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International Journal of Business Forecasting and Marketing Intelligence
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International Journal of Business Forecasting and Marketing Intelligence (3 papers in press)
Understanding the adoption of mobile marketing by small and medium enterprises of Pakistan by Zeeshan Iqbal, Maimoona Malik, Masood-ul Hassan Abstract: This study aimed to explore the mechanism of mobile marketing adoption intention by the small and medium enterprises of Pakistan. Based on the theoretical lens of technology-organisation-environment (TOE), the researchers examined the influence of top management support, novelty seeking management, competitors pressure and perceived cost on intention to adopt mobile marketing as promotional tool. A self-administrative survey questionnaire was adapted and distributed by using convenient sampling technique for data collection. Furthermore, PLS-SEM approach was employed to test the empirical relationships between the study constructs. The results revealed that top management support, novelty seeking management and competitors pressure have a positive influence on the intention to adopt mobile marketing. Moreover, perceived cost has negative association with intention to adopt mobile marketing by small and medium enterprises due to limited financial resources. Finally, the theoretical and practical implications, limitations and directions for future research were also discussed. Keywords: small and medium enterprises; mobile marketing; intention; technology-organization-environment; TOE; Pakistan. DOI: 10.1504/IJBFMI.2019.10019289
An Uncertain inventory model for deteriorating products with imperfections, variable selling price, partial backlogging and selling price dependent time varying demand by ARINDUM MUKHOPADHYAY Abstract: Imperfect items are unavoidable in inventory systems because of imperfect production, human-errors, damages, etc. In this competitive world, demand of a newly launched hi-tech products decreases over time because some better quality items are available in the market at the same or less price. This situation pushes the manufacturers to reduce selling price so that demand of that item may increase. Also many customers prefer to buy from other sellers when stock-out occurs. Keeping all these facts in mind, an inventory model is developed for imperfect items with decreasing selling price, waiting time dependent backlogging and selling price dependent time varying demand subject to constant deterioration rate adopting the techniques from uncertain programming, the above model is modified to an uncertain model with all the cost parameters as uncertain variables. Then the model is converted into equivalent expected value model and sensitivity of optimal policy is analysed. Keywords: Inventory; Partial Backlogging; Shortages; Deterioration; Imperfect quality; Uncertain Programming. DOI: 10.1504/IJBFMI.2019.10022309
VANFIS: virtual adaptive neuro-fuzzy inference system for modeling and forecasting stock data by Sarat Nayak, Bijan Misra Abstract: Random fluctuations take place in stock data. At fluctuation points, it is difficult to predict the next data points from the previous data. Close enough data points are more informative to the forecasting process but not available adequately. This article presents deterministic and stochastic methods for exploration of virtual data positions from actual data and incorporated to original dataset. An adaptive neuro-fuzzy inference system (ANFIS) is exposed to such virtual data positions and works in a virtual environment. The model is termed as VANFIS, i.e., virtual ANFIS and employed to infer future stock indices of real stock markets. The performance of VANFIS methods are validated using 15 years data from ten stock markets and using five metrics. Also, relative worth of proposed methods are carried out over ANFIS. Experimental results show the significant improvement in prediction accuracy when proposed methods adopted. Keywords: stock market forecasting; financial time series forecasting; Adaptive Network-based Fuzzy Inference System (ANFIS); virtual data position (VDP); linear extrapolation. DOI: 10.1504/IJBFMI.2019.10022518