopping in China. Asian Social Science, 8(13): 40-50.

Hair, J.J.F., W.C. Black, B.J. Babin and R.E. Anderson, 2014. Multivariate data analysis. 7th Edn.: Pearson New International Edition, 259. Available from www.pearsoned.co.uk.

Iskana, F.R., 2015. This is bukalapak.Com's strategy to be number one. Available from https://m.kontan.co.id/news/ini-strategi-bukalapakcom-agar-jadi-nomor-satu.

Lin, G.T. and C.-C. Sun, 2009. Factors influencing satisfaction and loyalty in online shopping: An integrated model. Online Information Review, 33(3): 458-475.Available at: https://doi.org/10.1108/14684520910969907.

Loiacono, E., R.T. Watson and D. Goodhue, 2002. Web QualTM: A web site quality instrument. American Marketing Association: Winter Marketing Educators’ Conference, (January 2002), pp: 1–12.

Ningrum, D.W., 2015. 10 situs e-commerce paling laris, bukalapak.Com nomor 1. Available from http://tekno.liputan6.com/read/2323611/10-situs-e-commerce-paling-laris-bukalapakcom-nomor-1.

Parasuraman, A., V.A. Zeithaml and A. Malhotra, 2005. ES-QUAL: A multiple-item scale for assessing electronic service quality. Journal of Service Research, 7(3): 213-233.Available at: https://doi.org/10.1177/1094670504271156.

Quan, S., 2010. Assessing the effects of e-service quality and esatisfaction on internet banking loyalty in China. Proceedings of the International Conference on E-Business and E-Government, ICEE 2010. pp: 93–96.

Reichheld, F.F. and P. Schefter, 2000. E-loyalty: Your secret weapon on the web. Harvard Business Review, 78(4): 105-113.

Ting, O.S., M. Ariff, M. Shoki, N. Zakuan and Z. Sulaiman, 2016. Relationship between e-service quality, e-satisfaction and e-loyalty in B2C e-commerce. Advanced Science, Engineering and Medicine, 8(10): 819-825.Available at: https://doi.org/10.1166/asem.2016.1935.

Tjiptaningsih, D.S. and L. Aryani, 2014. The effect of service quality and customer satisfaction on customer loyalty (case study in fast pizza fast food restaurant in South Jakarta). Online Journal & Proceeding of General Soedirman University, 4(1): 202-215.

Wendha, A.A.A.A.P., I.K. Rahyuda and I.G.A. Suasana, 2013. Influence of service quality on garuda Indonesia customer satisfaction and loyalty in Denpasar. Journal of Management, Business Strategy, and Entrepreneurship, 7(1): 19-28.

Wibowo, H.A., 2016. The important role of service quality and campus image in forming satisfaction and loyalty of PTS students X failure to switch costs. Journal of Management Science, 2(2): 105–116.

Wibowo, H.A. and M.J. Widikusyanto, 2017. The role of cost switches to the classical relationship of service quality, satisfaction, and customer loyalty in the higher education industry. (Study at PTS X). Management Science, 2(1): 1-12.

Wijanto, S.H., 2008. Structural equation modeling dengan lisrel 8.8 konsep & tutorial. 1st Edn., Yogyakarta: Graha Ilmu.

Wolfinbarger, M. and M.C. Gilly, 2003. Etailq: Dimensionalizing, measuring and predicting etail quality. Journal of Retailing, 79(3): 183-198.

World Bank, 2019. Individuals using the internet (% of population). Available from https://data.worldbank.org/indicator/ it.net.user.zs.

Yang, H., 2007. Assessing the effects of e-quality and e-satisfaction on website loyalty. International Journal of Mathematics and Computers in Simulation, 1(3): 288–294.

Yang, H. and F.-S. Tsai, 2007. General E-S-QUAL scales applied to websites satisfaction and loyalty model. Communications of the IIMA, 7(2): 115–126.

Yanmie, L.N.Y. and M.K.K. Ching, 2012. Factors affecting Hong Kong customer’s E-loyalty and repeated purchase intention in online Chinese retail stores and the moderating efect of Electronic word-of-mouth. Hong Kong Baptist University.

Yao, C. and S. Liao, 2011. Measuring the antecedent effects of service cognition and internet shopping anxiety on consumer satisfaction with e-tailing service. Management & Marketing Challenges for the Knowledge Society, 6(135): 59–78.

Yoo, B. and N. Donthu, 2001. Developing a scale to measure the perceived quality of an internet shopping site (sitequal). Quarterly Journal of Electronic Commerce, 2(1): 31-45.

Zavareh, F.B., M.S.M. Ariff, A. Jusoh, N. Zakuan, A.Z. Bahari and M. Ashourian, 2012. E-service quality dimensions and their effects on e-customer satisfaction in internet banking services. Procedia-Social and Behavioral Sciences, 40: 441-445.

Zhang, X. and V.R. Prybutok, 2005. A consumer perspective of e-service quality. IEEE transactions on Engineering Management, 52(4): 461-477.Available at: https://doi.org/10.1109/tem.2005.856568.

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Hermansyah Andi Wibowo (2019). The Mediating Role of E-Satisfaction on the Effect of E-Service Quality Dimensions on E-Loyalty: A Lesson from Bukalapak.Com Indonesia. Humanities and Social Sciences Letters, 7(4): 199-208. DOI: 10.18488/journal.73.2019.74.199.208
This study examines the role of electronic satisfaction mediation on the effect of electronic service quality dimensions on electronic customer loyalty. Bukalapak.com was ranked ninth of the most popular sites accessed from Indonesia. Bukalapak.com is aggressively promoting and improving the quality of its services. However, the dimensions of electronic services quality that affect the behavior of its customers are still unclear. Research focusing on the effects of the dimensions of electronic service quality mediated by electronic satisfaction is still scarce. Therefore, we offer new insights on how the latest types of interactions must be maintained. We applied Structural Equation Modelling for hypothesis testing. This study found evidence that three dimensions of electronic service quality (privacy, web design, and compensation) have been shown to influence electronic loyalty which is mediated by electronic satisfaction. This influence is positive and pure mediation. The theoretical implication of this research is the need to prioritize a human aspect to an e-marketplace context. Even though these implications need to be tested in a broader context of population, the practical implications of this research are important incentives for e-marketplace sites such as bukalapak.com, tokopedia.com, lazada.com, etc., to pay attention to human aspects of their services to gain customer satisfaction and loyalty.
Contribution/ Originality
The main contribution of this paper is finding that the human aspects of users were the most important part of e-service quality to gain customer satisfaction and loyalty in the e-marketplace industry.

Triad of Big Data Supply Chain Analytics, Supply Chain Integration and Supply Chain Performance: Evidences from Oil and Gas Sector

Pages: 209-224
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Triad of Big Data Supply Chain Analytics, Supply Chain Integration and Supply Chain Performance: Evidences from Oil and Gas Sector

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DOI: 10.18488/journal.73.2019.74.209.224

Mobashar Mubarik , Raja Zuraidah binti Raja Mohd Rasi

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Accenture Global Operations Megatrends Study, 2014. Big data analytics in supply chain: Hype or here to stay? Available from http://www.accenture.com/us-en/Pages/insight-global-operations-megatrends-big-data-analytics.aspx [Accessed November 17, 2019].

Agrawal, N. and S. Sharma, 2012. Application of fuzzy techniques in a multistage manufacturing system. The International Journal of Advanced Manufacturing Technology, 60(1-4): 397-407.Available at: https://doi.org/10.1007/s00170-011-3607-9.

Apte, A.U., R.G. Rendon and J. Salmeron, 2011. An optimization approach to strategic sourcing: A case study of the United States Air Force. Journal of Purchasing and Supply Management, 17(4): 222-230.Available at: https://doi.org/10.1016/j.pursup.2011.03.002.

Barnaghi, P., A. Sheth and C. Henson, 2013. From data to actionable knowledge: Big data challenges in the web of things. IEEE Intelligent Systems(6): 6-11.Available at: https://doi.org/10.1109/mis.2013.142.

Bibri, S.E., 2019. On the sustainability of smart and smarter cities in the era of big data: An interdisciplinary and transdisciplinary literature review. Journal of Big Data, 6(1): 6-25.

Borade, A.B., G. Kannan and S.V. Bansod, 2013. Analytical hierarchy process-based framework for VMI adoption. International Journal of Production Research, 51(4): 963-978.Available at: https://doi.org/10.1080/00207543.2011.650795.

Bressolles, G. and G. Lang, 2019. KPIs for performance measurement of e-fulfillment systems in multi-channel retailing. International Journal of Retail & Distribution Management.

Casino, F., T.K. Dasaklis and C. Patsakis, 2018. A systematic literature review of blockchain-based applications: Current status, classification and open issues. Telematics and Informatics, 36(1): 55-81.

Chai, J. and E.W. Ngai, 2015. Multi-perspective strategic supplier selection in uncertain environments. International Journal of Production Economics, 166: 215-225.Available at: https://doi.org/10.1016/j.ijpe.2014.09.035.

Chen, A. and J. Blue, 2010. Performance analysis of demand planning approaches for aggregating, forecasting and disaggregating interrelated demands. International Journal of Production Economics, 128(2): 586-602.

Chen, H., R.H. Chiang and V.C. Storey, 2012. Business intelligence and analytics: From big data to big impact. MISQ, 4(36): 1165–1188.

Choi, T.-M., 2013. Optimal apparel supplier selection with forecast updates under carbon emission taxation scheme. Computers & Operations Research, 40(11): 2646-2655.Available at: https://doi.org/10.1016/j.cor.2013.04.017.

Downing, M., M. Chipulu, U. Ojiako and D. Kaparis, 2014. Advanced inventory planning and forecasting solutions: A case study of the UKTLCS Chinook maintenance programme. Production Planning & Control, 25(1): 73-90.Available at: https://doi.org/10.1080/09537287.2012.658451.

Drexl, M., 2012. Applications of the vehicle routing problem with trailers and transshipments. European Journal of Operational Research, 227(2): 275-283.

Ekici, A., 2013. An improved model for supplier selection under capacity constraint and multiple criteria. International Journal of Production Economics, 141(2): 574-581.Available at: https://doi.org/10.1016/j.ijpe.2012.09.013.

Fernandes, R., B. Gouveia and C. Pinho, 2013. Integrated inventory valuation in multi-echelon production/distribution systems. International Journal of Production Research, 51(9): 2578-2592.Available at: https://doi.org/10.1080/00207543.2012.737947.

Genpact, 2014. Bartels, N., Beyond pricing and procurement: maturing technology, globali- zation, and a seller's market shift focus in supplier  management to analytics, risk, and collaboration. Manuf. Bus. Technol, 24(6): 32–34.

Guerrero, W.J., T. Yeung and C. Guéret, 2013. Joint-optimization of inventory policies on a multi-product multi-echelon pharmaceutical system with batching and ordering constraints. European Journal of Operational Research, 231(1): 98-108.Available at: https://doi.org/10.1016/j.ejor.2013.05.030.

Gumus, A.T., A.F. Guneri and F. Ulengin, 2010. A new methodology for multi-echelon inventory management in stochastic and neuro-fuzzy environments. International Journal of Production Economics, 128(1): 248-260.Available at: https://doi.org/10.1016/j.ijpe.2010.06.019.

Gunasekaran, A., T. Papadopoulos, R. Dubey, S.F. Wamba, S.J. Childe, B. Hazen and S. Akter, 2017. Big data and predictive analytics for supply chain and organizational performance. Journal of Business Research, 70(1): 308-317.

Guo, C. and X. Li, 2014. A multi-echelon inventory system with supplier selection and order allocation under stochastic demand. International Journal of Production Economics, 151: 37-47.Available at: https://doi.org/10.1016/j.ijpe.2014.01.017.

Hair, J.J.F., L.M. Matthews, R.L. Matthews and M. Sarstedt, 2017. PLS-SEM or CB-SEM: Updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2): 107-123.Available at: https://doi.org/10.1504/ijmda.2017.10008574.

Hazen, B.T., R.E. Overstreet and C.G. Cegielski, 2012. Supply chain innovation diffusion: Going beyond adoption. The International Journal of Logistics Management, 23(1): 119-134.Available at: https://doi.org/10.1108/09574091211226957.

Ho, W., T. He, C.K.M. Lee and A. Emrouznejad, 2012. Strategic logistics outsourcing: An integrated QFD and fuzzy AHP approach. Expert Systems with Applications, 39(12): 10841-10850.Available at: https://doi.org/10.1016/j.eswa.2012.03.009.

Ho, W., X. Xu and P.K. Dey, 2010. Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1): 16-24.Available at: https://doi.org/10.1016/j.ejor.2009.05.009.

Jain, S., E. Lindskog, J. Andersson and B. Johansson, 2013. A hierarchical approach for evaluating energy trade-offs in supply chains. International Journal of Production Economics, 146(2): 411-422.Available at: https://doi.org/10.1016/j.ijpe.2013.03.015.

Kabak, M. and S. Burmaoğlu, 2013. A holistic evaluation of the e-procurement website by using a hybrid MCDM methodology. Electronic Government, an International Journal, 10(2): 125-150.Available at: https://doi.org/10.1504/eg.2013.052598.

Kaliani, S.V.P., V. Chandran and M. Awais Bhatti, 2016. Supply chain practices and performance: The indirect effects of supply chain integration. Benchmarking: An International Journal, 23(6): 1445-1471.Available at: https://doi.org/10.1108/bij-03-2015-0023.

Khan, K., 2013. The transformative power of advanced analytics. Supply Chain Management Review, 17(3): 48-49.

Lapide, L., 2000. What about measuring supply chain performance. Achieving Supply Chain Excellence Through Technology, 2(2): 287-297.

Leung, J.Y.-T. and Z.-L. Chen, 2013. Integrated production and distribution with fixed delivery departure dates. Operations Research Letters, 41(3): 290-293.Available at: https://doi.org/10.1016/j.orl.2013.02.006.

Li, B., H. Wang, J. Yang, M. Guo and C. Qi, 2013. A belief-rule-based inference method for aggregate production planning under uncertainty. International Journal of Production Research, 51(1): 83-105.Available at: https://doi.org/10.1080/00207543.2011.652262.

Li, L., F. Liu and C. Li, 2014. Customer satisfaction evaluation method for customized product development using entropy weight and analytic hierarchy process. Computers & Industrial Engineering, 77: 80-87.Available at: https://doi.org/10.1016/j.cie.2014.09.009.

Li, Q. and A. Liu, 2019. Big data driven supply chain management. Procedia CIRP, 81: 1089-1094.Available at: https://doi.org/10.1016/j.procir.2019.03.258.

Liang, H., N. Saraf, Q. Hu and Y. Xue, 2007. Assimilation of enterprise systems: The effect of institutional pressures and the mediating role of top management MIS Quarterly, 31(1): 59-87.

Liu, Z., D.K.H. Chua and K.-W. Yeoh, 2011. Aggregate production planning for shipbuilding with variation-inventory trade-offs. International Journal of Production Research, 49(20): 6249-6272.Available at: https://doi.org/10.1080/00207543.2010.527388.

Luo, W., Y. Shi and V. Venkatesh, 2018. Exploring the factors of achieving supply chain excellence: A New Zealand perspective. Production Planning & Control, 29(8): 655-667.Available at: https://doi.org/10.1080/09537287.2018.1451004.

Minis, I. and A. Tatarakis, 2011. Stochastic single vehicle routing problem with delivery and pick up and a predefined customer sequence. European Journal of operational research, 213(1): 37-51.Available at: https://doi.org/10.1016/j.ejor.2011.03.011.

Mirzapour, A.-E.-H.S., H. Malekly and M. Aryanezhad, 2011. A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty. International Journal of Production Economics, 134(1): 28-42.Available at: https://doi.org/10.1016/j.ijpe.2011.01.027.

Mishra, A.N., S. Devaraj and G. Vaidyanathan, 2013. Capability hierarchy in electronic procurement and procurement process performance: An empirical analysis. Journal of Operations Management, 31(6): 376-390.Available at: https://doi.org/10.1016/j.jom.2013.07.011.

Moktadir, M.A., S.M. Ali, S.K. Paul and N. Shukla, 2019. Barriers to big data analytics in manufacturing supply chains: A case study from Bangladesh. Computers & Industrial Engineering, 128: 1063-1075.Available at: https://doi.org/10.1016/j.cie.2018.04.013.

Mubarak, F., M. Shujaat and N. Naghavi, 2019. Impact of supplier relational capital on supply chain performance in Pakistani textile industry. Asian Economic and Financial Review, 9(3): 318-328.Available at: https://doi.org/10.18488/journal.aefr.2019.93.318.328.

Mubarik, M.S., V. Chandran and E.S. Devadason, 2018. Measuring human capital in small and medium manufacturing enterprises: What matters? Social Indicators Research, 137(2): 605-623.Available at: https://doi.org/10.1007/s11205-017-1601-9.

Mubarik, M.S., C. Govindaraju and E.S. Devadason, 2016. Human capital development for SMEs in Pakistan: Is the “one-size-fits-all” policy adequate?. International Journal of Social Economics, 43(8): 804-822.Available at: https://doi.org/10.1108/ijse-02-2015-0033.

Mubarik, M.S., N. Naghavi and R.T. Mahmood, 2019. Intellectual capital, competitive advantage and the ambidexterity liaison. Human Systems Management, 38(3): 267-277.Available at: https://doi.org/10.3233/hsm-180409.

Mubarik, S., N. Naghavi and M. Faraz, 2019. Governance-led intellectual capital disclosure: Empirical evidence from Pakistan. Humanities, 7(3): 141-155.Available at: https://doi.org/10.18488/journal.73.2019.73.141.155.

Mubarik, S., A.Z. Warsi, M. Nayaz and T. Malik, 2012. Transportation outsourcing and supply chain performance: A study of Pakistan’s pharmaceutical industry. South Asian Journal of Management, 6(2): 35-41.

Muhtaroglu, F.C.P., S. Demir, M. Obali and C. Girgin, 2013. Business model canvas perspective on big data applications, In: Proceedings of the IEEE International Conference on Big Data. pp: 32–36.

Najafi, M. and R.Z. Farahani, 2013. New forecasting insights on the bullwhip effect in a supply chain. IMA Journal of Management Mathematics, 25(3): 259-286.Available at: https://doi.org/10.1093/imaman/dpt007.

Nakatani, K. and T.-T. Chuang, 2011. A web analytics tool selection method: An analytical hierarchy process approach. Internet Research, 21(2): 171-186.Available at: https://doi.org/10.1108/10662241111123757.

Oruezabala, G. and J.-C. Rico, 2012. The impact of sustainable public procurement on supplier management—The case of French public hospitals. Industrial Marketing Management, 41(4): 573-580.Available at: https://doi.org/10.1016/j.indmarman.2012.04.004.

Ozdamar, L. and O. Demir, 2012. A hierarchical clustering and routing procedure for large scale disaster relief logistics planning. Transportation Research Part E: Logistics and Transportation Review, 48(3): 591-602.Available at: https://doi.org/10.1016/j.tre.2011.11.003.

Peterson, R.A., 1994. A meta-analysis of Cronbach's coefficient alpha. Journal of Consumer Research, 21(2): 381-391.

Rajesh, G. and P. Malliga, 2013. Supplier selection based on AHP QFD methodology. Procedia Engineering, 64: 1283-1292.Available at: https://doi.org/10.1016/j.proeng.2013.09.209.

Sage, 2013. Better inventory management: Big challenges, big data, emerging solutions. Available from http://na.sage.com/media/site/erp/responsive/resources/Sage-ERP-Better-Inventory-Management-wp.pdf [Accessed 09.11.2018].

Scott, J.A., W. Ho and P.K. Dey, 2013. Strategic sourcing in the UK bioenergy industry. International Journal of Production Economics, 146(2): 478-490.Available at: https://doi.org/10.1016/j.ijpe.2013.01.027.

Shen, Y. and S.P. Willems, 2012. Strategic sourcing for the short-lifecycle products. International Journal of Production Economics, 139(2): 575-585.Available at: https://doi.org/10.1016/j.ijpe.2012.05.032.

Siva, V., 2012. Improvement in product development: Use of back-end data to support upstream efforts of robust design methodology. Quality Innovation Prosperity, 16(2): 84-102.Available at: https://doi.org/10.12776/qip.v16i2.65.

Song, G.-Y., Y. Cheon, K. Lee, H. Lim, K.-Y. Chung and H.-C. Rim, 2014. Multiple categorizations of products: Cognitive modeling of customers through social media data mining. Personal and Ubiquitous Computing, 18(6): 1387-1403.Available at: https://doi.org/10.1007/s00779-013-0740-5.

Souza, G.C., 2014. Supply chain analytics. Business Horizons, 57(5): 595-605.

Srinivasan, R., G.L. Lilien, A. Rangaswamy, G.M. Pingitore and D. Seldin, 2012. The total product design concept and an application to the auto market. Journal of Product Innovation Management, 29: 3-20.Available at: https://doi.org/10.1111/j.1540-5885.2012.00958.x.

Subramanian, N. and R. Ramanathan, 2012. A review of applications of analytic hierarchy process in operations management. International Journal of Production Economics, 138(2): 215-241.

Swaminathan, S., 2012. The effects of big data on the logistics industry. Available from http:// www.oracle.com/us/corporate/profit/archives/opinion/021512-sswaminathan- 1523937.html [Accessed 20.11.19].

Tseng, P.-H. and C.-H. Liao, 2015. Supply chain integration, information technology, market orientation and firm performance in container shipping firms. The International Journal of Logistics Management, 26(1): 82-106.Available at: https://doi.org/10.1108/ijlm-09-2012-0088.

Vidal, T., T.G. Crainic, M. Gendreau and C. Prins, 2013. Heuristics for multi-attribute vehicle routing problems: A survey and synthesis. European Journal of operational research, 231(1): 1-21.Available at: https://doi.org/10.1016/j.ejor.2013.02.053.

Walker, H. and S. Brammer, 2012. The relationship between sustainable procurement and e-procurement in the public sector. International Journal of Production Economics, 140(1): 256-268.Available at: https://doi.org/10.1016/j.ijpe.2012.01.008.

Waller, M.A. and S.E. Fawcett, 2013. Data science, predictive analytics, and big data: A revolution that will transform supply chain design and management. Journal of Business Logistics, 34(2): 77-84.Available at: https://doi.org/10.1111/jbl.12010.

Wamba, S.F., S. Akter, A. Edwards, G. Chopin and D. Gnanzou, 2015. How ‘big data’can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165: 234-246.Available at: https://doi.org/10.1016/j.ijpe.2014.12.031.

Wang, G. and L. Lei, 2012. Polynomial-time solvable cases of the capacitated multi-echelon shipping network scheduling problem with delivery deadlines. International Journal of Production Economics, 137(2): 263-271.Available at: https://doi.org/10.1016/j.ijpe.2012.02.006.

Wang, G. and L. Lei, 2015. Integrated operations scheduling with delivery deadlines. Computers & Industrial Engineering, 85: 177-185.Available at: https://doi.org/10.1016/j.cie.2015.03.015.

Wei, C., Y. Li and X. Cai, 2011. Robust optimal policies of production and inventory with uncertain returns and demand. International Journal of Production Economics, 134(2): 357-367.Available at: https://doi.org/10.1016/j.ijpe.2009.11.008.

Yeniyurt, S., J.W. Henke Jr and E. Cavusgil, 2013. Integrating global and local procurement for superior supplier working relations. International Business Review, 22(2): 351-362.Available at: https://doi.org/10.1016/j.ibusrev.2012.06.004.

Zeotmulder, E., 2014. Good data, better procurement, summit: Bus. Public Sector Procurement, 17(1): 8–11.

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Mobashar Mubarik , Raja Zuraidah binti Raja Mohd Rasi (2019). Triad of Big Data Supply Chain Analytics, Supply Chain Integration and Supply Chain Performance: Evidences from Oil and Gas Sector. Humanities and Social Sciences Letters, 7(4): 209-224. DOI: 10.18488/journal.73.2019.74.209.224
The objective of the paper is to examine the impact of big data supply chain analytics on supply chain performance. Second, study also examines the role of supply chain integration in the association between big data supply chain analytics and supply chain performance. The data were collected from 166 experts working in Oil and Gas Marketing companies. The experts were selected through expert sampling, a sub case of purposive sampling. We employed covariance based structural equation modeling to estimate the modelled relationships. The results of measurement model indicated the reliability, validity and fitness of measurement models. The findings of the study revealed a significant direct impact of big data supply chain analytics upon the five major dimensions of supply chain i.e., plan, supplier management, procurement management, make, and inventory management. Whereas the results did not show any effect of BDSCA on transportation management. Likewise, findings also revealed that distribution and network designing part of supply chain could be radically improved with the application of BDSCA. The study concludes that despite sea-potential of BDSCA in supply chain management field, the research work in this area is yet in infancy stage. Primarily, the research work aiming to know the level of BDSCA orientation and its application strategy requires immediate attention of the researchers and practitioners.
Contribution/ Originality
The study contributes to the literature on BDSCA-supply chain performance association in two ways. First it provides empirical evidences on the association of BDSCA and supply chain performance. Second, it clarifies the role of supply chain integration in the association between BDSCA and supply chain performance.

Short-Run Dynamics between Trading Participants in Bursa Malaysia During QE and Post-QE Exit

Pages: 225-237
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DOI: 10.18488/journal.73.2019.74.225.237

Wee-Yeap Lau , Tien-Ming Yip

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Wee-Yeap Lau , Tien-Ming Yip (2019). Short-Run Dynamics between Trading Participants in Bursa Malaysia During QE and Post-QE Exit. Humanities and Social Sciences Letters, 7(4): 225-237. DOI: 10.18488/journal.73.2019.74.225.237
This study investigates the trading dynamics between institutional, foreign and retail investors during Quantitative Easing (QE) Tapering and post-QE exit. An analytical framework is developed to classify all transactions into trading, short-selling or information flow. Notably our results show: Firstly, during QE tapering, there is short-selling by Foreign Investor. Foreign Sales also provides cue to Local Institutional Sales. Net buyers are Local Institution; Secondly, in Post-QE exit, Foreign Sales is the most endogenous variable. Net sellers are Foreign, followed by Local Retail; Thirdly, from 7 to 12 months in Post-QE exit, there are short-selling by Foreign and Local Institution corresponding to sharp market downtrend. Net sellers are Foreign and Retail. Overall, Local Institutional is the net buyer in all sub-periods while Foreign fund is the net seller during Post-QE periods. Our result recognizes the importance of Local Institutional Investors in withstanding the selling pressure of foreign investors during the QE exit periods. This paper contributes to the extant literature by providing the usefulness of trading participant statistics to market players in the backdrop of market uncertainty due to QE exit.
Contribution/ Originality
This study contributes to the existing literature of trading participant statistics from emerging market during QE and Post-QE periods. Using econometric modelling, this is the first study that analyses the trading dynamics of buying, selling, information flow and short-selling between different market participants in Malaysian stock exchange.